tokens
list | ner_tags
list |
|---|---|
[
"This",
"paper",
"describes",
"the",
"participation",
"of",
"the",
"IRIT",
"team",
"in",
"the",
"TRAC",
"(Trolling,",
"Aggression",
"and",
"Cyberbullying)",
"2020",
"shared",
"task",
"(Bhattacharya",
"et",
"al.,",
"2020)",
"on",
"Aggression",
"Identification",
"and",
"more",
"precisely",
"to",
"the",
"shared",
"task",
"in",
"English",
"language.",
"The",
"shared",
"task",
"was",
"further",
"divided",
"into",
"two",
"sub-tasks:",
"(a)",
"aggression",
"identification",
"and",
"(b)",
"misogynistic",
"aggression",
"identification.",
"We",
"proposed",
"to",
"use",
"the",
"transformer",
"based",
"language",
"model",
"BERT",
"(Bidirectional",
"Encoder",
"Representation",
"from",
"Transformer)",
"for",
"the",
"two",
"sub-tasks.",
"Our",
"team",
"was",
"qualified",
"as",
"twelfth",
"out",
"of",
"sixteen",
"participants",
"on",
"sub-task",
"(a)",
"and",
"eleventh",
"out",
"of",
"fifteen",
"participants",
"on",
"sub-task",
"(b)."
] |
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[
"Large-scale",
"parsing",
"is",
"still",
"a",
"complex",
"and",
"timeconsuming",
"process",
",",
"often",
"so",
"much",
"that",
"it",
"is",
"infeasible",
"in",
"real-world",
"applications",
".",
"The",
"parsing",
"system",
"described",
"here",
"addresses",
"this",
"problem",
"by",
"combining",
"finite-state",
"approaches",
",",
"statistical",
"parsing",
"techniques",
"and",
"engineering",
"knowledge",
",",
"thus",
"keeping",
"parsing",
"complexity",
"as",
"low",
"as",
"possible",
"at",
"the",
"cost",
"of",
"a",
"slight",
"decrease",
"in",
"performance",
".",
"The",
"parser",
"is",
"robust",
"and",
"fast",
"and",
"at",
"the",
"same",
"time",
"based",
"on",
"strong",
"linguistic",
"foundations",
"."
] |
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[
"Planning",
"safe",
"trajectories",
"under",
"uncertain",
"and",
"dynamic",
"conditions",
"makes",
"the",
"autonomous",
"driving",
"problem",
"significantly",
"complex.",
"Current",
"sampling-based",
"methods",
"such",
"as",
"Rapidly",
"Exploring",
"Random",
"Trees",
"(RRTs)",
"are",
"not",
"ideal",
"for",
"this",
"problem",
"because",
"of",
"the",
"high",
"computational",
"cost.",
"Supervised",
"learning",
"methods",
"such",
"as",
"Imitation",
"Learning",
"lack",
"generalization",
"and",
"safety",
"guarantees.",
"To",
"address",
"these",
"problems",
"and",
"in",
"order",
"to",
"ensure",
"a",
"robust",
"framework,",
"we",
"propose",
"a",
"Hierarchical",
"Reinforcement",
"Learning",
"(HRL)",
"structure",
"combined",
"with",
"a",
"Proportional-Integral-Derivative",
"(PID)",
"controller",
"for",
"trajectory",
"planning.",
"HRL",
"helps",
"divide",
"the",
"task",
"of",
"autonomous",
"vehicle",
"driving",
"into",
"sub-goals",
"and",
"supports",
"the",
"network",
"to",
"learn",
"policies",
"for",
"both",
"high-level",
"options",
"and",
"low-level",
"trajectory",
"planner",
"choices.",
"The",
"introduction",
"of",
"sub-goals",
"decreases",
"convergence",
"time",
"and",
"enables",
"the",
"policies",
"learned",
"to",
"be",
"reused",
"for",
"other",
"scenarios.",
"In",
"addition,",
"the",
"proposed",
"planner",
"is",
"made",
"robust",
"by",
"guaranteeing",
"smooth",
"trajectories",
"and",
"by",
"handling",
"the",
"noisy",
"perception",
"system",
"of",
"the",
"ego-car.",
"The",
"PID",
"controller",
"is",
"used",
"for",
"tracking",
"the",
"waypoints,",
"which",
"ensures",
"smooth",
"trajectories",
"and",
"reduces",
"jerk.",
"The",
"problem",
"of",
"incomplete",
"observations",
"is",
"handled",
"by",
"using",
"a",
"Long-Short-Term-Memory",
"(LSTM)",
"layer",
"in",
"the",
"network.",
"Results",
"from",
"the",
"high-fidelity",
"CARLA",
"simulator",
"indicate",
"that",
"the",
"proposed",
"method",
"reduces",
"convergence",
"time,",
"generates",
"smoother",
"trajectories,",
"and",
"is",
"able",
"to",
"handle",
"dynamic",
"surroundings",
"and",
"noisy",
"observations."
] |
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"Though",
"early",
"successes",
"of",
"Statistical",
"Machine",
"Translation",
"(SMT)",
"systems",
"are",
"attributed",
"in",
"part",
"to",
"the",
"explicit",
"modelling",
"of",
"the",
"interaction",
"between",
"any",
"two",
"source",
"and",
"target",
"units,",
"e.g.,",
"alignment,",
"the",
"recent",
"Neural",
"Machine",
"Translation",
"(NMT)",
"systems",
"resort",
"to",
"the",
"attention",
"which",
"partially",
"encodes",
"the",
"interaction",
"for",
"efficiency.",
"In",
"this",
"paper,",
"we",
"employ",
"Joint",
"Representation",
"that",
"fully",
"accounts",
"for",
"each",
"possible",
"interaction.",
"We",
"sidestep",
"the",
"inefficiency",
"issue",
"by",
"refining",
"representations",
"with",
"the",
"proposed",
"efficient",
"attention",
"operation.",
"The",
"resulting",
"Reformer",
"models",
"offer",
"a",
"new",
"Sequence-to-",
"Sequence",
"modelling",
"paradigm",
"besides",
"the",
"Encoder-Decoder",
"framework",
"and",
"outperform",
"the",
"Transformer",
"baseline",
"in",
"either",
"the",
"small",
"scale",
"IWSLT14",
"German-English,",
"English-German",
"and",
"IWSLT15",
"Vietnamese-English",
"or",
"the",
"large",
"scale",
"NIST12",
"Chinese-English",
"translation",
"tasks",
"by",
"about",
"1",
"BLEU",
"point.We",
"also",
"propose",
"a",
"systematic",
"model",
"scaling",
"approach,",
"allowing",
"the",
"Reformer",
"model",
"to",
"beat",
"the",
"state-of-the-art",
"Transformer",
"in",
"IWSLT14",
"German-English",
"and",
"NIST12",
"Chinese-English",
"with",
"about",
"50%",
"fewer",
"parameters.",
"The",
"code",
"is",
"publicly",
"available",
"at",
"https://github.com/lyy1994/reformer."
] |
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[
"Datasets",
"that",
"boosted",
"state-of-the-art",
"solutions",
"for",
"Question",
"Answering",
"(QA)",
"systems",
"prove",
"that",
"it",
"is",
"possible",
"to",
"ask",
"questions",
"in",
"natural",
"language",
"manner.",
"However,",
"users",
"are",
"still",
"used",
"to",
"query-like",
"systems",
"where",
"they",
"type",
"in",
"keywords",
"to",
"search",
"for",
"answer.",
"In",
"this",
"study",
"we",
"validate",
"which",
"parts",
"of",
"questions",
"are",
"essential",
"for",
"obtaining",
"valid",
"answer.",
"In",
"order",
"to",
"conclude",
"that,",
"we",
"take",
"advantage",
"of",
"LIME",
"-",
"a",
"framework",
"that",
"explains",
"prediction",
"by",
"local",
"approximation.",
"We",
"find",
"that",
"grammar",
"and",
"natural",
"language",
"is",
"disregarded",
"by",
"QA.",
"State-of-the-art",
"model",
"can",
"answer",
"properly",
"even",
"if",
"{'}asked{'}",
"only",
"with",
"a",
"few",
"words",
"with",
"high",
"coefficients",
"calculated",
"with",
"LIME",
".",
"According",
"to",
"our",
"knowledge,",
"it",
"is",
"the",
"first",
"time",
"that",
"QA",
"model",
"is",
"being",
"explained",
"by",
"LIME",
"."
] |
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[
"An",
"important",
"aspect",
"of",
"the",
"quality",
"of",
"a",
"public",
"transport",
"service",
"is",
"its",
"reliability,",
"which",
"is",
"defined",
"as",
"the",
"invariability",
"of",
"the",
"service",
"attributes.",
"Preventive",
"measures",
"taken",
"during",
"planning",
"can",
"reduce",
"risks",
"of",
"unreliability",
"throughout",
"operations.",
"In",
"order",
"to",
"tackle",
"reliability",
"during",
"the",
"service",
"planning",
"phase,",
"a",
"key",
"piece",
"of",
"information",
"is",
"the",
"long-term",
"prediction",
"of",
"the",
"density",
"of",
"the",
"travel",
"time,",
"which",
"conveys",
"the",
"uncertainty",
"of",
"travel",
"times.",
"We",
"introduce",
"a",
"reliable",
"approach",
"to",
"one",
"of",
"the",
"problems",
"of",
"service",
"planning",
"in",
"public",
"transport,",
"namely",
"the",
"Multiple",
"Depot",
"Vehicle",
"Scheduling",
"Problem",
"(MDVSP),",
"which",
"takes",
"as",
"input",
"a",
"set",
"of",
"trips",
"and",
"the",
"probability",
"density",
"function",
"(p.d.f.)",
"of",
"the",
"travel",
"time",
"of",
"each",
"trip",
"in",
"order",
"to",
"output",
"delay-tolerant",
"vehicle",
"schedules.",
"This",
"work",
"empirically",
"compares",
"probabilistic",
"models",
"for",
"the",
"prediction",
"of",
"the",
"conditional",
"p.d.f.",
"of",
"the",
"travel",
"time,",
"as",
"a",
"first",
"step",
"towards",
"reliable",
"MDVSP",
"solutions.",
"Two",
"types",
"of",
"probabilistic",
"models,",
"namely",
"similarity-based",
"density",
"estimation",
"models",
"and",
"a",
"smoothed",
"Logistic",
"Regression",
"for",
"probabilistic",
"classification",
"model,",
"are",
"compared",
"on",
"a",
"dataset",
"of",
"more",
"than",
"41,000",
"trips",
"and",
"50",
"bus",
"routes",
"of",
"the",
"city",
"of",
"Montr\\'eal.",
"The",
"result",
"of",
"a",
"vast",
"majority",
"of",
"probabilistic",
"models",
"outperforms",
"that",
"of",
"a",
"Random",
"Forests",
"model,",
"which",
"is",
"not",
"inherently",
"probabilistic,",
"thus",
"highlighting",
"the",
"added",
"value",
"of",
"modeling",
"the",
"conditional",
"p.d.f.",
"of",
"the",
"travel",
"time",
"with",
"probabilistic",
"models.",
"A",
"similarity-based",
"density",
"estimation",
"model",
"using",
"a",
"$k$",
"Nearest",
"Neighbors",
"method",
"and",
"a",
"Kernel",
"Density",
"Estimation",
"predicted",
"the",
"best",
"estimate",
"of",
"the",
"TRUE",
"conditional",
"p.d.f.",
"on",
"this",
"dataset."
] |
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"We",
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"a",
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"approaches",
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"Analysis)",
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"We",
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"best",
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"We",
"thenapply",
"this",
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"We",
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"with",
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"cf.\\S3.3)",
"on",
"the",
"Rare",
"Word",
"Similarity",
"dataset."
] |
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[
"In",
"this",
"paper,",
"we",
"propose",
"a",
"novel",
"effective",
"light-weight",
"framework,",
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"LightTrack,",
"for",
"online",
"human",
"pose",
"tracking.",
"The",
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"and",
"is",
"faster",
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"online",
"and",
"offline",
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"Single-person",
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"Tracking",
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"functioning",
"entity,",
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"light",
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"tracking.",
"We",
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"Convolution",
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"captures",
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"It",
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"sudden",
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"shift",
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"drifting.",
"To",
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"best",
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"our",
"knowledge,",
"this",
"is",
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"pose",
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"fashion.",
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"other",
"pose",
"estimators",
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"candidate",
"matching",
"mechanisms.",
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"outperforms",
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"online",
"methods",
"while",
"maintaining",
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"much",
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"frame",
"rate,",
"and",
"is",
"very",
"competitive",
"with",
"our",
"offline",
"state-of-the-art.",
"We",
"make",
"the",
"code",
"publicly",
"available",
"at:",
"https://github.com/Guanghan/lighttrack."
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"The",
"increase",
"in",
"the",
"number",
"of",
"Internet",
"users",
"and",
"the",
"strong",
"interactionbrought",
"by",
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"2",
"made",
"the",
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"Mining",
"an",
"important",
"task",
"in",
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"area",
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"language",
"processing.",
"Although",
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"capable",
"of",
"performingthis",
"task,",
"few",
"use",
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"classification,",
"where",
"there",
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"a",
"group",
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"truelabels",
"for",
"each",
"example.",
"This",
"type",
"of",
"classification",
"is",
"useful",
"for",
"situationswhere",
"the",
"opinions",
"are",
"analyzed",
"from",
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"perspective",
"of",
"the",
"reader,",
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"because",
"each",
"person",
"can",
"have",
"different",
"interpretations",
"and",
"opinions",
"onthe",
"same",
"subject.",
"This",
"paper",
"discuss",
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"efficiency",
"of",
"problem",
"transformationmethods",
"combined",
"with",
"different",
"classification",
"algorithms",
"for",
"the",
"task",
"ofmulti-label",
"classification",
"of",
"reactions",
"in",
"news",
"texts.",
"To",
"do",
"that,",
"extensivetests",
"were",
"carried",
"out",
"on",
"two",
"news",
"corpora",
"written",
"in",
"Brazilian",
"Portugueseannotated",
"with",
"reactions.",
"A",
"new",
"corpus",
"called",
"BFRC-PT",
"is",
"presented.",
"In",
"thetests",
"performed,",
"the",
"highest",
"number",
"of",
"correct",
"predictions",
"was",
"obtained",
"withthe",
"Classifier",
"Chains",
"method",
"combined",
"with",
"the",
"Random",
"Forest",
"algorithm.",
"Whenconsidering",
"the",
"class",
"distribution,",
"the",
"best",
"results",
"were",
"obtained",
"with",
"theBinary",
"Relevance",
"method",
"combined",
"with",
"the",
"LSTM",
"and",
"Random",
"Forest",
"algorithms."
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"The",
"use",
"of",
"multi-modal",
"data",
"such",
"as",
"the",
"combination",
"of",
"whole",
"slide",
"images",
"(WSIs)",
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"gene",
"expression",
"data",
"for",
"survival",
"analysis",
"can",
"lead",
"to",
"more",
"accurate",
"survival",
"predictions.",
"Previous",
"multi-modal",
"survival",
"models",
"are",
"not",
"able",
"to",
"efficiently",
"excavate",
"the",
"intrinsic",
"information",
"within",
"each",
"modality.",
"Moreover,",
"despite",
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"results",
"show",
"that",
"WSIs",
"provide",
"more",
"effective",
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"gene",
"expression",
"data,",
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"regard",
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"they",
"cannot",
"flexibly",
"utilize",
"the",
"potential",
"connection",
"between",
"the",
"modalities.",
"To",
"address",
"the",
"above",
"problems,",
"we",
"propose",
"a",
"new",
"asymmetrical",
"multi-modal",
"method,",
"termed",
"as",
"AMMASurv.",
"Specifically,",
"we",
"design",
"an",
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"multi-modal",
"attention",
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"(AMMA)",
"in",
"Transformer",
"encoder",
"for",
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"data",
"to",
"enable",
"a",
"more",
"flexible",
"multi-modal",
"information",
"fusion",
"for",
"survival",
"prediction.",
"Different",
"from",
"previous",
"works,",
"AMMASurv",
"can",
"effectively",
"utilize",
"the",
"intrinsic",
"information",
"within",
"every",
"modality",
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"flexibly",
"adapts",
"to",
"the",
"modalities",
"of",
"different",
"importance.",
"Extensive",
"experiments",
"are",
"conducted",
"to",
"validate",
"the",
"effectiveness",
"of",
"the",
"proposed",
"model.",
"Encouraging",
"results",
"demonstrate",
"the",
"superiority",
"of",
"our",
"method",
"over",
"other",
"state-of-the-art",
"methods."
] |
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"Recent",
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"ranking",
"networks,",
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"increasingly",
"heavy",
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"burden",
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"growing",
"numbers",
"of",
"parameters",
"and",
"the",
"adoption",
"of",
"model",
"ensembles.",
"Knowledge",
"Distillation",
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"is",
"a",
"common",
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"to",
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"the",
"effectiveness",
"and",
"efficiency.",
"However,",
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"is",
"not",
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"apply",
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"to",
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"problems.",
"Ranking",
"Distillation",
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"has",
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"address",
"this",
"issue,",
"but",
"only",
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"tasks.",
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"method",
"for",
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"problems",
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"allows",
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"model,",
"providing",
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"We",
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"#NAME?",
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"model",
"structure",
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"ranking",
"to",
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"model.",
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"to",
"rank",
"the",
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"list.",
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"our",
"method,",
"not",
"just",
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"biology",
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"BPLs",
"from",
"?",
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"was",
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"supported",
"by",
"NSERC",
",",
"Canada",
"."
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".",
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"such",
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"outperform",
"the",
"other",
"techniques",
"."
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"tasks.",
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"#NAME?",
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"in",
"Spanish.",
"We",
"release",
"all",
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"implemented",
"in",
"this",
"work",
"under",
"open",
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"datasets",
"by",
"0.56%,",
"0.50%,",
"and",
"0.39%,",
"respectively",
"compared",
"to",
"the",
"state-of-the-art",
"approaches.",
"Our",
"approach",
"performs",
"better",
"than",
"DARTS",
",",
"improving",
"the",
"accuracy",
"by",
"0.28%,",
"1.64%,",
"0.34%,",
"4.5%,",
"and",
"3.27%",
"compared",
"to",
"DARTS",
",",
"on",
"CIFAR-10,",
"CIFAR-100,",
"Fashion-MNIST,",
"CompCars,",
"and",
"MIO-TCD",
"datasets,",
"respectively."
] |
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[
"The",
"performance",
"of",
"a",
"cross-sectional",
"currency",
"strategy",
"depends",
"crucially",
"on",
"accurately",
"ranking",
"instruments",
"prior",
"to",
"portfolio",
"construction.",
"While",
"this",
"ranking",
"step",
"is",
"traditionally",
"performed",
"using",
"heuristics,",
"or",
"by",
"sorting",
"outputs",
"produced",
"by",
"pointwise",
"regression",
"or",
"classification",
"models,",
"Learning",
"to",
"Rank",
"algorithms",
"have",
"recently",
"presented",
"themselves",
"as",
"competitive",
"and",
"viable",
"alternatives.",
"Despite",
"improving",
"ranking",
"accuracy",
"on",
"average",
"however,",
"these",
"techniques",
"do",
"not",
"account",
"for",
"the",
"possibility",
"that",
"assets",
"positioned",
"at",
"the",
"extreme",
"ends",
"of",
"the",
"ranked",
"list",
"--",
"which",
"are",
"ultimately",
"used",
"to",
"construct",
"the",
"long/short",
"portfolios",
"--",
"can",
"assume",
"different",
"distributions",
"in",
"the",
"input",
"space,",
"and",
"thus",
"lead",
"to",
"sub-optimal",
"strategy",
"performance.",
"Drawing",
"from",
"research",
"in",
"Information",
"Retrieval",
"that",
"demonstrates",
"the",
"utility",
"of",
"contextual",
"information",
"embedded",
"within",
"top-ranked",
"documents",
"to",
"learn",
"the",
"query's",
"characteristics",
"to",
"improve",
"ranking,",
"we",
"propose",
"an",
"analogous",
"approach:",
"exploiting",
"the",
"features",
"of",
"both",
"out-",
"and",
"under-performing",
"instruments",
"to",
"learn",
"a",
"model",
"for",
"refining",
"the",
"original",
"ranked",
"list.",
"Under",
"a",
"re-ranking",
"framework,",
"we",
"adapt",
"the",
"Transformer",
"architecture",
"to",
"encode",
"the",
"features",
"of",
"extreme",
"assets",
"for",
"refining",
"our",
"selection",
"of",
"long/short",
"instruments",
"obtained",
"with",
"an",
"initial",
"retrieval.",
"Backtesting",
"on",
"a",
"set",
"of",
"31",
"currencies,",
"our",
"proposed",
"methodology",
"significantly",
"boosts",
"Sharpe",
"ratios",
"--",
"by",
"approximately",
"20%",
"over",
"the",
"original",
"LTR",
"algorithms",
"and",
"double",
"that",
"of",
"traditional",
"baselines."
] |
[
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
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6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
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6,
6,
6,
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6,
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6,
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6,
6,
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6,
6,
6,
6,
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1,
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6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6
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[
"Model",
"extraction",
"attacks",
"are",
"a",
"kind",
"of",
"attacks",
"in",
"which",
"an",
"adversary",
"obtains",
"a",
"new",
"model,",
"whose",
"performance",
"is",
"equivalent",
"to",
"that",
"of",
"a",
"target",
"model,",
"via",
"query",
"access",
"to",
"the",
"target",
"model",
"efficiently,",
"i.e.,",
"fewer",
"datasets",
"and",
"computational",
"resources",
"than",
"those",
"of",
"the",
"target",
"model.",
"Existing",
"works",
"have",
"dealt",
"with",
"only",
"simple",
"deep",
"neural",
"networks",
"(DNNs),",
"e.g.,",
"only",
"three",
"layers,",
"as",
"targets",
"of",
"model",
"extraction",
"attacks,",
"and",
"hence",
"are",
"not",
"aware",
"of",
"the",
"effectiveness",
"of",
"recurrent",
"neural",
"networks",
"(RNNs)",
"in",
"dealing",
"with",
"time-series",
"data.",
"In",
"this",
"work,",
"we",
"shed",
"light",
"on",
"the",
"threats",
"of",
"model",
"extraction",
"attacks",
"against",
"RNNs.",
"We",
"discuss",
"whether",
"a",
"model",
"with",
"a",
"higher",
"accuracy",
"can",
"be",
"extracted",
"with",
"a",
"simple",
"RNN",
"from",
"a",
"long",
"short-term",
"memory",
"(LSTM",
"),",
"which",
"is",
"a",
"more",
"complicated",
"and",
"powerful",
"RNN.",
"Specifically,",
"we",
"tackle",
"the",
"following",
"problems.",
"First,",
"in",
"a",
"case",
"of",
"a",
"classification",
"problem,",
"such",
"as",
"image",
"recognition,",
"extraction",
"of",
"an",
"RNN",
"model",
"without",
"final",
"outputs",
"from",
"an",
"LSTM",
"model",
"is",
"presented",
"by",
"utilizing",
"outputs",
"halfway",
"through",
"the",
"sequence.",
"Next,",
"in",
"a",
"case",
"of",
"a",
"regression",
"problem.",
"such",
"as",
"in",
"weather",
"forecasting,",
"a",
"new",
"attack",
"by",
"newly",
"configuring",
"a",
"loss",
"function",
"is",
"presented.",
"We",
"conduct",
"experiments",
"on",
"our",
"model",
"extraction",
"attacks",
"against",
"an",
"RNN",
"and",
"an",
"LSTM",
"trained",
"with",
"publicly",
"available",
"academic",
"datasets.",
"We",
"then",
"show",
"that",
"a",
"model",
"with",
"a",
"higher",
"accuracy",
"can",
"be",
"extracted",
"efficiently,",
"especially",
"through",
"configuring",
"a",
"loss",
"function",
"and",
"a",
"more",
"complex",
"architecture",
"different",
"from",
"the",
"target",
"model."
] |
[
1,
3,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
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6,
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6,
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6,
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6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
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6,
6,
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6,
6,
6,
6,
6,
6,
6
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[
"Unpaired",
"Image-to-Image",
"Translation",
"(I2IT)",
"tasks",
"often",
"suffer",
"from",
"lack",
"of",
"data,",
"a",
"problem",
"which",
"self-supervised",
"learning",
"(SSL)",
"has",
"recently",
"been",
"very",
"popular",
"and",
"successful",
"at",
"tackling.",
"Leveraging",
"auxiliary",
"tasks",
"such",
"as",
"rotation",
"prediction",
"or",
"generative",
"colorization,",
"SSL",
"can",
"produce",
"better",
"and",
"more",
"robust",
"representations",
"in",
"a",
"low",
"data",
"regime.",
"Training",
"such",
"tasks",
"along",
"an",
"I2IT",
"task",
"is",
"however",
"computationally",
"intractable",
"as",
"model",
"size",
"and",
"the",
"number",
"of",
"task",
"grow.",
"On",
"the",
"other",
"hand,",
"learning",
"sequentially",
"could",
"incur",
"catastrophic",
"forgetting",
"of",
"previously",
"learned",
"tasks.",
"To",
"alleviate",
"this,",
"we",
"introduce",
"Lifelong",
"Self-Supervision",
"(LiSS)",
"as",
"a",
"way",
"to",
"pre-train",
"an",
"I2IT",
"model",
"(e.g.,",
"CycleGAN",
")",
"on",
"a",
"set",
"of",
"self-supervised",
"auxiliary",
"tasks.",
"By",
"keeping",
"an",
"exponential",
"moving",
"average",
"of",
"past",
"encoders",
"and",
"distilling",
"the",
"accumulated",
"knowledge,",
"we",
"are",
"able",
"to",
"maintain",
"the",
"network's",
"validation",
"performance",
"on",
"a",
"number",
"of",
"tasks",
"without",
"any",
"form",
"of",
"replay,",
"parameter",
"isolation",
"or",
"retraining",
"techniques",
"typically",
"used",
"in",
"continual",
"learning.",
"We",
"show",
"that",
"models",
"trained",
"with",
"LiSS",
"perform",
"better",
"on",
"past",
"tasks,",
"while",
"also",
"being",
"more",
"robust",
"than",
"the",
"CycleGAN",
"baseline",
"to",
"color",
"bias",
"and",
"entity",
"entanglement",
"(when",
"two",
"entities",
"are",
"very",
"close)."
] |
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1,
3,
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6,
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6,
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6,
6,
6,
6,
6,
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6,
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6,
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6,
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6,
6,
6,
6,
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6,
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6,
6,
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6,
6,
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6,
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6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
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6,
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6,
6,
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6,
6,
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6,
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6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6
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[
"While",
"impressive",
"performance",
"in",
"natural",
"language",
"processing",
"tasks",
"has",
"been",
"achieved",
"for",
"many",
"languages",
"by",
"transfer",
"learning",
"from",
"large",
"pretrained",
"multilingual",
"language",
"models,",
"it",
"is",
"limited",
"by",
"the",
"unavailability",
"of",
"large",
"corpora",
"for",
"most",
"languages",
"and",
"the",
"barrier",
"of",
"different",
"scripts.",
"Script",
"difference",
"forces",
"the",
"tokens",
"of",
"two",
"languages",
"to",
"be",
"separated",
"at",
"the",
"input.",
"Thus",
"we",
"hypothesize",
"that",
"transliterating",
"all",
"the",
"languages",
"to",
"the",
"same",
"script",
"can",
"improve",
"the",
"performance",
"of",
"language",
"models.",
"Languages",
"of",
"South",
"Asia",
"and",
"Southeast",
"Asia",
"present",
"a",
"unique",
"opportunity",
"of",
"testing",
"this",
"hypothesis",
"as",
"almost",
"all",
"of",
"the",
"major",
"languages",
"in",
"this",
"region",
"have",
"their",
"own",
"script.",
"Nevertheless,",
"it",
"is",
"possible",
"to",
"transliterate",
"them",
"to",
"a",
"single",
"representation",
"easily.",
"We",
"validate",
"our",
"hypothesis",
"empirically",
"by",
"pretraining",
"ALBERT",
"models",
"on",
"the",
"Indo-Aryan",
"languages",
"available",
"on",
"the",
"OSCAR",
"corpus",
"and",
"measuring",
"the",
"model's",
"performance",
"on",
"the",
"Indo-Aryan",
"subset",
"of",
"the",
"IndicGLUE",
"benchmark.",
"Compared",
"to",
"the",
"non-transliteration-based",
"model,",
"the",
"transliteration-based",
"model",
"(termed",
"XLM-Indic)",
"shows",
"significant",
"improvement",
"on",
"almost",
"all",
"tasks",
"of",
"IndicGLUE.",
"For",
"example,",
"XLM-Indic",
"performed",
"better",
"on",
"News",
"Classification",
"(0.41%),",
"Multiple",
"Choice",
"QA",
"(4.62%),",
"NER",
"(6.66%),",
"and",
"Cloze-Style",
"QA",
"(3.32%).",
"In",
"addition,",
"XLM-Indic",
"establishes",
"new",
"SOTA",
"results",
"for",
"most",
"tasks",
"the",
"on",
"IndicGLUE",
"benchmark",
"while",
"being",
"competitive",
"at",
"the",
"rest.",
"Across",
"the",
"tasks",
"of",
"IndicGLUE,",
"the",
"most",
"underrepresented",
"languages",
"seem",
"to",
"gain",
"the",
"most",
"improvement.",
"For",
"instance,",
"for",
"the",
"NER",
",",
"XLM-Indic",
"achieves",
"10%,",
"35%,",
"and",
"58.50%",
"better",
"F1-scores",
"on",
"Gujarati,",
"Panjabi,",
"and",
"Oriya",
"languages",
"compared",
"to",
"the",
"current",
"SOTA."
] |
[
6,
6,
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[
"Differentiable",
"Neural",
"Architecture",
"Search",
"(DNAS",
")",
"has",
"demonstrated",
"great",
"success",
"in",
"designing",
"state-of-the-art,",
"efficient",
"neural",
"networks.",
"However,",
"DARTS-based",
"DNAS",
"'s",
"search",
"space",
"is",
"small",
"when",
"compared",
"to",
"other",
"search",
"methods',",
"since",
"all",
"candidate",
"network",
"layers",
"must",
"be",
"explicitly",
"instantiated",
"in",
"memory.",
"To",
"address",
"this",
"bottleneck,",
"we",
"propose",
"a",
"memory",
"and",
"computationally",
"efficient",
"DNAS",
"variant:",
"DMaskingNAS.",
"This",
"algorithm",
"expands",
"the",
"search",
"space",
"by",
"up",
"to",
"$10^{14}\\times$",
"over",
"conventional",
"DNAS",
",",
"supporting",
"searches",
"over",
"spatial",
"and",
"channel",
"dimensions",
"that",
"are",
"otherwise",
"prohibitively",
"expensive:",
"input",
"resolution",
"and",
"number",
"of",
"filters.",
"We",
"propose",
"a",
"masking",
"mechanism",
"for",
"feature",
"map",
"reuse,",
"so",
"that",
"memory",
"and",
"computational",
"costs",
"stay",
"nearly",
"constant",
"as",
"the",
"search",
"space",
"expands.",
"Furthermore,",
"we",
"employ",
"effective",
"shape",
"propagation",
"to",
"maximize",
"per-FLOP",
"or",
"per-parameter",
"accuracy.",
"The",
"searched",
"FBNetV2s",
"yield",
"state-of-the-art",
"performance",
"when",
"compared",
"with",
"all",
"previous",
"architectures.",
"With",
"up",
"to",
"421$\\times$",
"less",
"search",
"cost,",
"DMaskingNAS",
"finds",
"models",
"with",
"0.90%",
"higher",
"accuracy,",
"15%",
"fewer",
"FLOPs",
"than",
"MobileNetV3-Small;",
"and",
"with",
"similar",
"accuracy",
"but",
"20%",
"fewer",
"FLOPs",
"than",
"Efficient-B0.",
"Furthermore,",
"our",
"FBNetV2",
"outperforms",
"MobileNetV3",
"by",
"2.60%",
"in",
"accuracy,",
"with",
"equivalent",
"model",
"size.",
"FBNetV2",
"models",
"are",
"open-sourced",
"at",
"https://github.com/facebookresearch/mobile-vision."
] |
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[
"Dynamic",
"robust",
"PCA",
"refers",
"to",
"the",
"dynamic",
"(time-varying)",
"extension",
"of",
"robustPCA",
"(RPCA",
").",
"It",
"assumes",
"that",
"the",
"TRUE",
"(uncorrupted)",
"data",
"lies",
"in",
"alow-dimensional",
"subspace",
"that",
"can",
"change",
"with",
"time,",
"albeit",
"slowly.",
"The",
"goal",
"isto",
"track",
"this",
"changing",
"subspace",
"over",
"time",
"in",
"the",
"presence",
"of",
"sparse",
"outliers.We",
"develop",
"and",
"study",
"a",
"novel",
"algorithm,",
"that",
"we",
"call",
"simple-ReProCS,",
"based",
"onthe",
"recently",
"introduced",
"Recursive",
"Projected",
"Compressive",
"Sensing",
"(ReProCS)framework.",
"Our",
"work",
"provides",
"the",
"first",
"guarantee",
"for",
"dynamic",
"RPCA",
"that",
"holdsunder",
"weakened",
"versions",
"of",
"standard",
"RPCA",
"assumptions,",
"slow",
"subspace",
"change",
"anda",
"lower",
"bound",
"assumption",
"on",
"most",
"outlier",
"magnitudes.",
"Our",
"result",
"is",
"significantbecause",
"(i)",
"it",
"removes",
"the",
"strong",
"assumptions",
"needed",
"by",
"the",
"two",
"previouscomplete",
"guarantees",
"for",
"ReProCS-based",
"algorithms;",
"(ii)",
"it",
"shows",
"that",
"it",
"ispossible",
"to",
"achieve",
"significantly",
"improved",
"outlier",
"tolerance,",
"compared",
"with",
"allexisting",
"RPCA",
"or",
"dynamic",
"RPCA",
"solutions",
"by",
"exploiting",
"the",
"above",
"two",
"simpleextra",
"assumptions;",
"and",
"(iii)",
"it",
"proves",
"that",
"simple-ReProCS",
"is",
"online",
"(afterinitialization),",
"fast,",
"and,",
"has",
"near-optimal",
"memory",
"complexity."
] |
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[
"Neural",
"Machine",
"Translation",
"(NMT)",
"for",
"low-resource",
"languages",
"suffers",
"from",
"low",
"performance",
"because",
"of",
"the",
"lack",
"of",
"large",
"amounts",
"of",
"parallel",
"data",
"and",
"language",
"diversity.",
"To",
"contribute",
"to",
"ameliorating",
"this",
"problem,",
"we",
"built",
"a",
"baseline",
"model",
"for",
"English-Hausa",
"machine",
"translation,",
"which",
"is",
"considered",
"a",
"task",
"for",
"low-resource",
"language.",
"The",
"Hausa",
"language",
"is",
"the",
"second",
"largest",
"Afro-Asiatic",
"language",
"in",
"the",
"world",
"after",
"Arabic",
"and",
"it",
"is",
"the",
"third",
"largest",
"language",
"for",
"trading",
"across",
"a",
"larger",
"swath",
"of",
"West",
"Africa",
"countries,",
"after",
"English",
"and",
"French.",
"In",
"this",
"paper,",
"we",
"curated",
"different",
"datasets",
"containing",
"Hausa-English",
"parallel",
"corpus",
"for",
"our",
"translation.",
"We",
"trained",
"baseline",
"models",
"and",
"evaluated",
"the",
"performance",
"of",
"our",
"models",
"using",
"the",
"Recurrent",
"and",
"Transformer",
"encoder-decoder",
"architecture",
"with",
"two",
"tokenization",
"approaches:",
"standard",
"word-level",
"tokenization",
"and",
"Byte",
"Pair",
"Encoding",
"(BPE)",
"subword",
"tokenization."
] |
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[
"Convolutional",
"networks",
"have",
"been",
"the",
"paradigm",
"of",
"choice",
"in",
"many",
"computer",
"vision",
"applications.",
"The",
"convolution",
"operation",
"however",
"has",
"a",
"significant",
"weakness",
"in",
"that",
"it",
"only",
"operates",
"on",
"a",
"local",
"neighborhood,",
"thus",
"missing",
"global",
"information.",
"Self-attention,",
"on",
"the",
"other",
"hand,",
"has",
"emerged",
"as",
"a",
"recent",
"advance",
"to",
"capture",
"long",
"range",
"interactions,",
"but",
"has",
"mostly",
"been",
"applied",
"to",
"sequence",
"modeling",
"and",
"generative",
"modeling",
"tasks.",
"In",
"this",
"paper,",
"we",
"consider",
"the",
"use",
"of",
"self-attention",
"for",
"discriminative",
"visual",
"tasks",
"as",
"an",
"alternative",
"to",
"convolutions.",
"We",
"introduce",
"a",
"novel",
"two-dimensional",
"relative",
"self-attention",
"mechanism",
"that",
"proves",
"competitive",
"in",
"replacing",
"convolutions",
"as",
"a",
"stand-alone",
"computational",
"primitive",
"for",
"image",
"classification.",
"We",
"find",
"in",
"control",
"experiments",
"that",
"the",
"best",
"results",
"are",
"obtained",
"when",
"combining",
"both",
"convolutions",
"and",
"self-attention.",
"We",
"therefore",
"propose",
"to",
"augment",
"convolutional",
"operators",
"with",
"this",
"self-attention",
"mechanism",
"by",
"concatenating",
"convolutional",
"feature",
"maps",
"with",
"a",
"set",
"of",
"feature",
"maps",
"produced",
"via",
"self-attention.",
"Extensive",
"experiments",
"show",
"that",
"Attention",
"Augmentation",
"leads",
"to",
"consistent",
"improvements",
"in",
"image",
"classification",
"on",
"ImageNet",
"and",
"object",
"detection",
"on",
"COCO",
"across",
"many",
"different",
"models",
"and",
"scales,",
"including",
"ResNets",
"and",
"a",
"state-of-the",
"art",
"mobile",
"constrained",
"network,",
"while",
"keeping",
"the",
"number",
"of",
"parameters",
"similar.",
"In",
"particular,",
"our",
"method",
"achieves",
"a",
"$1.3\\%$",
"top-1",
"accuracy",
"improvement",
"on",
"ImageNet",
"classification",
"over",
"a",
"ResNet50",
"baseline",
"and",
"outperforms",
"other",
"attention",
"mechanisms",
"for",
"images",
"such",
"as",
"Squeeze-and-Excitation.",
"It",
"also",
"achieves",
"an",
"improvement",
"of",
"1.4",
"mAP",
"in",
"COCO",
"Object",
"Detection",
"on",
"top",
"of",
"a",
"RetinaNet",
"baseline."
] |
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[
"The",
"shift",
"from",
"paper",
"to",
"electronic",
"documents",
"has",
"caused",
"the",
"curation",
"of",
"information",
"sources",
"in",
"large",
"electronic",
"databases",
"to",
"become",
"more",
"generalized",
".",
"In",
"the",
"biomedical",
"domain",
",",
"continuing",
"efforts",
"aim",
"at",
"refining",
"indexing",
"tools",
"to",
"assist",
"with",
"the",
"update",
"and",
"maintenance",
"of",
"databases",
"such",
"as",
"MEDLINE",
"?",
".",
"In",
"this",
"paper",
",",
"we",
"evaluate",
"two",
"statistical",
"methods",
"of",
"producing",
"MeSH",
"?",
"indexing",
"recommendations",
"for",
"the",
"genetics",
"literature",
",",
"including",
"recommendations",
"involving",
"subheadings",
",",
"which",
"is",
"a",
"novel",
"application",
"for",
"the",
"methods",
".",
"We",
"show",
"that",
"a",
"generic",
"representation",
"of",
"the",
"documents",
"yields",
"both",
"better",
"precision",
"and",
"recall",
".",
"We",
"also",
"find",
"that",
"a",
"domainspecific",
"representation",
"of",
"the",
"documents",
"can",
"contribute",
"to",
"enhancing",
"recall",
"."
] |
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[
"In",
"this",
"paper,",
"we",
"consider",
"the",
"problem",
"of",
"Robust",
"Matrix",
"Completion",
"(RMC)where",
"the",
"goal",
"is",
"to",
"recover",
"a",
"low-rank",
"matrix",
"by",
"observing",
"a",
"small",
"number",
"ofits",
"entries",
"out",
"of",
"which",
"a",
"few",
"can",
"be",
"arbitrarily",
"corrupted.",
"We",
"propose",
"asimple",
"projected",
"gradient",
"descent",
"method",
"to",
"estimate",
"the",
"low-rank",
"matrix",
"thatalternately",
"performs",
"a",
"projected",
"gradient",
"descent",
"step",
"and",
"cleans",
"up",
"a",
"few",
"ofthe",
"corrupted",
"entries",
"using",
"hard-thresholding.",
"Our",
"algorithm",
"solves",
"RMC",
"usingnearly",
"optimal",
"number",
"of",
"observations",
"as",
"well",
"as",
"nearly",
"optimal",
"number",
"ofcorruptions.",
"Our",
"result",
"also",
"implies",
"significant",
"improvement",
"over",
"the",
"existingtime",
"complexity",
"bounds",
"for",
"the",
"low-rank",
"matrix",
"completion",
"problem.",
"Finally,",
"anapplication",
"of",
"our",
"result",
"to",
"the",
"robust",
"PCA",
"problem",
"(low-rank+sparse",
"matrixseparation)",
"leads",
"to",
"nearly",
"linear",
"time",
"(in",
"matrix",
"dimensions)",
"algorithm",
"forthe",
"same;",
"existing",
"state-of-the-art",
"methods",
"require",
"quadratic",
"time.",
"Ourempirical",
"results",
"corroborate",
"our",
"theoretical",
"results",
"and",
"show",
"that",
"even",
"formoderate",
"sized",
"problems,",
"our",
"method",
"for",
"robust",
"PCA",
"is",
"an",
"an",
"order",
"of",
"magnitudefaster",
"than",
"the",
"existing",
"methods."
] |
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[
"Single",
"Image",
"Super-Resolution",
"(SISR)",
"aims",
"to",
"improve",
"resolution",
"of",
"small-size",
"low-quality",
"image",
"from",
"a",
"single",
"one.",
"With",
"popularity",
"of",
"consumer",
"electronics",
"in",
"our",
"daily",
"life,",
"this",
"topic",
"has",
"become",
"more",
"and",
"more",
"attractive.",
"In",
"this",
"paper,",
"we",
"argue",
"that",
"the",
"curse",
"of",
"dimensionality",
"is",
"the",
"underlying",
"reason",
"of",
"limiting",
"the",
"performance",
"of",
"state-of-the-art",
"algorithms.",
"To",
"address",
"this",
"issue,",
"we",
"propose",
"Progressive",
"Adversarial",
"Network",
"(PAN)",
"that",
"is",
"capable",
"of",
"coping",
"with",
"this",
"difficulty",
"for",
"domain-specific",
"image",
"super-resolution.",
"The",
"key",
"principle",
"of",
"PAN",
"is",
"that",
"we",
"do",
"not",
"apply",
"any",
"distance-based",
"reconstruction",
"errors",
"as",
"the",
"loss",
"to",
"be",
"optimized,",
"thus",
"free",
"from",
"the",
"restriction",
"of",
"the",
"curse",
"of",
"dimensionality.",
"To",
"maintain",
"faithful",
"reconstruction",
"precision,",
"we",
"resort",
"to",
"U-Net",
"and",
"progressive",
"growing",
"of",
"neural",
"architecture.",
"The",
"low-level",
"features",
"in",
"encoder",
"can",
"be",
"transferred",
"into",
"decoder",
"to",
"enhance",
"textural",
"details",
"with",
"U-Net",
".",
"Progressive",
"growing",
"enhances",
"image",
"resolution",
"gradually,",
"thereby",
"preserving",
"precision",
"of",
"recovered",
"image.",
"Moreover,",
"to",
"obtain",
"high-fidelity",
"outputs,",
"we",
"leverage",
"the",
"framework",
"of",
"the",
"powerful",
"StyleGAN",
"to",
"perform",
"adversarial",
"learning.",
"Without",
"the",
"curse",
"of",
"dimensionality,",
"our",
"model",
"can",
"super-resolve",
"large-size",
"images",
"with",
"remarkable",
"photo-realistic",
"details",
"and",
"few",
"distortions.",
"Extensive",
"experiments",
"demonstrate",
"the",
"superiority",
"of",
"our",
"algorithm",
"over",
"state-of-the-arts",
"both",
"quantitatively",
"and",
"qualitatively."
] |
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[
"In",
"this",
"paper",
"we",
"describe",
"a",
"dynamic",
"normalization",
"process",
"applied",
"to",
"socialnetwork",
"multilingual",
"documents",
"(Facebook",
"and",
"Twitter)",
"to",
"improve",
"theperformance",
"of",
"the",
"Author",
"profiling",
"task",
"for",
"short",
"texts.",
"After",
"thenormalization",
"process,",
"$n$-grams",
"of",
"characters",
"and",
"n-grams",
"of",
"POS",
"tags",
"areobtained",
"to",
"extract",
"all",
"the",
"possible",
"stylistic",
"information",
"encoded",
"in",
"thedocuments",
"(emoticons,",
"character",
"flooding,",
"capital",
"letters,",
"references",
"to",
"otherusers,",
"hyperlinks,",
"hashtags,",
"etc.).",
"Experiments",
"with",
"SVM",
"showed",
"up",
"to",
"90%",
"ofperformance."
] |
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[
"The",
"wind",
"is",
"one",
"of",
"the",
"most",
"increasingly",
"used",
"renewable",
"energy",
"resources.",
"Accurate",
"and",
"reliable",
"forecast",
"of",
"wind",
"speed",
"is",
"necessary",
"for",
"efficient",
"power",
"production;",
"however,",
"it",
"is",
"not",
"an",
"easy",
"task",
"because",
"it",
"depends",
"upon",
"meteorological",
"features",
"of",
"the",
"surrounding",
"region.",
"Deep",
"learning",
"is",
"extensively",
"used",
"these",
"days",
"for",
"performing",
"feature",
"extraction.",
"It",
"has",
"also",
"been",
"observed",
"that",
"the",
"integration",
"of",
"several",
"learning",
"models,",
"known",
"as",
"ensemble",
"learning,",
"generally",
"gives",
"better",
"performance",
"compared",
"to",
"a",
"single",
"model.",
"The",
"design",
"of",
"wings,",
"tail,",
"and",
"nose",
"of",
"a",
"jet",
"improves",
"the",
"aerodynamics",
"resulting",
"in",
"a",
"smooth",
"and",
"controlled",
"flight",
"of",
"the",
"jet",
"against",
"the",
"variations",
"of",
"the",
"air",
"currents.",
"Inspired",
"by",
"the",
"shape",
"and",
"working",
"of",
"a",
"jet,",
"a",
"novel",
"Deep",
"Ensemble",
"Learning",
"using",
"Jet-like",
"Architecture",
"(DEL-Jet)",
"technique",
"is",
"proposed",
"to",
"enhance",
"the",
"diversity",
"and",
"robustness",
"of",
"a",
"learning",
"system",
"against",
"the",
"variations",
"in",
"the",
"input",
"space.",
"The",
"diverse",
"feature",
"spaces",
"of",
"the",
"base-regressors",
"are",
"exploited",
"using",
"the",
"jet-like",
"ensemble",
"architecture.",
"Two",
"Convolutional",
"Neural",
"Networks",
"(as",
"jet",
"wings)",
"and",
"one",
"deep",
"Auto-Encoder",
"(as",
"jet",
"tail)",
"are",
"used",
"to",
"extract",
"the",
"diverse",
"feature",
"spaces",
"from",
"the",
"input",
"data.",
"After",
"that,",
"nonlinear",
"PCA",
"(as",
"jet",
"main",
"body)",
"is",
"employed",
"to",
"reduce",
"the",
"dimensionality",
"of",
"extracted",
"feature",
"space.",
"Finally,",
"both",
"the",
"reduced",
"and",
"the",
"original",
"feature",
"spaces",
"are",
"exploited",
"to",
"train",
"the",
"meta-regressor",
"(as",
"jet",
"nose)",
"for",
"forecasting",
"the",
"wind",
"speed.",
"The",
"performance",
"of",
"the",
"proposed",
"DEL-Jet",
"technique",
"is",
"evaluated",
"for",
"ten",
"independent",
"runs",
"and",
"shows",
"that",
"the",
"deep",
"and",
"jet-like",
"architecture",
"helps",
"in",
"improving",
"the",
"robustness",
"and",
"generalization",
"of",
"the",
"learning",
"system."
] |
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[
"Chinese",
"word",
"segmentation",
"(CWS)",
"is",
"a",
"fundamental",
"task",
"for",
"Chinese",
"language",
"understanding.",
"Recently,",
"neural",
"network-based",
"models",
"have",
"attained",
"superior",
"performance",
"in",
"solving",
"the",
"in-domain",
"CWS",
"task.",
"Last",
"year,",
"Bidirectional",
"Encoder",
"Representation",
"from",
"Transformers",
"(BERT",
"),",
"a",
"new",
"language",
"representation",
"model,",
"has",
"been",
"proposed",
"as",
"a",
"backbone",
"model",
"for",
"many",
"natural",
"language",
"tasks",
"and",
"redefined",
"the",
"corresponding",
"performance.",
"The",
"excellent",
"performance",
"of",
"BERT",
"motivates",
"us",
"to",
"apply",
"it",
"to",
"solve",
"the",
"CWS",
"task.",
"By",
"conducting",
"intensive",
"experiments",
"in",
"the",
"benchmark",
"datasets",
"from",
"the",
"second",
"International",
"Chinese",
"Word",
"Segmentation",
"Bake-off,",
"we",
"obtain",
"several",
"keen",
"observations.",
"BERT",
"can",
"slightly",
"improve",
"the",
"performance",
"even",
"when",
"the",
"datasets",
"contain",
"the",
"issue",
"of",
"labeling",
"inconsistency.",
"When",
"applying",
"sufficiently",
"learned",
"features,",
"Softmax,",
"a",
"simpler",
"classifier,",
"can",
"attain",
"the",
"same",
"performance",
"as",
"that",
"of",
"a",
"more",
"complicated",
"classifier,",
"e.g.,",
"Conditional",
"Random",
"Field",
"(CRF).",
"The",
"performance",
"of",
"BERT",
"usually",
"increases",
"as",
"the",
"model",
"size",
"increases.",
"The",
"features",
"extracted",
"by",
"BERT",
"can",
"be",
"also",
"applied",
"as",
"good",
"candidates",
"for",
"other",
"neural",
"network",
"models."
] |
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[
"Spoken",
"Language",
"Understanding",
"(SLU)",
"mainly",
"involves",
"two",
"tasks,",
"intent",
"detection",
"and",
"slot",
"filling,",
"which",
"are",
"generally",
"modeled",
"jointly",
"in",
"existing",
"works.",
"However,",
"most",
"existing",
"models",
"fail",
"to",
"fully",
"utilize",
"co-occurrence",
"relations",
"between",
"slots",
"and",
"intents,",
"which",
"restricts",
"their",
"potential",
"performance.",
"To",
"address",
"this",
"issue,",
"in",
"this",
"paper",
"we",
"propose",
"a",
"novel",
"Collaborative",
"Memory",
"Network",
"(CM-Net)",
"based",
"on",
"the",
"well-designed",
"block,",
"named",
"CM-block.",
"The",
"CM-block",
"firstly",
"captures",
"slot-specific",
"and",
"intent-specific",
"features",
"from",
"memories",
"in",
"a",
"collaborative",
"manner,",
"and",
"then",
"uses",
"these",
"enriched",
"features",
"to",
"enhance",
"local",
"context",
"representations,",
"based",
"on",
"which",
"the",
"sequential",
"information",
"flow",
"leads",
"to",
"more",
"specific",
"(slot",
"and",
"intent)",
"global",
"utterance",
"representations.",
"Through",
"stacking",
"multiple",
"CM-blocks,",
"our",
"CM-Net",
"is",
"able",
"to",
"alternately",
"perform",
"information",
"exchange",
"among",
"specific",
"memories,",
"local",
"contexts",
"and",
"the",
"global",
"utterance,",
"and",
"thus",
"incrementally",
"enriches",
"each",
"other.",
"We",
"evaluate",
"the",
"CM-Net",
"on",
"two",
"standard",
"benchmarks",
"(ATIS",
"and",
"SNIPS)",
"and",
"a",
"self-collected",
"corpus",
"(CAIS).",
"Experimental",
"results",
"show",
"that",
"the",
"CM-Net",
"achieves",
"the",
"state-of-the-art",
"results",
"on",
"the",
"ATIS",
"and",
"SNIPS",
"in",
"most",
"of",
"criteria,",
"and",
"significantly",
"outperforms",
"the",
"baseline",
"models",
"on",
"the",
"CAIS.",
"Additionally,",
"we",
"make",
"the",
"CAIS",
"dataset",
"publicly",
"available",
"for",
"the",
"research",
"community."
] |
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[
"In",
"this",
"paper",
"a",
"simple",
"and",
"computationally",
"efficient",
"approach",
"as",
"per",
"the",
"complexity",
"has",
"been",
"presented",
"for",
"Automatic",
"Skin",
"Lesion",
"Segmentation",
"using",
"a",
"Deep",
"Learning",
"architecture",
"called",
"SegNet",
"including",
"some",
"additional",
"specifications",
"for",
"the",
"improvisation",
"of",
"the",
"results.",
"The",
"secondary",
"objective",
"is",
"to",
"keep",
"the",
"pre/post",
"#NAME?",
"of",
"the",
"images",
"minimal.",
"The",
"presented",
"model",
"is",
"trained",
"on",
"limited",
"images",
"from",
"the",
"PH2",
"dataset",
"which",
"includes",
"dermoscopic",
"images,",
"manually",
"segmented.",
"It",
"also",
"contains",
"their",
"masks,",
"the",
"clinical",
"diagnosis",
"and",
"the",
"identification",
"of",
"several",
"dermoscopic",
"structures,",
"performed",
"by",
"professional",
"dermatologists.",
"The",
"aim",
"is",
"to",
"achieve",
"a",
"performance",
"threshold",
"Jaccard",
"Index",
"(IOU)",
"92%",
"after",
"evaluation."
] |
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[
"Deep",
"neural",
"networks",
"are",
"widely",
"used",
"in",
"machine",
"learning",
"applications.However,",
"the",
"deployment",
"of",
"large",
"neural",
"networks",
"models",
"can",
"be",
"difficult",
"todeploy",
"on",
"mobile",
"devices",
"with",
"limited",
"power",
"budgets.",
"To",
"solve",
"this",
"problem,",
"wepropose",
"Trained",
"Ternary",
"Quantization",
"(TTQ),",
"a",
"method",
"that",
"can",
"reduce",
"theprecision",
"of",
"weights",
"in",
"neural",
"networks",
"to",
"ternary",
"values.",
"This",
"method",
"has",
"verylittle",
"accuracy",
"degradation",
"and",
"can",
"even",
"improve",
"the",
"accuracy",
"of",
"some",
"models(32,",
"44,",
"56-layer",
"ResNet)",
"on",
"CIFAR-10",
"and",
"AlexNet",
"on",
"ImageNet.",
"And",
"our",
"AlexNet",
"model",
"is",
"trained",
"from",
"scratch,",
"which",
"means",
"it's",
"as",
"easy",
"as",
"to",
"train",
"normal",
"fullprecision",
"model.",
"We",
"highlight",
"our",
"trained",
"quantization",
"method",
"that",
"can",
"learnboth",
"ternary",
"values",
"and",
"ternary",
"assignment.",
"During",
"inference,",
"only",
"ternaryvalues",
"(2-bit",
"weights)",
"and",
"scaling",
"factors",
"are",
"needed,",
"therefore",
"our",
"models",
"arenearly",
"16x",
"smaller",
"than",
"full-precision",
"models.",
"Our",
"ternary",
"models",
"can",
"also",
"beviewed",
"as",
"sparse",
"binary",
"weight",
"networks,",
"which",
"can",
"potentially",
"be",
"acceleratedwith",
"custom",
"circuit.",
"Experiments",
"on",
"CIFAR-10",
"show",
"that",
"the",
"ternary",
"modelsobtained",
"by",
"trained",
"quantization",
"method",
"outperform",
"full-precision",
"models",
"ofResNet-32,44,56",
"by",
"0.04%,",
"0.16%,",
"0.36%,",
"respectively.",
"On",
"ImageNet,",
"our",
"modeloutperforms",
"full-precision",
"AlexNet",
"model",
"by",
"0.30%",
"of",
"Top-1",
"accuracy",
"andoutperforms",
"previous",
"ternary",
"models",
"by",
"3%."
] |
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[
"We",
"present",
"an",
"approach",
"for",
"encoding",
"visual",
"task",
"relationships",
"to",
"improve",
"model",
"performance",
"in",
"an",
"Unsupervised",
"Domain",
"Adaptation",
"(UDA)",
"setting.",
"Semantic",
"segmentation",
"and",
"monocular",
"depth",
"estimation",
"are",
"shown",
"to",
"be",
"complementary",
"tasks;",
"in",
"a",
"multi-task",
"learning",
"setting,",
"a",
"proper",
"encoding",
"of",
"their",
"relationships",
"can",
"further",
"improve",
"performance",
"on",
"both",
"tasks.",
"Motivated",
"by",
"this",
"observation,",
"we",
"propose",
"a",
"novel",
"Cross-Task",
"Relation",
"Layer",
"(CTRL",
"),",
"which",
"encodes",
"task",
"dependencies",
"between",
"the",
"semantic",
"and",
"depth",
"predictions.",
"To",
"capture",
"the",
"cross-task",
"relationships,",
"we",
"propose",
"a",
"neural",
"network",
"architecture",
"that",
"contains",
"task-specific",
"and",
"cross-task",
"refinement",
"heads.",
"Furthermore,",
"we",
"propose",
"an",
"Iterative",
"Self-Learning",
"(ISL)",
"training",
"scheme,",
"which",
"exploits",
"semantic",
"pseudo-labels",
"to",
"provide",
"extra",
"supervision",
"on",
"the",
"target",
"domain.",
"We",
"experimentally",
"observe",
"improvements",
"in",
"both",
"tasks'",
"performance",
"because",
"the",
"complementary",
"information",
"present",
"in",
"these",
"tasks",
"is",
"better",
"captured.",
"Specifically,",
"we",
"show",
"that:",
"-1",
"our",
"approach",
"improves",
"performance",
"on",
"all",
"tasks",
"when",
"they",
"are",
"complementary",
"and",
"mutually",
"dependent;",
"-2",
"the",
"CTRL",
"helps",
"to",
"improve",
"both",
"semantic",
"segmentation",
"and",
"depth",
"estimation",
"tasks",
"performance",
"in",
"the",
"challenging",
"UDA",
"setting;",
"-3",
"the",
"proposed",
"ISL",
"training",
"scheme",
"further",
"improves",
"the",
"semantic",
"segmentation",
"performance.",
"The",
"implementation",
"is",
"available",
"at",
"https://github.com/susaha/ctrl-uda."
] |
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[
"We",
"focus",
"on",
"the",
"problem",
"of",
"capturing",
"declarative",
"knowledge",
"about",
"entities",
"in",
"the",
"learned",
"parameters",
"of",
"a",
"language",
"model.",
"We",
"introduce",
"a",
"new",
"model",
"-",
"Entities",
"as",
"Experts",
"(EAE)",
"-",
"that",
"can",
"access",
"distinct",
"memories",
"of",
"the",
"entities",
"mentioned",
"in",
"a",
"piece",
"of",
"text.",
"Unlike",
"previous",
"efforts",
"to",
"integrate",
"entity",
"knowledge",
"into",
"sequence",
"models,",
"EAE's",
"entity",
"representations",
"are",
"learned",
"directly",
"from",
"text.",
"We",
"show",
"that",
"EAE's",
"learned",
"representations",
"capture",
"sufficient",
"knowledge",
"to",
"answer",
"TriviaQA",
"questions",
"such",
"as",
"Which\tO\nDr.\tO\nWho\tO\nvillain\tO\nhas\tO\nbeen\tO\nplayed\tO\nby\tO\nRoger\tO\nDelgado,\tO\nAnthony\tO\nAinley,\tO\nEric\tO\nRoberts?,",
"outperforming",
"an",
"encoder-generator",
"Transformer",
"model",
"with",
"10x",
"the",
"parameters.",
"According",
"to",
"the",
"LAMA",
"knowledge",
"probes,",
"EAE",
"contains",
"more",
"factual",
"knowledge",
"than",
"a",
"similarly",
"sized",
"BERT,",
"as",
"well",
"as",
"previous",
"approaches",
"that",
"integrate",
"external",
"sources",
"of",
"entity",
"knowledge.",
"Because",
"EAE",
"associates",
"parameters",
"with",
"specific",
"entities,",
"it",
"only",
"needs",
"to",
"access",
"a",
"fraction",
"of",
"its",
"parameters",
"at",
"inference",
"time,",
"and",
"we",
"show",
"that",
"the",
"correct",
"identification",
"and",
"representation",
"of",
"entities",
"is",
"essential",
"to",
"EAE's",
"performance."
] |
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"architecture",
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"modalities",
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"errors",
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",",
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"control",
"distributed",
"interactive",
"simulations",
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[
"Visual",
"Question",
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"(VQA)",
"is",
"a",
"challenging",
"task",
"that",
"has",
"received",
"increasing",
"attention",
"from",
"both",
"the",
"computer",
"vision",
"and",
"the",
"natural",
"language",
"processing",
"communities.",
"A",
"VQA",
"model",
"combines",
"visual",
"and",
"textual",
"features",
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"order",
"to",
"answer",
"questions",
"grounded",
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"an",
"image.",
"Current",
"works",
"in",
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"focus",
"on",
"questions",
"which",
"are",
"answerable",
"by",
"direct",
"analysis",
"of",
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"question",
"and",
"image",
"alone.",
"We",
"present",
"a",
"concept-aware",
"algorithm,",
"ConceptBert,",
"for",
"questions",
"which",
"require",
"common",
"sense,",
"or",
"basic",
"factual",
"knowledge",
"from",
"external",
"structured",
"content.",
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"an",
"image",
"and",
"a",
"question",
"in",
"natural",
"language,",
"ConceptBert",
"requires",
"visual",
"elements",
"of",
"the",
"image",
"and",
"a",
"Knowledge",
"Graph",
"(KG)",
"to",
"infer",
"the",
"correct",
"answer.",
"We",
"introduce",
"a",
"multi-modal",
"representation",
"which",
"learns",
"a",
"joint",
"Concept-Vision-Language",
"embedding",
"inspired",
"by",
"the",
"popular",
"BERT",
"architecture.",
"We",
"exploit",
"ConceptNet",
"KG",
"for",
"encoding",
"the",
"common",
"sense",
"knowledge",
"and",
"evaluate",
"our",
"methodology",
"on",
"the",
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"(OK-VQA)",
"and",
"VQA",
"datasets."
] |
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[
"Recurrent",
"deep",
"learning",
"language",
"models",
"like",
"the",
"LSTM",
"are",
"often",
"used",
"to",
"provide",
"advanced",
"cyber-defense",
"for",
"high-value",
"assets.",
"The",
"underlying",
"assumption",
"for",
"using",
"LSTM",
"networks",
"for",
"malware-detection",
"is",
"that",
"the",
"op-code",
"sequence",
"of",
"malware",
"could",
"be",
"treated",
"as",
"a",
"(spoken)",
"language",
"representation.",
"There",
"are",
"differences",
"between",
"any",
"spoken-language",
"(sequence",
"of",
"words/sentences)",
"and",
"the",
"machine-language",
"(sequence",
"of",
"op-codes).",
"In",
"this",
"paper,",
"we",
"demonstrate",
"that",
"due",
"to",
"these",
"inherent",
"differences,",
"an",
"LSTM",
"model",
"with",
"its",
"default",
"configuration",
"as",
"tuned",
"for",
"a",
"spoken-language,",
"may",
"not",
"work",
"well",
"to",
"detect",
"malware",
"(using",
"its",
"op-code",
"sequence)",
"unless",
"the",
"network's",
"essential",
"hyper-parameters",
"are",
"tuned",
"appropriately.",
"In",
"the",
"process,",
"we",
"also",
"determine",
"the",
"relative",
"importance",
"of",
"all",
"the",
"different",
"hyper-parameters",
"of",
"an",
"LSTM",
"network",
"as",
"applied",
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"malware",
"detection",
"using",
"their",
"op-code",
"sequence",
"representations.",
"We",
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"different",
"configurations",
"of",
"LSTM",
"networks,",
"and",
"altered",
"hyper-parameters",
"like",
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"embedding-size,",
"number",
"of",
"hidden",
"layers,",
"number",
"of",
"LSTM",
"#NAME?",
"in",
"a",
"hidden",
"layer,",
"pruning/padding-length",
"of",
"the",
"input-vector,",
"activation-function,",
"and",
"batch-size.",
"We",
"discovered",
"that",
"owing",
"to",
"the",
"enhanced",
"complexity",
"of",
"the",
"malware/machine-language,",
"the",
"performance",
"of",
"an",
"LSTM",
"network",
"configured",
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"Intrusion",
"Detection",
"System,",
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"very",
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"the",
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"input",
"sequence-length,",
"and",
"the",
"choice",
"of",
"the",
"activation-function.",
"Also,",
"for",
"(spoken)",
"language-modeling,",
"the",
"recurrent",
"architectures",
"by-far",
"outperform",
"their",
"non-recurrent",
"counterparts.",
"Therefore,",
"we",
"also",
"assess",
"how",
"sequential",
"DL",
"architectures",
"like",
"the",
"LSTM",
"compare",
"against",
"their",
"non-sequential",
"counterparts",
"like",
"the",
"MLP-DNN",
"for",
"the",
"purpose",
"of",
"malware-detection."
] |
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[
"Standard",
"video",
"and",
"movie",
"description",
"tasks",
"abstract",
"away",
"from",
"person",
"identities,",
"thus",
"failing",
"to",
"link",
"identities",
"across",
"sentences.",
"We",
"propose",
"a",
"multi-sentence",
"Identity-Aware",
"Video",
"Description",
"task,",
"which",
"overcomes",
"this",
"limitation",
"and",
"requires",
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"persons",
"locally",
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"of",
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"clips.",
"We",
"introduce",
"an",
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"task",
"of",
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"the",
"Identity,",
"that",
"aims",
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"predict",
"persons'",
"IDs",
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"a",
"set",
"of",
"clips,",
"when",
"the",
"video",
"descriptions",
"are",
"given.",
"Our",
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"to",
"this",
"task",
"leverages",
"a",
"Transformer",
"architecture",
"allowing",
"for",
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"joint",
"prediction",
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"One",
"of",
"the",
"key",
"components",
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"gender-aware",
"textual",
"representation",
"as",
"well",
"an",
"additional",
"gender",
"prediction",
"objective",
"in",
"the",
"main",
"model.",
"This",
"auxiliary",
"task",
"allows",
"us",
"to",
"propose",
"a",
"two-stage",
"approach",
"to",
"Identity-Aware",
"Video",
"Description",
".",
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"first",
"generate",
"multi-sentence",
"video",
"descriptions,",
"and",
"then",
"apply",
"our",
"Fill-in",
"the",
"Identity",
"model",
"to",
"establish",
"links",
"between",
"the",
"predicted",
"person",
"entities.",
"To",
"be",
"able",
"to",
"tackle",
"both",
"tasks,",
"we",
"augment",
"the",
"Large",
"Scale",
"Movie",
"Description",
"Challenge",
"(LSMDC)",
"benchmark",
"with",
"new",
"annotations",
"suited",
"for",
"our",
"problem",
"statement.",
"Experiments",
"show",
"that",
"our",
"proposed",
"Fill-in",
"the",
"Identity",
"model",
"is",
"superior",
"to",
"several",
"baselines",
"and",
"recent",
"works,",
"and",
"allows",
"us",
"to",
"generate",
"descriptions",
"with",
"locally",
"re-identified",
"people."
] |
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[
"Document-level",
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"identification",
"is",
"an",
"important",
"subtask",
"in",
"event",
"factuality",
"and",
"is",
"crucial",
"for",
"discourse",
"understanding",
"in",
"Natural",
"Language",
"Processing",
"(NLP).",
"Previous",
"studies",
"mainly",
"suffer",
"from",
"the",
"scarcity",
"of",
"suitable",
"corpus",
"and",
"effective",
"methods.",
"To",
"solve",
"these",
"two",
"issues,",
"we",
"first",
"construct",
"a",
"corpus",
"annotated",
"with",
"both",
"document-",
"and",
"sentence-level",
"event",
"factuality",
"information",
"on",
"both",
"English",
"and",
"Chinese",
"texts.",
"Then",
"we",
"present",
"an",
"LSTM",
"neural",
"network",
"based",
"on",
"adversarial",
"training",
"with",
"both",
"intra-",
"and",
"inter-sequence",
"attentions",
"to",
"identify",
"document-level",
"event",
"factuality.",
"Experimental",
"results",
"show",
"that",
"our",
"neural",
"network",
"model",
"can",
"outperform",
"various",
"baselines",
"on",
"the",
"constructed",
"corpus."
] |
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[
"Lesions",
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"by",
"computed",
"tomography",
"(CT)",
"scans,",
"are",
"arguably",
"oftenelliptical",
"objects.",
"However,",
"current",
"lesion",
"detection",
"systems",
"are",
"predominantlyadopted",
"from",
"the",
"popular",
"Region",
"Proposal",
"Networks",
"(RPN",
"s)",
"that",
"only",
"proposebounding",
"boxes",
"without",
"fully",
"leveraging",
"the",
"elliptical",
"geometry",
"of",
"lesions.",
"Inthis",
"paper,",
"we",
"present",
"Gaussian",
"Proposal",
"Networks",
"(GPNs),",
"a",
"novel",
"extension",
"toRPN",
"s,",
"to",
"detect",
"lesion",
"bounding",
"ellipses.",
"Instead",
"of",
"directly",
"regressing",
"therotation",
"angle",
"of",
"the",
"ellipse",
"as",
"the",
"common",
"practice,",
"GPN",
"represents",
"boundingellipses",
"as",
"2D",
"Gaussian",
"distributions",
"on",
"the",
"image",
"plain",
"and",
"minimizes",
"theKullback-Leibler",
"(KL)",
"divergence",
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"the",
"proposed",
"Gaussian",
"and",
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"groundtruth",
"Gaussian",
"for",
"object",
"localization.",
"We",
"show",
"the",
"KL",
"divergence",
"lossapproximately",
"incarnates",
"the",
"regression",
"loss",
"in",
"the",
"RPN",
"framework",
"when",
"therotation",
"angle",
"is",
"0",
"Experiments",
"on",
"the",
"DeepLesion",
"dataset",
"show",
"that",
"GPNsignificantly",
"outperforms",
"RPN",
"for",
"lesion",
"bounding",
"ellipse",
"detection",
"thanks",
"tolower",
"localization",
"error.",
"GPN",
"is",
"open",
"sourced",
"athttps://github.com/baidu-research/GPN"
] |
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[
"Support",
"Vector",
"Machines",
"(SVM",
"s)",
"are",
"powerful",
"learners",
"that",
"have",
"led",
"tostate-of-the-art",
"results",
"in",
"various",
"computer",
"vision",
"problems.",
"SVM",
"s",
"suffer",
"fromvarious",
"drawbacks",
"in",
"terms",
"of",
"selecting",
"the",
"right",
"kernel,",
"which",
"depends",
"on",
"theimage",
"descriptors,",
"as",
"well",
"as",
"computational",
"and",
"memory",
"efficiency.",
"This",
"paperintroduces",
"a",
"novel",
"kernel,",
"which",
"serves",
"such",
"issues",
"well.",
"The",
"kernel",
"is",
"learnedby",
"exploiting",
"a",
"large",
"amount",
"of",
"low-complex,",
"randomized",
"binary",
"mappings",
"of",
"theinput",
"feature.",
"This",
"leads",
"to",
"an",
"efficient",
"SVM",
",",
"while",
"also",
"alleviating",
"the",
"taskof",
"kernel",
"selection.",
"We",
"demonstrate",
"the",
"capabilities",
"of",
"our",
"kernel",
"on",
"6standard",
"vision",
"benchmarks,",
"in",
"which",
"we",
"combine",
"several",
"common",
"imagedescriptors,",
"namely",
"histograms",
"(Flowers17",
"and",
"Daimler),",
"attribute-likedescriptors",
"(UCI,",
"OSR,",
"and",
"a-VOC08),",
"and",
"Sparse",
"Quantization",
"(ImageNet).Results",
"show",
"that",
"our",
"kernel",
"learning",
"adapts",
"well",
"to",
"the",
"different",
"descriptorstypes,",
"achieving",
"the",
"performance",
"of",
"the",
"kernels",
"specifically",
"tuned",
"for",
"eachimage",
"descriptor,",
"and",
"with",
"similar",
"evaluation",
"cost",
"as",
"efficient",
"SVM",
"methods."
] |
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[
"Dense",
"word",
"vectors",
"or",
"{`}word",
"embeddings{'}",
"which",
"encode",
"semantic",
"properties",
"of",
"words,",
"have",
"now",
"become",
"integral",
"to",
"NLP",
"tasks",
"like",
"Machine",
"Translation",
"(MT),",
"Question",
"Answering",
"(QA),",
"Word",
"Sense",
"Disambiguation",
"(WSD),",
"and",
"Information",
"Retrieval",
"(IR).",
"In",
"this",
"paper,",
"we",
"use",
"various",
"existing",
"approaches",
"to",
"create",
"multiple",
"word",
"embeddings",
"for",
"14",
"Indian",
"languages.",
"We",
"place",
"these",
"embeddings",
"for",
"all",
"these",
"languages,",
"\\textit{viz.},",
"Assamese,",
"Bengali,",
"Gujarati,",
"Hindi,",
"Kannada,",
"Konkani,",
"Malayalam,",
"Marathi,",
"Nepali,",
"Odiya,",
"Punjabi,",
"Sanskrit,",
"Tamil,",
"and",
"Telugu",
"in",
"a",
"single",
"repository.",
"Relatively",
"newer",
"approaches",
"that",
"emphasize",
"catering",
"to",
"context",
"(BERT,",
"ELMo,",
"\\textit{etc.})",
"have",
"shown",
"significant",
"improvements,",
"but",
"require",
"a",
"large",
"amount",
"of",
"resources",
"to",
"generate",
"usable",
"models.",
"We",
"release",
"pre-trained",
"embeddings",
"generated",
"using",
"both",
"contextual",
"and",
"non-contextual",
"approaches.",
"We",
"also",
"use",
"MUSE",
"and",
"XLM",
"to",
"train",
"cross-lingual",
"embeddings",
"for",
"all",
"pairs",
"of",
"the",
"aforementioned",
"languages.",
"To",
"show",
"the",
"efficacy",
"of",
"our",
"embeddings,",
"we",
"evaluate",
"our",
"embedding",
"models",
"on",
"XPOS,",
"UPOS",
"and",
"NER",
"tasks",
"for",
"all",
"these",
"languages.",
"We",
"release",
"a",
"total",
"of",
"436",
"models",
"using",
"8",
"different",
"approaches.",
"We",
"hope",
"they",
"are",
"useful",
"for",
"the",
"resource-constrained",
"Indian",
"language",
"NLP.",
"The",
"title",
"of",
"this",
"paper",
"refers",
"to",
"the",
"famous",
"novel",
"{``}A",
"Passage",
"to",
"India{''}",
"by",
"E.M.",
"Forster,",
"published",
"initially",
"in",
"1924"
] |
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[
"The",
"task",
"of",
"identifying",
"emotions",
"from",
"a",
"given",
"music",
"track",
"has",
"been",
"an",
"active",
"pursuit",
"in",
"the",
"Music",
"Information",
"Retrieval",
"(MIR)",
"community",
"for",
"years.",
"Music",
"emotion",
"recognition",
"has",
"typically",
"relied",
"on",
"acoustic",
"features,",
"social",
"tags,",
"and",
"other",
"metadata",
"to",
"identify",
"and",
"classify",
"music",
"emotions.",
"The",
"role",
"of",
"lyrics",
"in",
"music",
"emotion",
"recognition",
"remains",
"under-appreciated",
"in",
"spite",
"of",
"several",
"studies",
"reporting",
"superior",
"performance",
"of",
"music",
"emotion",
"classifiers",
"based",
"on",
"features",
"extracted",
"from",
"lyrics.",
"In",
"this",
"study,",
"we",
"use",
"the",
"transformer-based",
"approach",
"model",
"using",
"XLNet",
"as",
"the",
"base",
"architecture",
"which,",
"till",
"date,",
"has",
"not",
"been",
"used",
"to",
"identify",
"emotional",
"connotations",
"of",
"music",
"based",
"on",
"lyrics.",
"Our",
"proposed",
"approach",
"outperforms",
"existing",
"methods",
"for",
"multiple",
"datasets.",
"We",
"used",
"a",
"robust",
"methodology",
"to",
"enhance",
"web-crawlers'",
"accuracy",
"for",
"extracting",
"lyrics.",
"This",
"study",
"has",
"important",
"implications",
"in",
"improving",
"applications",
"involved",
"in",
"playlist",
"generation",
"of",
"music",
"based",
"on",
"emotions",
"in",
"addition",
"to",
"improving",
"music",
"recommendation",
"systems."
] |
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[
"Natural",
"language",
"to",
"SQL",
"(NL2SQL)",
"aims",
"to",
"parse",
"a",
"natural",
"language",
"with",
"a",
"given",
"database",
"into",
"a",
"SQL",
"query,",
"which",
"widely",
"appears",
"in",
"practical",
"Internet",
"applications.",
"Jointly",
"encode",
"database",
"schema",
"and",
"question",
"utterance",
"is",
"a",
"difficult",
"but",
"important",
"task",
"in",
"NL2SQL.",
"One",
"solution",
"is",
"to",
"treat",
"the",
"input",
"as",
"a",
"heterogeneous",
"graph.",
"However,",
"it",
"failed",
"to",
"learn",
"good",
"word",
"representation",
"in",
"question",
"utterance.",
"Learning",
"better",
"word",
"representation",
"is",
"important",
"for",
"constructing",
"a",
"well-designed",
"NL2SQL",
"system.",
"To",
"solve",
"the",
"challenging",
"task,",
"we",
"present",
"a",
"Relation",
"aware",
"Semi-autogressive",
"Semantic",
"Parsing",
"(\\MODN)",
"~framework,",
"which",
"is",
"more",
"adaptable",
"for",
"NL2SQL.",
"It",
"first",
"learns",
"relation",
"embedding",
"over",
"the",
"schema",
"entities",
"and",
"question",
"words",
"with",
"predefined",
"schema",
"relations",
"with",
"ELECTRA",
"and",
"relation",
"aware",
"transformer",
"layer",
"as",
"backbone.",
"Then",
"we",
"decode",
"the",
"query",
"SQL",
"with",
"a",
"semi-autoregressive",
"parser",
"and",
"predefined",
"SQL",
"syntax.",
"From",
"empirical",
"results",
"and",
"case",
"study,",
"our",
"model",
"shows",
"its",
"effectiveness",
"in",
"learning",
"better",
"word",
"representation",
"in",
"NL2SQL."
] |
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[
"Transformer-based",
"language",
"models",
"have",
"taken",
"many",
"fields",
"in",
"NLP",
"by",
"storm.",
"BERT",
"and",
"its",
"derivatives",
"dominate",
"most",
"of",
"the",
"existing",
"evaluation",
"benchmarks,",
"including",
"those",
"for",
"Word",
"Sense",
"Disambiguation",
"(WSD),",
"thanks",
"to",
"their",
"ability",
"in",
"capturing",
"context-sensitive",
"semantic",
"nuances.",
"However,",
"there",
"is",
"still",
"little",
"knowledge",
"about",
"their",
"capabilities",
"and",
"potential",
"limitations",
"in",
"encoding",
"and",
"recovering",
"word",
"senses.",
"In",
"this",
"article,",
"we",
"provide",
"an",
"in-depth",
"quantitative",
"and",
"qualitative",
"analysis",
"of",
"the",
"celebrated",
"BERT",
"model",
"with",
"respect",
"to",
"lexical",
"ambiguity.",
"One",
"of",
"the",
"main",
"conclusions",
"of",
"our",
"analysis",
"is",
"that",
"BERT",
"can",
"accurately",
"capture",
"high-level",
"sense",
"distinctions,",
"even",
"when",
"a",
"limited",
"number",
"of",
"examples",
"is",
"available",
"for",
"each",
"word",
"sense.",
"Our",
"analysis",
"also",
"reveals",
"that",
"in",
"some",
"cases",
"language",
"models",
"come",
"close",
"to",
"solving",
"coarse-grained",
"noun",
"disambiguation",
"under",
"ideal",
"conditions",
"in",
"terms",
"of",
"availability",
"of",
"training",
"data",
"and",
"computing",
"resources.",
"However,",
"this",
"scenario",
"rarely",
"occurs",
"in",
"real-world",
"settings",
"and,",
"hence,",
"many",
"practical",
"challenges",
"remain",
"even",
"in",
"the",
"coarse-grained",
"setting.",
"We",
"also",
"perform",
"an",
"in-depth",
"comparison",
"of",
"the",
"two",
"main",
"language",
"model",
"based",
"WSD",
"strategies,",
"i.e.,",
"fine-tuning",
"and",
"feature",
"extraction,",
"finding",
"that",
"the",
"latter",
"approach",
"is",
"more",
"robust",
"with",
"respect",
"to",
"sense",
"bias",
"and",
"it",
"can",
"better",
"exploit",
"limited",
"available",
"training",
"data.",
"In",
"fact,",
"the",
"simple",
"feature",
"extraction",
"strategy",
"of",
"averaging",
"contextualized",
"embeddings",
"proves",
"robust",
"even",
"using",
"only",
"three",
"training",
"sentences",
"per",
"word",
"sense,",
"with",
"minimal",
"improvements",
"obtained",
"by",
"increasing",
"the",
"size",
"of",
"this",
"training",
"data."
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"We",
"present",
"a",
"pilot",
"study",
"of",
"word-sense",
"annotation",
"using",
"multiple",
"annotators",
",",
"relatively",
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"words",
",",
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"corpus",
".",
"Annotators",
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"in",
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",",
"using",
"an",
"annotation",
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",",
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"individual",
"words",
"and",
"their",
"general",
"usage",
"properties",
".",
"Our",
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"is",
"on",
"identifying",
"systematic",
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"words",
"and",
"annotators",
"that",
"can",
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"We",
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"semantic",
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".",
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"in",
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"selection",
"across",
"annotators",
",",
"and",
"present",
"the",
"use",
"of",
"association",
"rules",
"to",
"mine",
"the",
"data",
"for",
"systematic",
"differences",
"across",
"annotators",
"."
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"An",
"accurate",
"seizure",
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"system",
"enables",
"early",
"warnings",
"before",
"seizure",
"onset",
"of",
"epileptic",
"patients.",
"It",
"is",
"extremely",
"important",
"for",
"drug-refractory",
"patients.",
"Conventional",
"seizure",
"prediction",
"works",
"usually",
"rely",
"on",
"features",
"extracted",
"from",
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"(EEG",
")",
"recordings",
"and",
"classification",
"algorithms",
"such",
"as",
"regression",
"or",
"support",
"vector",
"machine",
"(SVM",
")",
"to",
"locate",
"the",
"short",
"time",
"before",
"seizure",
"onset.",
"However,",
"such",
"methods",
"cannot",
"achieve",
"high-accuracy",
"prediction",
"due",
"to",
"information",
"loss",
"of",
"the",
"hand-crafted",
"features",
"and",
"the",
"limited",
"classification",
"ability",
"of",
"regression",
"and",
"SVM",
"algorithms.",
"We",
"propose",
"an",
"end-to-end",
"deep",
"learning",
"solution",
"using",
"a",
"convolutional",
"neural",
"network",
"(CNN)",
"in",
"this",
"paper.",
"One",
"and",
"two",
"dimensional",
"kernels",
"are",
"adopted",
"in",
"the",
"early-",
"and",
"late-stage",
"convolution",
"and",
"max-pooling",
"layers,",
"respectively.",
"The",
"proposed",
"CNN",
"model",
"is",
"evaluated",
"on",
"Kaggle",
"intracranial",
"and",
"CHB-MIT",
"scalp",
"EEG",
"datasets.",
"Overall",
"sensitivity,",
"FALSE",
"prediction",
"rate,",
"and",
"area",
"under",
"receiver",
"operating",
"characteristic",
"curve",
"reaches",
"93.5%,",
"0.063/h,",
"0.981",
"and",
"98.8%,",
"0.074/h,",
"0.988",
"on",
"two",
"datasets",
"respectively.",
"Comparison",
"with",
"state-of-the-art",
"works",
"indicates",
"that",
"the",
"proposed",
"model",
"achieves",
"exceeding",
"prediction",
"performance."
] |
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[
"Common",
"Representation",
"Learning",
"(CRL),",
"wherein",
"different",
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"(orviews)",
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"the",
"data",
"are",
"embedded",
"in",
"a",
"common",
"subspace,",
"is",
"receiving",
"a",
"lot",
"ofattention",
"recently.",
"Two",
"popular",
"paradigms",
"here",
"are",
"Canonical",
"CorrelationAnalysis",
"(CCA)",
"based",
"approaches",
"and",
"Autoencoder",
"(AE",
")",
"based",
"approaches.",
"CCAbased",
"approaches",
"learn",
"a",
"joint",
"representation",
"by",
"maximizing",
"correlation",
"of",
"theviews",
"when",
"projected",
"to",
"the",
"common",
"subspace.",
"AE",
"based",
"methods",
"learn",
"a",
"commonrepresentation",
"by",
"minimizing",
"the",
"error",
"of",
"reconstructing",
"the",
"two",
"views.",
"Each",
"ofthese",
"approaches",
"has",
"its",
"own",
"advantages",
"and",
"disadvantages.",
"For",
"example,",
"whileCCA",
"based",
"approaches",
"outperform",
"AE",
"based",
"approaches",
"for",
"the",
"task",
"of",
"transferlearning,",
"they",
"are",
"not",
"as",
"scalable",
"as",
"the",
"latter.",
"In",
"this",
"work",
"we",
"propose",
"an",
"AE",
"based",
"approach",
"called",
"Correlational",
"Neural",
"Network",
"(CorrNet),",
"that",
"explicitlymaximizes",
"correlation",
"among",
"the",
"views",
"when",
"projected",
"to",
"the",
"common",
"subspace.Through",
"a",
"series",
"of",
"experiments,",
"we",
"demonstrate",
"that",
"the",
"proposed",
"CorrNet",
"isbetter",
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"the",
"above",
"mentioned",
"approaches",
"with",
"respect",
"to",
"its",
"ability",
"to",
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"common",
"representations.",
"Further,",
"we",
"employ",
"CorrNet",
"for",
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"crosslanguage",
"tasks",
"and",
"show",
"that",
"the",
"representations",
"learned",
"using",
"CorrNet",
"performbetter",
"than",
"the",
"ones",
"learned",
"using",
"other",
"state",
"of",
"the",
"art",
"approaches."
] |
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[
"Despite",
"the",
"widespread",
"adoption",
"of",
"deep",
"learning",
"for",
"machine",
"translation,",
"it",
"is",
"still",
"expensive",
"to",
"develop",
"high-quality",
"translation",
"models.",
"In",
"this",
"work,",
"we",
"investigate",
"the",
"use",
"of",
"pre-trained",
"models,",
"such",
"as",
"T5",
"for",
"Portuguese-English",
"and",
"English-Portuguese",
"translation",
"tasks",
"using",
"low-cost",
"hardware.",
"We",
"explore",
"the",
"use",
"of",
"Portuguese",
"and",
"English",
"pre-trained",
"language",
"models",
"and",
"propose",
"an",
"adaptation",
"of",
"the",
"English",
"tokenizer",
"to",
"represent",
"Portuguese",
"characters,",
"such",
"as",
"diaeresis,",
"acute",
"and",
"grave",
"accents.",
"We",
"compare",
"our",
"models",
"to",
"the",
"Google",
"Translate",
"API",
"and",
"MarianMT",
"on",
"a",
"subset",
"of",
"the",
"ParaCrawl",
"dataset,",
"as",
"well",
"as",
"to",
"the",
"winning",
"submission",
"to",
"the",
"WMT19",
"Biomedical",
"Translation",
"Shared",
"Task.",
"We",
"also",
"describe",
"our",
"submission",
"to",
"the",
"WMT20",
"Biomedical",
"Translation",
"Shared",
"Task.",
"Our",
"results",
"show",
"that",
"our",
"models",
"have",
"a",
"competitive",
"performance",
"to",
"state-of-the-art",
"models",
"while",
"being",
"trained",
"on",
"modest",
"hardware",
"(a",
"single",
"8GB",
"gaming",
"GPU",
"for",
"nine",
"days).",
"Our",
"data,",
"models",
"and",
"code",
"are",
"available",
"at",
"https://github.com/unicamp-dl/Lite-T5",
"#NAME?",
"."
] |
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[
"Convolutional",
"Neural",
"Networks",
"(CNNs)",
"have",
"been",
"successfully",
"used",
"in",
"various",
"Music",
"Information",
"Retrieval",
"(MIR)",
"tasks,",
"both",
"as",
"end-to-end",
"models",
"and",
"as",
"feature",
"extractors",
"for",
"more",
"complex",
"systems.",
"However,",
"the",
"MIR",
"field",
"is",
"still",
"dominated",
"by",
"the",
"classical",
"VGG",
"#NAME?",
"CNN",
"architecture",
"variants,",
"often",
"in",
"combination",
"with",
"more",
"complex",
"modules",
"such",
"as",
"attention,",
"and/or",
"techniques",
"such",
"as",
"pre-training",
"on",
"large",
"datasets.",
"Deeper",
"models",
"such",
"as",
"ResNet",
"--",
"which",
"surpassed",
"VGG",
"by",
"a",
"large",
"margin",
"in",
"other",
"domains",
"--",
"are",
"rarely",
"used",
"in",
"MIR.",
"One",
"of",
"the",
"main",
"reasons",
"for",
"this,",
"as",
"we",
"will",
"show,",
"is",
"the",
"lack",
"of",
"generalization",
"of",
"deeper",
"CNNs",
"in",
"the",
"music",
"domain.",
"In",
"this",
"paper,",
"we",
"present",
"a",
"principled",
"way",
"to",
"make",
"deep",
"architectures",
"like",
"ResNet",
"competitive",
"for",
"music-related",
"tasks,",
"based",
"on",
"well-designed",
"regularization",
"strategies.",
"In",
"particular,",
"we",
"analyze",
"the",
"recently",
"introduced",
"Receptive-Field",
"Regularization",
"and",
"Shake-Shake,",
"and",
"show",
"that",
"they",
"significantly",
"improve",
"the",
"generalization",
"of",
"deep",
"CNNs",
"on",
"music-related",
"tasks,",
"and",
"that",
"the",
"resulting",
"deep",
"CNNs",
"can",
"outperform",
"current",
"more",
"complex",
"models",
"such",
"as",
"CNNs",
"augmented",
"with",
"pre-training",
"and",
"attention.",
"We",
"demonstrate",
"this",
"on",
"two",
"different",
"MIR",
"tasks",
"and",
"two",
"corresponding",
"datasets,",
"thus",
"offering",
"our",
"deep",
"regularized",
"CNNs",
"as",
"a",
"new",
"baseline",
"for",
"these",
"datasets,",
"which",
"can",
"also",
"be",
"used",
"as",
"a",
"feature-extracting",
"module",
"in",
"future,",
"more",
"complex",
"approaches."
] |
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[
"We",
"propose",
"RIFE",
",",
"a",
"Real-time",
"Intermediate",
"Flow",
"Estimation",
"algorithm",
"for",
"Video",
"Frame",
"Interpolation",
"(VFI).",
"Many",
"recent",
"flow-based",
"VFI",
"methods",
"first",
"estimate",
"the",
"bi-directional",
"optical",
"flows,",
"then",
"scale",
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"reverse",
"them",
"to",
"approximate",
"intermediate",
"flows,",
"leading",
"to",
"artifacts",
"on",
"motion",
"boundaries.",
"RIFE",
"uses",
"a",
"neural",
"network",
"named",
"IFNet",
"that",
"can",
"directly",
"estimate",
"the",
"intermediate",
"flows",
"from",
"coarse-to-fine",
"with",
"much",
"better",
"speed.",
"We",
"design",
"a",
"privileged",
"distillation",
"scheme",
"for",
"training",
"intermediate",
"flow",
"model,",
"which",
"leads",
"to",
"a",
"large",
"performance",
"improvement.",
"Experiments",
"demonstrate",
"that",
"RIFE",
"is",
"flexible",
"and",
"can",
"achieve",
"state-of-the-art",
"performance",
"on",
"several",
"public",
"benchmarks.",
"The",
"code",
"is",
"available",
"at",
"\\url{https://github.com/hzwer/arXiv2020-RIFE",
"}"
] |
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[
"A",
"limiting",
"factor",
"towards",
"the",
"wide",
"routine",
"use",
"of",
"wearables",
"devices",
"for",
"continuous",
"healthcare",
"monitoring",
"is",
"their",
"cumbersome",
"and",
"obtrusive",
"nature.",
"This",
"is",
"particularly",
"TRUE",
"for",
"electroencephalography",
"(EEG",
")",
"recordings,",
"which",
"require",
"the",
"placement",
"of",
"multiple",
"electrodes",
"in",
"contact",
"with",
"the",
"scalp.",
"In",
"this",
"work,",
"we",
"propose",
"to",
"identify",
"the",
"optimal",
"wearable",
"EEG",
"electrode",
"set-up,",
"in",
"terms",
"of",
"minimal",
"number",
"of",
"electrodes,",
"comfortable",
"location",
"and",
"performance,",
"for",
"EEG",
"#NAME?",
"event",
"detection",
"and",
"monitoring.",
"By",
"relying",
"on",
"the",
"demonstrated",
"power",
"of",
"autoencoder",
"(AE",
")",
"networks",
"to",
"learn",
"latent",
"representations",
"from",
"high-dimensional",
"data,",
"our",
"proposed",
"strategy",
"trains",
"an",
"AE",
"architecture",
"in",
"a",
"one-class",
"classification",
"setup",
"with",
"different",
"electrode",
"set-ups",
"as",
"input",
"data.",
"The",
"resulting",
"models",
"are",
"assessed",
"using",
"the",
"F-score",
"and",
"the",
"best",
"set-up",
"is",
"chosen",
"according",
"to",
"the",
"established",
"optimal",
"criteria.",
"Using",
"alpha",
"wave",
"detection",
"as",
"use",
"case,",
"we",
"demonstrate",
"that",
"the",
"proposed",
"method",
"allows",
"to",
"detect",
"an",
"alpha",
"state",
"from",
"an",
"optimal",
"set-up",
"consisting",
"of",
"electrodes",
"in",
"the",
"forehead",
"and",
"behind",
"the",
"ear,",
"with",
"an",
"average",
"F-score",
"of",
"0.78.",
"Our",
"results",
"suggest",
"that",
"a",
"learning-based",
"approach",
"can",
"be",
"used",
"to",
"enable",
"the",
"design",
"and",
"implementation",
"of",
"optimized",
"wearable",
"devices",
"for",
"real-life",
"healthcare",
"monitoring."
] |
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[
"Researches",
"have",
"demonstrated",
"that",
"low",
"bit-width",
"(e.g.,",
"INT8)",
"quantization",
"can",
"be",
"employed",
"to",
"accelerate",
"the",
"inference",
"process.",
"It",
"makes",
"the",
"gradient",
"quantization",
"very",
"promising",
"since",
"the",
"backward",
"propagation",
"requires",
"approximately",
"twice",
"more",
"computation",
"than",
"forward",
"one.",
"Due",
"to",
"the",
"variability",
"and",
"uncertainty",
"of",
"gradient",
"distribution,",
"a",
"lot",
"of",
"methods",
"have",
"been",
"proposed",
"to",
"attain",
"training",
"stability.",
"However,",
"most",
"of",
"them",
"ignore",
"the",
"channel-wise",
"gradient",
"distributions",
"and",
"the",
"impact",
"of",
"gradients",
"with",
"different",
"magnitudes,",
"resulting",
"in",
"the",
"degradation",
"of",
"final",
"accuracy.",
"In",
"this",
"paper,",
"we",
"propose",
"a",
"novel",
"INT8",
"quantization",
"training",
"framework",
"for",
"convolutional",
"neural",
"network",
"to",
"address",
"the",
"above",
"issues.",
"Specifically,",
"we",
"adopt",
"Gradient",
"Vectorized",
"Quantization",
"to",
"quantize",
"the",
"gradient,",
"based",
"on",
"the",
"observation",
"that",
"layer-wise",
"gradients",
"contain",
"multiple",
"distributions",
"along",
"the",
"channel",
"dimension.",
"Then,",
"Magnitude-aware",
"Clipping",
"Strategy",
"is",
"introduced",
"by",
"taking",
"the",
"magnitudes",
"of",
"gradients",
"into",
"consideration",
"when",
"minimizing",
"the",
"quantization",
"error,",
"and",
"we",
"present",
"a",
"theoretical",
"derivation",
"to",
"solve",
"the",
"quantization",
"parameters",
"of",
"different",
"distributions.",
"Experimental",
"results",
"on",
"broad",
"range",
"of",
"computer",
"vision",
"tasks,",
"such",
"as",
"image",
"classification,",
"object",
"detection",
"and",
"video",
"classification,",
"demonstrate",
"that",
"the",
"proposed",
"Distribution",
"Adaptive",
"INT8",
"Quantization",
"training",
"method",
"has",
"achieved",
"almost",
"lossless",
"training",
"accuracy",
"for",
"different",
"backbones,",
"including",
"ResNet,",
"MobileNetV2,",
"InceptionV3,",
"VGG",
"and",
"AlexNet,",
"which",
"is",
"superior",
"to",
"the",
"state-of-the-art",
"techniques.",
"Moreover,",
"we",
"further",
"implement",
"the",
"INT8",
"kernel",
"that",
"can",
"accelerate",
"the",
"training",
"iteration",
"more",
"than",
"200%",
"under",
"the",
"latest",
"Turing",
"architecture,",
"i.e.,",
"our",
"method",
"excels",
"on",
"both",
"training",
"accuracy",
"and",
"speed."
] |
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[
"The",
"monitoring",
"of",
"rotating",
"machinery",
"is",
"an",
"essential",
"task",
"in",
"today's",
"production",
"processes.",
"Currently,",
"several",
"machine",
"learning",
"and",
"deep",
"learning-based",
"modules",
"have",
"achieved",
"excellent",
"results",
"in",
"fault",
"detection",
"and",
"diagnosis.",
"Nevertheless,",
"to",
"further",
"increase",
"user",
"adoption",
"and",
"diffusion",
"of",
"such",
"technologies,",
"users",
"and",
"human",
"experts",
"must",
"be",
"provided",
"with",
"explanations",
"and",
"insights",
"by",
"the",
"modules.",
"Another",
"issue",
"is",
"related,",
"in",
"most",
"cases,",
"with",
"the",
"unavailability",
"of",
"labeled",
"historical",
"data",
"that",
"makes",
"the",
"use",
"of",
"supervised",
"models",
"unfeasible.",
"Therefore,",
"a",
"new",
"approach",
"for",
"fault",
"detection",
"and",
"diagnosis",
"in",
"rotating",
"machinery",
"is",
"here",
"proposed.",
"The",
"methodology",
"consists",
"of",
"three",
"parts:",
"feature",
"extraction,",
"fault",
"detection",
"and",
"fault",
"diagnosis.",
"In",
"the",
"first",
"part,",
"the",
"vibration",
"features",
"in",
"the",
"time",
"and",
"frequency",
"domains",
"are",
"extracted.",
"Secondly,",
"in",
"the",
"fault",
"detection,",
"the",
"presence",
"of",
"fault",
"is",
"verified",
"in",
"an",
"unsupervised",
"manner",
"based",
"on",
"anomaly",
"detection",
"algorithms.",
"The",
"modularity",
"of",
"the",
"methodology",
"allows",
"different",
"algorithms",
"to",
"be",
"implemented.",
"Finally,",
"in",
"fault",
"diagnosis,",
"Shapley",
"Additive",
"Explanations",
"(SHAP",
"),",
"a",
"technique",
"to",
"interpret",
"black-box",
"models,",
"is",
"used.",
"Through",
"the",
"feature",
"importance",
"ranking",
"obtained",
"by",
"the",
"model",
"explainability,",
"the",
"fault",
"diagnosis",
"is",
"performed.",
"Two",
"tools",
"for",
"diagnosis",
"are",
"proposed,",
"namely:",
"unsupervised",
"classification",
"and",
"root",
"cause",
"analysis.",
"The",
"effectiveness",
"of",
"the",
"proposed",
"approach",
"is",
"shown",
"on",
"three",
"datasets",
"containing",
"different",
"mechanical",
"faults",
"in",
"rotating",
"machinery.",
"The",
"study",
"also",
"presents",
"a",
"comparison",
"between",
"models",
"used",
"in",
"machine",
"learning",
"explainability:",
"SHAP",
"and",
"Local",
"Depth-based",
"Feature",
"Importance",
"for",
"the",
"Isolation",
"Forest",
"(Local-",
"DIFFI).",
"Lastly,",
"an",
"analysis",
"of",
"several",
"state-of-art",
"anomaly",
"detection",
"algorithms",
"in",
"rotating",
"machinery",
"is",
"included."
] |
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[
"Naturally",
"introduced",
"perturbations",
"in",
"audio",
"signal,",
"caused",
"by",
"emotional",
"and",
"physical",
"states",
"of",
"the",
"speaker,",
"can",
"significantly",
"degrade",
"the",
"performance",
"of",
"Automatic",
"Speech",
"Recognition",
"(ASR)",
"systems.",
"In",
"this",
"paper,",
"we",
"propose",
"a",
"front-end",
"based",
"on",
"Cycle-Consistent",
"Generative",
"Adversarial",
"Network",
"(CycleGAN",
")",
"which",
"transforms",
"naturally",
"perturbed",
"speech",
"into",
"normal",
"speech,",
"and",
"hence",
"improves",
"the",
"robustness",
"of",
"an",
"ASR",
"system.",
"The",
"CycleGAN",
"model",
"is",
"trained",
"on",
"non-parallel",
"examples",
"of",
"perturbed",
"and",
"normal",
"speech.",
"Experiments",
"on",
"spontaneous",
"laughter-speech",
"and",
"creaky-speech",
"datasets",
"show",
"that",
"the",
"performance",
"of",
"four",
"different",
"ASR",
"systems",
"improve",
"by",
"using",
"speech",
"obtained",
"from",
"CycleGAN",
"based",
"front-end,",
"as",
"compared",
"to",
"directly",
"using",
"the",
"original",
"perturbed",
"speech.",
"Visualization",
"of",
"the",
"features",
"of",
"the",
"laughter",
"perturbed",
"speech",
"and",
"those",
"generated",
"by",
"the",
"proposed",
"front-end",
"further",
"demonstrates",
"the",
"effectiveness",
"of",
"our",
"approach."
] |
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[
"Chatter",
"detection",
"from",
"sensor",
"signals",
"has",
"been",
"an",
"active",
"field",
"of",
"research.",
"While",
"some",
"success",
"has",
"been",
"reported",
"using",
"several",
"featurization",
"tools",
"and",
"machine",
"learning",
"algorithms,",
"existing",
"methods",
"have",
"several",
"drawbacks",
"such",
"as",
"manual",
"preprocessing",
"and",
"requiring",
"a",
"large",
"data",
"set.",
"In",
"this",
"paper,",
"we",
"present",
"an",
"alternative",
"approach",
"for",
"chatter",
"detection",
"based",
"on",
"K-Nearest",
"Neighbor",
"(kNN)",
"algorithm",
"for",
"classification",
"and",
"the",
"Dynamic",
"Time",
"Warping",
"(DTW",
")",
"as",
"a",
"time",
"series",
"similarity",
"measure.",
"The",
"used",
"time",
"series",
"are",
"the",
"acceleration",
"signals",
"acquired",
"from",
"the",
"tool",
"holder",
"in",
"a",
"series",
"of",
"turning",
"experiments.",
"Our",
"results,",
"show",
"that",
"this",
"approach",
"achieves",
"detection",
"accuracies",
"that",
"in",
"most",
"cases",
"outperform",
"existing",
"methods.",
"We",
"compare",
"our",
"results",
"to",
"the",
"traditional",
"methods",
"based",
"on",
"Wavelet",
"Packet",
"Transform",
"(WPT)",
"and",
"the",
"Ensemble",
"Empirical",
"Mode",
"Decomposition",
"(EEMD),",
"as",
"well",
"as",
"to",
"the",
"more",
"recent",
"Topological",
"Data",
"Analysis",
"(TDA)",
"based",
"approach.",
"We",
"show",
"that",
"in",
"three",
"out",
"of",
"four",
"cutting",
"configurations",
"our",
"DTW",
"#NAME?",
"approach",
"attains",
"the",
"highest",
"average",
"classification",
"rate",
"reaching",
"in",
"one",
"case",
"as",
"high",
"as",
"99%",
"accuracy.",
"Our",
"approach",
"does",
"not",
"require",
"feature",
"extraction,",
"is",
"capable",
"of",
"reusing",
"a",
"classifier",
"across",
"different",
"cutting",
"configurations,",
"and",
"it",
"uses",
"reasonably",
"sized",
"training",
"sets.",
"Although",
"the",
"resulting",
"high",
"accuracy",
"in",
"our",
"approach",
"is",
"associated",
"with",
"high",
"computational",
"cost,",
"this",
"is",
"specific",
"to",
"the",
"DTW",
"implementation",
"that",
"we",
"used.",
"Specifically,",
"we",
"highlight",
"available,",
"very",
"fast",
"DTW",
"implementations",
"that",
"can",
"even",
"be",
"implemented",
"on",
"small",
"consumer",
"electronics.",
"Therefore,",
"further",
"code",
"optimization",
"and",
"the",
"significantly",
"reduced",
"computational",
"effort",
"during",
"the",
"implementation",
"phase",
"make",
"our",
"approach",
"a",
"viable",
"option",
"for",
"in-process",
"chatter",
"detection."
] |
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"Subject",
"ellipsis",
"is",
"one",
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"the",
"characteristics",
"of",
"informal",
"English",
".",
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"investigation",
"of",
"subject",
"ellipsis",
"in",
"corpora",
"thus",
"reveals",
"an",
"abundance",
"of",
"pragmatic",
"and",
"extralinguistic",
"information",
"associated",
"with",
"subject",
"ellipsis",
"that",
"enhances",
"natural",
"language",
"understanding",
".",
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"essence",
",",
"the",
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"polite",
",",
"intimate",
",",
"friendly",
",",
"and",
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"determinate",
"implicatures",
".",
"This",
"paper",
"also",
"construes",
"linguistic",
"environments",
"that",
"triger",
"the",
"use",
"of",
"subject",
"ellipsis",
"and",
"resolve",
"subject",
"elipsis",
"."
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"A",
"recent",
"technical",
"breakthrough",
"in",
"the",
"domain",
"of",
"machine",
"learning",
"is",
"thediscovery",
"and",
"the",
"multiple",
"applications",
"of",
"Generative",
"Adversarial",
"Networks(GAN",
"s).",
"Those",
"generative",
"models",
"are",
"computationally",
"demanding,",
"as",
"a",
"GAN",
"iscomposed",
"of",
"two",
"deep",
"neural",
"networks,",
"and",
"because",
"it",
"trains",
"on",
"large",
"datasets.A",
"GAN",
"is",
"generally",
"trained",
"on",
"a",
"single",
"server.",
"In",
"this",
"paper,",
"we",
"address",
"the",
"problem",
"of",
"distributing",
"GAN",
"s",
"so",
"that",
"they",
"areable",
"to",
"train",
"over",
"datasets",
"that",
"are",
"spread",
"on",
"multiple",
"workers.",
"MD-GAN",
"isexposed",
"as",
"the",
"first",
"solution",
"for",
"this",
"problem:",
"we",
"propose",
"a",
"novel",
"learningprocedure",
"for",
"GAN",
"s",
"so",
"that",
"they",
"fit",
"this",
"distributed",
"setup.",
"We",
"then",
"compare",
"theperformance",
"of",
"MD-GAN",
"to",
"an",
"adapted",
"version",
"of",
"Federated",
"Learning",
"to",
"GAN",
"s,using",
"the",
"MNIST",
"and",
"CIFAR10",
"datasets.",
"MD-GAN",
"exhibits",
"a",
"reduction",
"by",
"a",
"factorof",
"two",
"of",
"the",
"learning",
"complexity",
"on",
"each",
"worker",
"node,",
"while",
"providing",
"betterperformances",
"than",
"federated",
"learning",
"on",
"both",
"datasets.",
"We",
"finally",
"discuss",
"thepractical",
"implications",
"of",
"distributing",
"GAN",
"s."
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[
"Acquiring",
"High",
"Resolution",
"(HR)",
"Magnetic",
"Resonance",
"(MR)",
"images",
"requires",
"the",
"patient",
"to",
"remain",
"still",
"for",
"long",
"periods",
"of",
"time,",
"which",
"causes",
"patient",
"discomfort",
"and",
"increases",
"the",
"probability",
"of",
"motion",
"induced",
"image",
"artifacts.",
"A",
"possible",
"solution",
"is",
"to",
"acquire",
"low",
"resolution",
"(LR)",
"images",
"and",
"to",
"process",
"them",
"with",
"the",
"Super",
"Resolution",
"Generative",
"Adversarial",
"Network",
"(SRGAN",
")",
"to",
"create",
"a",
"super-resolved",
"version.",
"This",
"work",
"applies",
"SRGAN",
"to",
"MR",
"images",
"of",
"the",
"prostate",
"and",
"performs",
"three",
"experiments.",
"The",
"first",
"experiment",
"explores",
"improving",
"the",
"in-plane",
"MR",
"image",
"resolution",
"by",
"factors",
"of",
"4",
"and",
"8,",
"and",
"shows",
"that,",
"while",
"the",
"PSNR",
"and",
"SSIM",
"(Structural",
"SIMilarity)",
"metrics",
"are",
"lower",
"than",
"the",
"isotropic",
"bicubic",
"interpolation",
"baseline,",
"the",
"SRGAN",
"is",
"able",
"to",
"create",
"images",
"that",
"have",
"high",
"edge",
"fidelity.",
"The",
"second",
"experiment",
"explores",
"anisotropic",
"super-resolution",
"via",
"synthetic",
"images,",
"in",
"that",
"the",
"input",
"images",
"to",
"the",
"network",
"are",
"anisotropically",
"downsampled",
"versions",
"of",
"HR",
"images.",
"This",
"experiment",
"demonstrates",
"the",
"ability",
"of",
"the",
"modified",
"SRGAN",
"to",
"perform",
"anisotropic",
"super-resolution,",
"with",
"quantitative",
"image",
"metrics",
"that",
"are",
"comparable",
"to",
"those",
"of",
"the",
"anisotropic",
"bicubic",
"interpolation",
"baseline.",
"Finally,",
"the",
"third",
"experiment",
"applies",
"a",
"modified",
"version",
"of",
"the",
"SRGAN",
"to",
"super-resolve",
"anisotropic",
"images",
"obtained",
"from",
"the",
"through-plane",
"slices",
"of",
"the",
"volumetric",
"MR",
"data.",
"The",
"output",
"super-resolved",
"images",
"contain",
"a",
"significant",
"amount",
"of",
"high",
"frequency",
"information",
"that",
"make",
"them",
"visually",
"close",
"to",
"their",
"HR",
"counterparts.",
"Overall,",
"the",
"promising",
"results",
"from",
"each",
"experiment",
"show",
"that",
"super-resolution",
"for",
"MR",
"images",
"is",
"a",
"successful",
"technique",
"and",
"that",
"producing",
"isotropic",
"MR",
"image",
"volumes",
"from",
"anisotropic",
"slices",
"is",
"an",
"achievable",
"goal."
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[
"In",
"this",
"paper,",
"we",
"propose",
"a",
"novel",
"Question-Guided",
"Hybrid",
"Convolution",
"(QGHC)network",
"for",
"Visual",
"Question",
"Answering",
"(VQA).",
"Most",
"state-of-the-art",
"VQA",
"methodsfuse",
"the",
"high-level",
"textual",
"and",
"visual",
"features",
"from",
"the",
"neural",
"network",
"andabandon",
"the",
"visual",
"spatial",
"information",
"when",
"learning",
"multi-modal",
"features.Toaddress",
"these",
"problems,",
"question-guided",
"kernels",
"generated",
"from",
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"inputquestion",
"are",
"designed",
"to",
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"with",
"visual",
"features",
"for",
"capturing",
"thetextual",
"and",
"visual",
"relationship",
"in",
"the",
"early",
"stage.",
"The",
"question-guidedconvolution",
"can",
"tightly",
"couple",
"the",
"textual",
"and",
"visual",
"information",
"but",
"alsointroduce",
"more",
"parameters",
"when",
"learning",
"kernels.",
"We",
"apply",
"the",
"groupconvolution,",
"which",
"consists",
"of",
"question-independent",
"kernels",
"andquestion-dependent",
"kernels,",
"to",
"reduce",
"the",
"parameter",
"size",
"and",
"alleviateover-fitting.",
"The",
"hybrid",
"convolution",
"can",
"generate",
"discriminative",
"multi-modalfeatures",
"with",
"fewer",
"parameters.",
"The",
"proposed",
"approach",
"is",
"also",
"complementary",
"toexisting",
"bilinear",
"pooling",
"fusion",
"and",
"attention",
"based",
"VQA",
"methods.",
"Byintegrating",
"with",
"them,",
"our",
"method",
"could",
"further",
"boost",
"the",
"performance.Extensive",
"experiments",
"on",
"public",
"VQA",
"datasets",
"validate",
"the",
"effectiveness",
"ofQGHC."
] |
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[
"Quantization",
"of",
"the",
"parameters",
"of",
"machine",
"learning",
"models,",
"such",
"as",
"deep",
"neural",
"networks,",
"requires",
"solving",
"constrained",
"optimization",
"problems,",
"where",
"the",
"constraint",
"set",
"is",
"formed",
"by",
"the",
"Cartesian",
"product",
"of",
"many",
"simple",
"discrete",
"sets.",
"For",
"such",
"optimization",
"problems,",
"we",
"study",
"the",
"performance",
"of",
"the",
"Alternating",
"Direction",
"Method",
"of",
"Multipliers",
"for",
"Quantization",
"($\\texttt{ADMM",
"-Q}$)",
"algorithm,",
"which",
"is",
"a",
"variant",
"of",
"the",
"widely-used",
"ADMM",
"method",
"applied",
"to",
"our",
"discrete",
"optimization",
"problem.",
"We",
"establish",
"the",
"convergence",
"of",
"the",
"iterates",
"of",
"$\\texttt{ADMM",
"-Q}$",
"to",
"certain",
"$\\textit{stationary",
"points}$.",
"To",
"the",
"best",
"of",
"our",
"knowledge,",
"this",
"is",
"the",
"first",
"analysis",
"of",
"an",
"ADMM",
"#NAME?",
"method",
"for",
"problems",
"with",
"discrete",
"variables/constraints.",
"Based",
"on",
"our",
"theoretical",
"insights,",
"we",
"develop",
"a",
"few",
"variants",
"of",
"$\\texttt{ADMM",
"-Q}$",
"that",
"can",
"handle",
"inexact",
"update",
"rules,",
"and",
"have",
"improved",
"performance",
"via",
"the",
"use",
"of",
"soft\tO\nprojection",
"and",
"injecting\tO\nrandomness\tO\nto\tO\nthe\tO\nalgorithm.",
"We",
"empirically",
"evaluate",
"the",
"efficacy",
"of",
"our",
"proposed",
"approaches."
] |
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[
"The",
"generative",
"adversarial",
"imitation",
"learning",
"(GAIL",
")",
"has",
"provided",
"an",
"adversarial",
"learning",
"framework",
"for",
"imitating",
"expert",
"policy",
"from",
"demonstrations",
"in",
"high-dimensional",
"continuous",
"tasks.",
"However,",
"almost",
"all",
"GAIL",
"and",
"its",
"extensions",
"only",
"design",
"a",
"kind",
"of",
"reward",
"function",
"of",
"logarithmic",
"form",
"in",
"the",
"adversarial",
"training",
"strategy",
"with",
"the",
"Jensen-Shannon",
"(JS)",
"divergence",
"for",
"all",
"complex",
"environments.",
"The",
"fixed",
"logarithmic",
"type",
"of",
"reward",
"function",
"may",
"be",
"difficult",
"to",
"solve",
"all",
"complex",
"tasks,",
"and",
"the",
"vanishing",
"gradients",
"problem",
"caused",
"by",
"the",
"JS",
"divergence",
"will",
"harm",
"the",
"adversarial",
"learning",
"process.",
"In",
"this",
"paper,",
"we",
"propose",
"a",
"new",
"algorithm",
"named",
"Wasserstein",
"Distance",
"guided",
"Adversarial",
"Imitation",
"Learning",
"(WDAIL)",
"for",
"promoting",
"the",
"performance",
"of",
"imitation",
"learning",
"(IL).",
"There",
"are",
"three",
"improvements",
"in",
"our",
"method:",
"(a)",
"introducing",
"the",
"Wasserstein",
"distance",
"to",
"obtain",
"more",
"appropriate",
"measure",
"in",
"the",
"adversarial",
"training",
"process,",
"(b)",
"using",
"proximal",
"policy",
"optimization",
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"in",
"the",
"reinforcement",
"learning",
"stage",
"which",
"is",
"much",
"simpler",
"to",
"implement",
"and",
"makes",
"the",
"algorithm",
"more",
"efficient,",
"and",
"(c)",
"exploring",
"different",
"reward",
"function",
"shapes",
"to",
"suit",
"different",
"tasks",
"for",
"improving",
"the",
"performance.",
"The",
"experiment",
"results",
"show",
"that",
"the",
"learning",
"procedure",
"remains",
"remarkably",
"stable,",
"and",
"achieves",
"significant",
"performance",
"in",
"the",
"complex",
"continuous",
"control",
"tasks",
"of",
"MuJoCo."
] |
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[
"In",
"recent",
"years,",
"Deep",
"Learning",
"(DL)",
"models",
"are",
"becoming",
"important",
"due",
"to",
"their",
"demonstrated",
"success",
"at",
"overcoming",
"complex",
"learning",
"problems.",
"DL",
"models",
"have",
"been",
"applied",
"effectively",
"for",
"different",
"Natural",
"Language",
"Processing",
"(NLP)",
"tasks",
"such",
"as",
"part-of-Speech",
"(PoS)",
"tagging",
"and",
"Machine",
"Translation",
"(MT).",
"Disease",
"Named",
"Entity",
"Recognition",
"(Disease-NER)",
"is",
"a",
"crucial",
"task",
"which",
"aims",
"at",
"extracting",
"disease",
"Named",
"Entities",
"(NEs)",
"from",
"text.",
"In",
"this",
"paper,",
"a",
"DL",
"model",
"for",
"Disease-NER",
"using",
"dictionary",
"information",
"is",
"proposed",
"and",
"evaluated",
"on",
"National",
"Center",
"for",
"Biotechnology",
"Information",
"(NCBI)",
"disease",
"corpus",
"and",
"BC5CDR",
"dataset.",
"Word",
"embeddings",
"trained",
"over",
"general",
"domain",
"texts",
"as",
"well",
"as",
"biomedical",
"texts",
"have",
"been",
"used",
"to",
"represent",
"input",
"to",
"the",
"proposed",
"model.",
"This",
"study",
"also",
"compares",
"two",
"different",
"Segment",
"Representation",
"(SR)",
"schemes,",
"namely",
"IOB2",
"and",
"IOBES",
"for",
"Disease-NER.",
"The",
"results",
"illustrate",
"that",
"using",
"dictionary",
"information,",
"pre-trained",
"word",
"embeddings,",
"character",
"embeddings",
"and",
"CRF",
"with",
"global",
"score",
"improves",
"the",
"performance",
"of",
"Disease-NER",
"system."
] |
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[
"Spatial",
"clustering",
"techniques",
"can",
"achieve",
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"multi-channel",
"noise",
"reduction",
"across",
"relatively",
"arbitrary",
"microphone",
"configurations,",
"but",
"have",
"difficulty",
"incorporating",
"a",
"detailed",
"speech/noise",
"model.",
"In",
"contrast,",
"LSTM",
"neural",
"networks",
"have",
"successfully",
"been",
"trained",
"to",
"recognize",
"speech",
"from",
"noise",
"on",
"single-channel",
"inputs,",
"but",
"have",
"difficulty",
"taking",
"full",
"advantage",
"of",
"the",
"information",
"in",
"multi-channel",
"recordings.",
"This",
"paper",
"integrates",
"these",
"two",
"approaches,",
"training",
"LSTM",
"speech",
"models",
"to",
"clean",
"the",
"masks",
"generated",
"by",
"the",
"Model-based",
"EM",
"Source",
"Separation",
"and",
"Localization",
"(MESSL)",
"spatial",
"clustering",
"method.",
"By",
"doing",
"so,",
"it",
"attains",
"both",
"the",
"spatial",
"separation",
"performance",
"and",
"generality",
"of",
"multi-channel",
"spatial",
"clustering",
"and",
"the",
"signal",
"modeling",
"performance",
"of",
"multiple",
"parallel",
"single-channel",
"LSTM",
"speech",
"enhancers.",
"Our",
"experiments",
"show",
"that",
"when",
"our",
"system",
"is",
"applied",
"to",
"the",
"CHiME-3",
"dataset",
"of",
"noisy",
"tablet",
"recordings,",
"it",
"increases",
"speech",
"quality",
"as",
"measured",
"by",
"the",
"Perceptual",
"Evaluation",
"of",
"Speech",
"Quality",
"(PESQ)",
"algorithm",
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"reduces",
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"word",
"error",
"rate",
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"the",
"baseline",
"CHiME-3",
"speech",
"recognizer,",
"as",
"compared",
"to",
"the",
"default",
"BeamformIt",
"beamformer."
] |
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[
"The",
"upsurge",
"of",
"prolific",
"blogging",
"and",
"microblogging",
"platforms",
"enabled",
"the",
"abusers",
"to",
"spread",
"negativity",
"and",
"threats",
"greater",
"than",
"ever.",
"Detecting",
"the",
"toxic",
"portions",
"substantially",
"aids",
"to",
"moderate",
"or",
"exclude",
"the",
"abusive",
"parts",
"for",
"maintaining",
"sound",
"online",
"platforms.",
"This",
"paper",
"describes",
"our",
"participation",
"in",
"the",
"SemEval",
"2021",
"toxic",
"span",
"detection",
"task.",
"The",
"task",
"requires",
"detecting",
"spans",
"that",
"convey",
"toxic",
"remarks",
"from",
"the",
"given",
"text.",
"We",
"explore",
"an",
"ensemble",
"of",
"sequence",
"labeling",
"models",
"including",
"the",
"BiLSTM-CRF,",
"spaCy",
"NER",
"model",
"with",
"custom",
"toxic",
"tags,",
"and",
"fine-tuned",
"BERT",
"model",
"to",
"identify",
"the",
"toxic",
"spans.",
"Finally,",
"a",
"majority",
"voting",
"ensemble",
"method",
"is",
"used",
"to",
"determine",
"the",
"unified",
"toxic",
"spans.",
"Experimental",
"results",
"depict",
"the",
"competitive",
"performance",
"of",
"our",
"model",
"among",
"the",
"participants."
] |
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[
"Recently,",
"semi-supervised",
"learning",
"(SSL)",
"methods,",
"in",
"the",
"framework",
"of",
"deep",
"learning",
"(DL),",
"have",
"been",
"shown",
"to",
"provide",
"state-of-the-art",
"results",
"on",
"image",
"datasets",
"by",
"exploiting",
"unlabeled",
"data.",
"Most",
"of",
"the",
"time",
"tested",
"on",
"object",
"recognition",
"tasks",
"in",
"images,",
"these",
"algorithms",
"are",
"rarely",
"compared",
"when",
"applied",
"to",
"audio",
"tasks.",
"In",
"this",
"article,",
"we",
"adapted",
"four",
"recent",
"SSL",
"methods",
"to",
"the",
"task",
"of",
"audio",
"tagging.",
"The",
"first",
"two",
"methods,",
"namely",
"Deep",
"Co-Training",
"(DCT)",
"and",
"Mean",
"Teacher",
"(MT)",
"involve",
"two",
"collaborative",
"neural",
"networks.",
"The",
"two",
"other",
"algorithms,",
"called",
"MixMatch",
"(MM)",
"and",
"FixMatch",
"(FM),",
"are",
"single-model",
"methods",
"that",
"rely",
"primarily",
"on",
"data",
"augmentation",
"strategies.",
"Using",
"the",
"Wide",
"ResNet",
"28-Feb",
"architecture",
"in",
"all",
"our",
"experiments,",
"10%",
"of",
"labeled",
"data",
"and",
"the",
"remaining",
"90\\%",
"as",
"unlabeled,",
"we",
"first",
"compare",
"the",
"four",
"methods'",
"accuracy",
"on",
"three",
"standard",
"benchmark",
"audio",
"event",
"datasets:",
"Environmental",
"Sound",
"Classification",
"(ESC-10),",
"UrbanSound8K",
"(UBS8K),",
"and",
"Google",
"Speech",
"Commands",
"(GSC).",
"MM",
"and",
"FM",
"outperformed",
"MT",
"and",
"DCT",
"significantly,",
"MM",
"being",
"the",
"best",
"method",
"in",
"most",
"experiments.",
"On",
"UBS8K",
"and",
"GSC,",
"in",
"particular,",
"MM",
"achieved",
"18.02%",
"and",
"3.25%",
"error",
"rates",
"(ER),",
"outperforming",
"models",
"trained",
"with",
"100%",
"of",
"the",
"available",
"labeled",
"data,",
"which",
"reached",
"23.29%",
"and",
"4.94%",
"ER,",
"respectively.",
"Second,",
"we",
"explored",
"the",
"benefits",
"of",
"using",
"the",
"mixup",
"augmentation",
"in",
"the",
"four",
"algorithms.",
"In",
"almost",
"all",
"cases,",
"mixup",
"brought",
"significant",
"gains.",
"For",
"instance,",
"on",
"GSC,",
"FM",
"reached",
"4.44%",
"and",
"3.31%",
"ER",
"without",
"and",
"with",
"mixup."
] |
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"Performing",
"high",
"level",
"cognitive",
"tasks",
"requires",
"the",
"integration",
"of",
"featuremaps",
"with",
"drastically",
"different",
"structure.",
"In",
"Visual",
"Question",
"Answering",
"(VQA)image",
"descriptors",
"have",
"spatial",
"structures,",
"while",
"lexical",
"inputs",
"inherentlyfollow",
"a",
"temporal",
"sequence.",
"The",
"recently",
"proposed",
"Multimodal",
"Compact",
"Bilinearpooling",
"(MCB)",
"forms",
"the",
"outer",
"products,",
"via",
"count-sketch",
"approximation,",
"of",
"thevisual",
"and",
"textual",
"representation",
"at",
"each",
"spatial",
"location.",
"While",
"thisprocedure",
"preserves",
"spatial",
"information",
"locally,",
"outer-products",
"are",
"takenindependently",
"for",
"each",
"fiber",
"of",
"the",
"activation",
"tensor,",
"and",
"therefore",
"do",
"notinclude",
"spatial",
"context.",
"In",
"this",
"work,",
"we",
"introduce",
"multi-dimensional",
"sketch({MD-sketch}),",
"a",
"novel",
"extension",
"of",
"count-sketch",
"to",
"tensors.",
"Using",
"this",
"newformulation,",
"we",
"propose",
"Multimodal",
"Compact",
"Tensor",
"Pooling",
"(MCT)",
"to",
"fullyexploit",
"the",
"global",
"spatial",
"context",
"during",
"bilinear",
"pooling",
"operations.Contrarily",
"to",
"MCB,",
"our",
"approach",
"preserves",
"spatial",
"context",
"by",
"directlyconvolving",
"the",
"MD-sketch",
"from",
"the",
"visual",
"tensor",
"features",
"with",
"the",
"text",
"vectorfeature",
"using",
"higher",
"order",
"FFT.",
"Furthermore",
"we",
"apply",
"MCT",
"incrementally",
"at",
"eachstep",
"of",
"the",
"question",
"embedding",
"and",
"accumulate",
"the",
"multi-modal",
"vectors",
"with",
"asecond",
"LSTM",
"layer",
"before",
"the",
"final",
"answer",
"is",
"chosen."
] |
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[
"A",
"new",
"technique",
"is",
"introduced",
",",
"linguistic",
"profiling",
",",
"in",
"which",
"large",
"numbers",
"of",
"counts",
"of",
"linguistic",
"features",
"are",
"used",
"as",
"a",
"text",
"profile",
",",
"which",
"can",
"then",
"be",
"compared",
"to",
"average",
"profiles",
"for",
"groups",
"of",
"texts",
".",
"The",
"technique",
"proves",
"to",
"be",
"quite",
"effective",
"for",
"authorship",
"verification",
"and",
"recognition",
".",
"The",
"best",
"parameter",
"settings",
"yield",
"a",
"FALSE",
"Accept",
"Rate",
"of",
"8.1",
"%",
"at",
"a",
"FALSE",
"Reject",
"Rate",
"equal",
"to",
"zero",
"for",
"the",
"verification",
"task",
"on",
"a",
"test",
"corpus",
"of",
"student",
"essays",
",",
"and",
"a",
"99.4",
"%",
"2-way",
"recognition",
"accuracy",
"on",
"the",
"same",
"corpus",
"."
] |
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[
"Different",
"from",
"short",
"videos",
"and",
"GIFs,",
"video",
"stories",
"contain",
"clear",
"plots",
"and",
"lists",
"of",
"principal",
"characters.",
"Without",
"identifying",
"the",
"connection",
"between",
"appearing",
"people",
"and",
"character",
"names,",
"a",
"model",
"is",
"not",
"able",
"to",
"obtain",
"a",
"genuine",
"understanding",
"of",
"the",
"plots.",
"Video",
"Story",
"Question",
"Answering",
"(VSQA)",
"offers",
"an",
"effective",
"way",
"to",
"benchmark",
"higher-level",
"comprehension",
"abilities",
"of",
"a",
"model.",
"However,",
"current",
"VSQA",
"methods",
"merely",
"extract",
"generic",
"visual",
"features",
"from",
"a",
"scene.",
"With",
"such",
"an",
"approach,",
"they",
"remain",
"prone",
"to",
"learning",
"just",
"superficial",
"correlations.",
"In",
"order",
"to",
"attain",
"a",
"genuine",
"understanding",
"of",
"who",
"did",
"what",
"to",
"whom,",
"we",
"propose",
"a",
"novel",
"model",
"that",
"continuously",
"refines",
"character-aware",
"relations.",
"This",
"model",
"specifically",
"considers",
"the",
"characters",
"in",
"a",
"video",
"story,",
"as",
"well",
"as",
"the",
"relations",
"connecting",
"different",
"characters",
"and",
"objects.",
"Based",
"on",
"these",
"signals,",
"our",
"framework",
"enables",
"weakly-supervised",
"face",
"naming",
"through",
"multi-instance",
"co-occurrence",
"matching",
"and",
"supports",
"high-level",
"reasoning",
"utilizing",
"Transformer",
"structures.",
"We",
"train",
"and",
"test",
"our",
"model",
"on",
"the",
"six",
"diverse",
"TV",
"shows",
"in",
"the",
"TVQA",
"dataset,",
"which",
"is",
"by",
"far",
"the",
"largest",
"and",
"only",
"publicly",
"available",
"dataset",
"for",
"VSQA.",
"We",
"validate",
"our",
"proposed",
"approach",
"over",
"TVQA",
"dataset",
"through",
"extensive",
"ablation",
"study."
] |
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[
"Recent",
"work",
"(e.g.",
"LAMA",
"(Petroni",
"et",
"al.,",
"2019))",
"has",
"found",
"that",
"the",
"quality",
"of",
"the",
"factual",
"information",
"extracted",
"from",
"Large",
"Language",
"Models",
"(LLMs)",
"depends",
"on",
"the",
"prompts",
"used",
"to",
"query",
"them.",
"This",
"inconsistency",
"is",
"problematic",
"because",
"different",
"users",
"will",
"query",
"LLMs",
"for",
"the",
"same",
"information",
"using",
"different",
"wording,",
"but",
"should",
"receive",
"the",
"same,",
"accurate",
"responses",
"regardless.",
"In",
"this",
"work",
"we",
"aim",
"to",
"address",
"this",
"shortcoming",
"by",
"introducing",
"P-Adapters:",
"lightweight",
"models",
"that",
"sit",
"between",
"the",
"embedding",
"layer",
"and",
"first",
"attention",
"layer",
"of",
"LLMs.",
"They",
"take",
"LLM",
"embeddings",
"as",
"input",
"and",
"output",
"continuous",
"prompts",
"that",
"are",
"used",
"to",
"query",
"the",
"LLM.",
"Additionally,",
"we",
"investigate",
"Mixture",
"of",
"Experts",
"(MoE)",
"models",
"that",
"learn",
"a",
"set",
"of",
"continuous",
"prompts",
"(\"experts\")",
"and",
"select",
"one",
"to",
"query",
"the",
"LLM.",
"They",
"require",
"a",
"separate",
"classifier",
"trained",
"on",
"human-annotated",
"data",
"to",
"map",
"natural",
"language",
"prompts",
"to",
"the",
"continuous",
"ones.",
"P-Adapters",
"perform",
"comparably",
"to",
"the",
"more",
"complex",
"MoE",
"models",
"in",
"extracting",
"factual",
"information",
"from",
"BERT",
"and",
"RoBERTa",
"while",
"eliminating",
"the",
"need",
"for",
"additional",
"annotations.",
"P-Adapters",
"show",
"between",
"12-26%",
"absolute",
"improvement",
"in",
"precision",
"and",
"36-50%",
"absolute",
"improvement",
"in",
"consistency",
"over",
"a",
"baseline",
"of",
"only",
"using",
"natural",
"language",
"queries.",
"Finally,",
"we",
"investigate",
"what",
"makes",
"a",
"P-adapter",
"successful",
"and",
"conclude",
"that",
"access",
"to",
"the",
"LLM's",
"embeddings",
"of",
"the",
"original",
"natural",
"language",
"prompt,",
"particularly",
"the",
"subject",
"of",
"the",
"entity",
"pair",
"being",
"asked",
"about,",
"is",
"a",
"significant",
"factor."
] |
[
6,
6,
6,
8,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
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6,
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6,
6,
6,
6,
6,
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6,
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6,
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6,
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6,
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6,
6,
6,
6,
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6,
6,
6,
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6,
6,
6,
6,
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6,
6,
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6,
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6,
6,
6,
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6,
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6,
6,
6,
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6,
6,
6,
6,
6,
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6,
6,
6,
6,
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6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
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6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
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6,
6,
6,
6,
6,
6,
6,
6
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[
"Knowledge",
"Graphs",
"(KGs)",
"are",
"ubiquitous",
"structures",
"for",
"information",
"storagein",
"several",
"real-world",
"applications",
"such",
"as",
"web",
"search,",
"e-commerce,",
"social",
"networks,",
"and",
"biology.",
"Querying",
"KGs",
"remains",
"a",
"foundational",
"and",
"challenging",
"problem",
"due",
"to",
"their",
"size",
"and",
"complexity.",
"Promising",
"approaches",
"to",
"tackle",
"this",
"problem",
"include",
"embedding",
"the",
"KG",
"units",
"(e.g.,",
"entities",
"and",
"relations)",
"in",
"a",
"Euclidean",
"space",
"such",
"that",
"the",
"query",
"embedding",
"contains",
"the",
"information",
"relevant",
"to",
"its",
"results.",
"These",
"approaches,",
"however,",
"fail",
"to",
"capture",
"the",
"hierarchical",
"nature",
"and",
"semantic",
"information",
"of",
"the",
"entities",
"present",
"in",
"the",
"graph.",
"Additionally,",
"most",
"of",
"these",
"approaches",
"only",
"utilize",
"multi-hop",
"queries",
"(that",
"can",
"be",
"modeled",
"by",
"simple",
"translation",
"operations)",
"to",
"learn",
"embeddings",
"and",
"ignore",
"more",
"complex",
"operations",
"such",
"as",
"intersection",
"and",
"union",
"of",
"simpler",
"queries.",
"To",
"tackle",
"such",
"complex",
"operations,",
"in",
"this",
"paper,",
"we",
"formulate",
"KG",
"representation",
"learning",
"as",
"a",
"self-supervised",
"logical",
"query",
"reasoning",
"problem",
"that",
"utilizes",
"translation,",
"intersection",
"and",
"union",
"queries",
"over",
"KGs.",
"We",
"propose",
"Hyperboloid",
"Embeddings",
"(HypE",
"),",
"a",
"novel",
"self-supervised",
"dynamic",
"reasoning",
"framework,",
"that",
"utilizes",
"positive",
"first-order",
"existential",
"queries",
"on",
"a",
"KG",
"to",
"learn",
"representations",
"of",
"its",
"entities",
"and",
"relations",
"as",
"hyperboloids",
"in",
"a",
"Poincar\\'e",
"ball.",
"HypE",
"models",
"the",
"positive",
"first-order",
"queries",
"as",
"geometrical",
"translation,",
"intersection,",
"and",
"union.",
"For",
"the",
"problem",
"of",
"KG",
"reasoning",
"in",
"real-world",
"datasets,",
"the",
"proposed",
"HypE",
"model",
"significantly",
"outperforms",
"the",
"state-of-the",
"art",
"results.",
"We",
"also",
"apply",
"HypE",
"to",
"an",
"anomaly",
"detection",
"task",
"on",
"a",
"popular",
"e-commerce",
"website",
"product",
"taxonomy",
"as",
"well",
"as",
"hierarchically",
"organized",
"web",
"articles",
"and",
"demonstrate",
"significant",
"performance",
"improvements",
"compared",
"to",
"existing",
"baseline",
"methods.",
"Finally,",
"we",
"also",
"visualize",
"the",
"learned",
"HypE",
"embeddings",
"in",
"a",
"Poincar\\'e",
"ball",
"to",
"clearly",
"interpret",
"and",
"comprehend",
"the",
"representation",
"space."
] |
[
1,
3,
6,
6,
6,
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6,
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6,
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6,
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6,
6,
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6,
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6,
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6,
6,
6,
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6,
6,
6,
6,
6,
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6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6
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[
"We",
"customize",
"an",
"end-to-end",
"image",
"compression",
"framework",
"for",
"retina",
"OCT",
"images",
"based",
"on",
"deep",
"convolutional",
"neural",
"networks",
"(CNNs).",
"The",
"customized",
"compression",
"scheme",
"consists",
"of",
"three",
"parts:",
"data",
"Preprocessing,",
"compression",
"CNNs,",
"and",
"reconstruction",
"CNNs.",
"Data",
"preprocessing",
"module",
"reduces",
"the",
"speckle",
"noise",
"of",
"the",
"OCT",
"images",
"and",
"the",
"segments",
"out",
"the",
"region",
"of",
"interest.",
"We",
"added",
"customized",
"skip",
"connections",
"between",
"the",
"compression",
"CNNs",
"and",
"the",
"reconstruction",
"CNNs",
"to",
"reserve",
"the",
"detail",
"information",
"and",
"trained",
"the",
"two",
"nets",
"together",
"with",
"the",
"semantic",
"segmented",
"image",
"patches",
"from",
"data",
"preprocessing",
"module.",
"To",
"train",
"the",
"two",
"networks",
"sensitive",
"to",
"both",
"low",
"frequency",
"information",
"and",
"high",
"frequency",
"information,",
"we",
"adopted",
"an",
"objective",
"function",
"with",
"two",
"parts:",
"A",
"PatchGAN",
"discriminator",
"to",
"judge",
"the",
"high",
"frequency",
"information",
"and",
"a",
"differentiable",
"MS-SSIM",
"penalty",
"to",
"evaluate",
"the",
"low",
"frequency",
"information.",
"The",
"proposed",
"framework",
"was",
"trained",
"and",
"evaluated",
"on",
"a",
"publicly",
"available",
"OCT",
"dataset.",
"The",
"evaluation",
"showed",
"above",
"99%",
"similarity",
"in",
"terms",
"of",
"multi-scale",
"structural",
"similarity",
"(MS-SSIM",
")",
"when",
"the",
"compression",
"ratio",
"is",
"as",
"high",
"as",
"40",
"Furthermore,",
"the",
"reconstructed",
"images",
"of",
"compression",
"ratio",
"80",
"from",
"the",
"proposed",
"framework",
"even",
"have",
"better",
"quality",
"than",
"that",
"of",
"compression",
"ratio",
"20",
"from",
"JPEG",
"by",
"visual",
"comparison.",
"The",
"testing",
"result",
"outperforms",
"JPEG",
"in",
"term",
"of",
"both",
"of",
"MS-SSIM",
"and",
"visualization,",
"which",
"is",
"more",
"obvious",
"as",
"the",
"increase",
"of",
"compression",
"ratio.",
"Our",
"preliminary",
"result",
"indicates",
"the",
"huge",
"potential",
"of",
"deep",
"neural",
"networks",
"on",
"customized",
"medical",
"image",
"compression."
] |
[
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6,
6,
6,
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6,
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8,
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6,
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6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
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6,
6,
6,
6,
6,
6,
8,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
8,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6
] |
[
"Informed",
"source",
"separation",
"has",
"recently",
"gained",
"renewed",
"interest",
"with",
"the",
"introduction",
"of",
"neural",
"networks",
"and",
"the",
"availability",
"of",
"large",
"multitrack",
"datasets",
"containing",
"both",
"the",
"mixture",
"and",
"the",
"separated",
"sources.",
"These",
"approaches",
"use",
"prior",
"information",
"about",
"the",
"target",
"source",
"to",
"improve",
"separation.",
"Historically,",
"Music",
"Information",
"Retrieval",
"researchers",
"have",
"focused",
"primarily",
"on",
"score-informed",
"source",
"separation,",
"but",
"more",
"recent",
"approaches",
"explore",
"lyrics-informed",
"source",
"separation.",
"However,",
"because",
"of",
"the",
"lack",
"of",
"multitrack",
"datasets",
"with",
"time-aligned",
"lyrics,",
"models",
"use",
"weak",
"conditioning",
"with",
"non-aligned",
"lyrics.",
"In",
"this",
"paper,",
"we",
"present",
"a",
"multimodal",
"multitrack",
"dataset",
"with",
"lyrics",
"aligned",
"in",
"time",
"at",
"the",
"word",
"level",
"with",
"phonetic",
"information",
"as",
"well",
"as",
"explore",
"strong",
"conditioning",
"using",
"the",
"aligned",
"phonemes.",
"Our",
"model",
"follows",
"a",
"U-Net",
"architecture",
"and",
"takes",
"as",
"input",
"both",
"the",
"magnitude",
"spectrogram",
"of",
"a",
"musical",
"mixture",
"and",
"a",
"matrix",
"with",
"aligned",
"phonetic",
"information.",
"The",
"phoneme",
"matrix",
"is",
"embedded",
"to",
"obtain",
"the",
"parameters",
"that",
"control",
"Feature-wise",
"Linear",
"Modulation",
"(FiLM)",
"layers.",
"These",
"layers",
"condition",
"the",
"U-Net",
"feature",
"maps",
"to",
"adapt",
"the",
"separation",
"process",
"to",
"the",
"presence",
"of",
"different",
"phonemes",
"via",
"affine",
"transformations.",
"We",
"show",
"that",
"phoneme",
"conditioning",
"can",
"be",
"successfully",
"applied",
"to",
"improve",
"singing",
"voice",
"source",
"separation."
] |
[
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6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
1,
5,
3,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
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6,
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6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
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6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6
] |
[
"This",
"paper",
"presents",
"the",
"details",
"of",
"the",
"Audio-Visual",
"Scene",
"Classification",
"task",
"in",
"the",
"DCASE",
"2021",
"Challenge",
"(Task",
"1",
"Subtask",
"B).",
"The",
"task",
"is",
"concerned",
"with",
"classification",
"using",
"audio",
"and",
"video",
"modalities,",
"using",
"a",
"dataset",
"of",
"synchronized",
"recordings.",
"This",
"task",
"has",
"attracted",
"43",
"submissions",
"from",
"13",
"different",
"teams",
"around",
"the",
"world.",
"Among",
"all",
"submissions,",
"more",
"than",
"half",
"of",
"the",
"submitted",
"systems",
"have",
"better",
"performance",
"than",
"the",
"baseline.",
"The",
"common",
"techniques",
"among",
"the",
"top",
"systems",
"are",
"the",
"usage",
"of",
"large",
"pretrained",
"models",
"such",
"as",
"ResNet",
"or",
"EfficientNet",
"which",
"are",
"trained",
"for",
"the",
"task-specific",
"problem.",
"Fine-tuning,",
"transfer",
"learning,",
"and",
"data",
"augmentation",
"techniques",
"are",
"also",
"employed",
"to",
"boost",
"the",
"performance.",
"More",
"importantly,",
"multi-modal",
"methods",
"using",
"both",
"audio",
"and",
"video",
"are",
"employed",
"by",
"all",
"the",
"top",
"5",
"teams.",
"The",
"best",
"system",
"among",
"all",
"achieved",
"a",
"logloss",
"of",
"0.195",
"and",
"accuracy",
"of",
"93.8%,",
"compared",
"to",
"the",
"baseline",
"system",
"with",
"logloss",
"of",
"0.662",
"and",
"accuracy",
"of",
"77.1%."
] |
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[
"Classical",
"approaches",
"for",
"one-class",
"problems",
"such",
"as",
"one-class",
"SVM",
"and",
"isolation",
"forest",
"require",
"careful",
"feature",
"engineering",
"when",
"applied",
"to",
"structured",
"domains",
"like",
"images.",
"State-of-the-art",
"methods",
"aim",
"to",
"leverage",
"deep",
"learning",
"to",
"learn",
"appropriate",
"features",
"via",
"two",
"main",
"approaches.",
"The",
"first",
"approach",
"based",
"on",
"predicting",
"transformations",
"(Golan",
"&",
"El-Yaniv,",
"2018;",
"Hendrycks",
"et",
"al.,",
"2019a)",
"while",
"successful",
"in",
"some",
"domains,",
"crucially",
"depends",
"on",
"an",
"appropriate",
"domain-specific",
"set",
"of",
"transformations",
"that",
"are",
"hard",
"to",
"obtain",
"in",
"general.",
"The",
"second",
"approach",
"of",
"minimizing",
"a",
"classical",
"one-class",
"loss",
"on",
"the",
"learned",
"final",
"layer",
"representations,",
"e.g.,",
"DeepSVDD",
"(Ruff",
"et",
"al.,",
"2018)",
"suffers",
"from",
"the",
"fundamental",
"drawback",
"of",
"representation",
"collapse.",
"In",
"this",
"work,",
"we",
"propose",
"Deep",
"Robust",
"One-Class",
"Classification",
"(DROCC)",
"that",
"is",
"both",
"applicable",
"to",
"most",
"standard",
"domains",
"without",
"requiring",
"any",
"side-information",
"and",
"robust",
"to",
"representation",
"collapse.",
"DROCC",
"is",
"based",
"on",
"the",
"assumption",
"that",
"the",
"points",
"from",
"the",
"class",
"of",
"interest",
"lie",
"on",
"a",
"well-sampled,",
"locally",
"linear",
"low",
"dimensional",
"manifold.",
"Empirical",
"evaluation",
"demonstrates",
"that",
"DROCC",
"is",
"highly",
"effective",
"in",
"two",
"different",
"one-class",
"problem",
"settings",
"and",
"on",
"a",
"range",
"of",
"real-world",
"datasets",
"across",
"different",
"domains:",
"tabular",
"data,",
"images",
"(CIFAR",
"and",
"ImageNet),",
"audio,",
"and",
"time-series,",
"offering",
"up",
"to",
"20%",
"increase",
"in",
"accuracy",
"over",
"the",
"state-of-the-art",
"in",
"anomaly",
"detection.",
"Code",
"is",
"available",
"at",
"https://github.com/microsoft/EdgeML."
] |
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[
"Aspect-Based",
"Sentiment",
"Analysis",
"(ABSA)",
"deals",
"with",
"the",
"extraction",
"of",
"sentiments",
"and",
"their",
"targets.",
"Collecting",
"labeled",
"data",
"for",
"this",
"task",
"in",
"order",
"to",
"help",
"neural",
"networks",
"generalize",
"better",
"can",
"be",
"laborious",
"and",
"time-consuming.",
"As",
"an",
"alternative,",
"similar",
"data",
"to",
"the",
"real-world",
"examples",
"can",
"be",
"produced",
"artificially",
"through",
"an",
"adversarial",
"process",
"which",
"is",
"carried",
"out",
"in",
"the",
"embedding",
"space.",
"Although",
"these",
"examples",
"are",
"not",
"real",
"sentences,",
"they",
"have",
"been",
"shown",
"to",
"act",
"as",
"a",
"regularization",
"method",
"which",
"can",
"make",
"neural",
"networks",
"more",
"robust.",
"In",
"this",
"work,",
"we",
"apply",
"adversarial",
"training,",
"which",
"was",
"put",
"forward",
"by",
"Goodfellow",
"et",
"al.",
"(2014),",
"to",
"the",
"post-trained",
"BERT",
"(BERT",
"-PT)",
"language",
"model",
"proposed",
"by",
"Xu",
"et",
"al.",
"-2019",
"on",
"the",
"two",
"major",
"tasks",
"of",
"Aspect",
"Extraction",
"and",
"Aspect",
"Sentiment",
"Classification",
"in",
"sentiment",
"analysis.",
"After",
"improving",
"the",
"results",
"of",
"post-trained",
"BERT",
"by",
"an",
"ablation",
"study,",
"we",
"propose",
"a",
"novel",
"architecture",
"called",
"BERT",
"Adversarial",
"Training",
"(BAT)",
"to",
"utilize",
"adversarial",
"training",
"in",
"ABSA.",
"The",
"proposed",
"model",
"outperforms",
"post-trained",
"BERT",
"in",
"both",
"tasks.",
"To",
"the",
"best",
"of",
"our",
"knowledge,",
"this",
"is",
"the",
"first",
"study",
"on",
"the",
"application",
"of",
"adversarial",
"training",
"in",
"ABSA."
] |
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[
"This",
"work",
"presents",
"an",
"efficient",
"yet",
"effective",
"online",
"Knowledge",
"Distillation",
"method",
"via",
"Collaborative",
"Learning,",
"termed",
"KDCL,",
"which",
"is",
"able",
"to",
"consistently",
"improve",
"the",
"generalization",
"ability",
"of",
"deep",
"neural",
"networks",
"(DNNs)",
"that",
"have",
"different",
"learning",
"capacities.",
"Unlike",
"existing",
"two-stage",
"knowledge",
"distillation",
"approaches",
"that",
"pre-train",
"a",
"DNN",
"with",
"large",
"capacity",
"as",
"the",
"teacher",
"and",
"then",
"transfer",
"the",
"teacher's",
"knowledge",
"to",
"another",
"student",
"DNN",
"unidirectionally",
"(i.e.",
"one-way),",
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"treats",
"all",
"DNNs",
"as",
"students",
"and",
"collaboratively",
"trains",
"them",
"in",
"a",
"single",
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"(knowledge",
"is",
"transferred",
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"arbitrary",
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"during",
"collaborative",
"training),",
"enabling",
"parallel",
"computing,",
"fast",
"computations,",
"and",
"appealing",
"generalization",
"ability.",
"Specifically,",
"we",
"carefully",
"design",
"multiple",
"methods",
"to",
"generate",
"soft",
"target",
"as",
"supervisions",
"by",
"effectively",
"ensembling",
"predictions",
"of",
"students",
"and",
"distorting",
"the",
"input",
"images.",
"Extensive",
"experiments",
"show",
"that",
"KDCL",
"consistently",
"improves",
"all",
"the",
"students",
"on",
"different",
"datasets,",
"including",
"CIFAR-100",
"and",
"ImageNet.",
"For",
"example,",
"when",
"trained",
"together",
"by",
"using",
"KDCL,",
"ResNet-50",
"and",
"MobileNetV2",
"achieve",
"78.20%",
"and",
"74.00%",
"top-1",
"accuracy",
"on",
"ImageNet,",
"outperforming",
"the",
"original",
"results",
"by",
"1.40%",
"and",
"2.00%",
"respectively.",
"We",
"also",
"verify",
"that",
"models",
"pre-trained",
"with",
"KDCL",
"transfer",
"well",
"to",
"object",
"detection",
"and",
"semantic",
"segmentation",
"on",
"MS",
"COCO",
"dataset.",
"For",
"instance,",
"the",
"FPN",
"detector",
"is",
"improved",
"by",
"0.90%",
"mAP."
] |
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[
"The",
"proliferation",
"of",
"healthcare",
"data",
"has",
"brought",
"the",
"opportunities",
"ofapplying",
"data-driven",
"approaches,",
"such",
"as",
"machine",
"learning",
"methods,",
"to",
"assistdiagnosis.",
"Recently,",
"many",
"deep",
"learning",
"methods",
"have",
"been",
"shown",
"with",
"impressivesuccesses",
"in",
"predicting",
"disease",
"status",
"with",
"raw",
"input",
"data.",
"However,",
"the\"black-box\"",
"nature",
"of",
"deep",
"learning",
"and",
"the",
"high-reliability",
"requirement",
"ofbiomedical",
"applications",
"have",
"created",
"new",
"challenges",
"regarding",
"the",
"existence",
"ofconfounding",
"factors.",
"In",
"this",
"paper,",
"with",
"a",
"brief",
"argument",
"that",
"inappropriatehandling",
"of",
"confounding",
"factors",
"will",
"lead",
"to",
"models'",
"sub-optimal",
"performance",
"inreal-world",
"applications,",
"we",
"present",
"an",
"efficient",
"method",
"that",
"can",
"remove",
"theinfluences",
"of",
"confounding",
"factors",
"such",
"as",
"age",
"or",
"gender",
"to",
"improve",
"theacross-cohort",
"prediction",
"accuracy",
"of",
"neural",
"networks.",
"One",
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"method",
"is",
"that",
"it",
"only",
"requires",
"minimal",
"changes",
"of",
"the",
"baseline",
"model'sarchitecture",
"so",
"that",
"it",
"can",
"be",
"plugged",
"into",
"most",
"of",
"the",
"existing",
"neuralnetworks.",
"We",
"conduct",
"experiments",
"across",
"CT-scan,",
"MRA,",
"and",
"EEG",
"brain",
"wave",
"withconvolutional",
"neural",
"networks",
"and",
"LSTM",
"to",
"verify",
"the",
"efficiency",
"of",
"our",
"method."
] |
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"studies",
"suggest",
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"machine",
"learning",
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"be",
"applied",
"to",
"develop",
"good",
"automatic",
"evaluation",
"metrics",
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"translated",
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".",
"This",
"paper",
"further",
"analyzes",
"aspects",
"of",
"learning",
"that",
"impact",
"performance",
".",
"We",
"argue",
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"proposed",
"approaches",
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"training",
"a",
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"as",
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"of",
"translation",
"quality",
",",
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"that",
"regression-based",
"learning",
"produces",
"more",
"reliable",
"metrics",
".",
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"demonstrate",
"the",
"feasibility",
"of",
"regression-based",
"metrics",
"through",
"empirical",
"analysis",
"of",
"learning",
"curves",
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"generalization",
"studies",
"and",
"show",
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"they",
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"standard",
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"Understanding",
"tasks.",
"In",
"this",
"paper,",
"we",
"demonstrate",
"the",
"efficacy",
"of",
"pre-trained",
"checkpoints",
"for",
"Sequence",
"Generation.",
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"a",
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"sequence-to-sequence",
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"utility",
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"initializing",
"our",
"model,",
"both",
"encoder",
"and",
"decoder,",
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"these",
"checkpoints.",
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"results",
"on",
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"Translation,",
"Text",
"Summarization,",
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"Splitting,",
"and",
"Sentence",
"Fusion."
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"real-world",
"applications.",
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"process",
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"datasets",
"containing",
"captioned",
"images,",
"meaning",
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"each",
"image",
"is",
"associated",
"with",
"one",
"(or",
"more)",
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"the",
"abundance",
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"uncaptioned",
"images",
"datasets,",
"the",
"number",
"of",
"captioned",
"datasets",
"is",
"limited.",
"To",
"address",
"this",
"issue,",
"in",
"this",
"paper",
"we",
"propose",
"an",
"approach",
"capable",
"of",
"generating",
"images",
"starting",
"from",
"a",
"given",
"text",
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"GAN",
"s",
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"uncaptioned",
"images",
"dataset.",
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"images",
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"results,",
"the",
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"the",
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"preliminary",
"but",
"still",
"promising."
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",",
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"size,",
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"Aspect-based",
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"mining",
"tasks",
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"systems.",
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"direction,",
"the",
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"modeling,",
"in",
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"often",
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"words,",
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"LDA",
"models.",
"Moreover,",
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"rely",
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"methods,",
"which",
"need",
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"load",
"the",
"whole",
"corpus",
"into",
"memory,",
"making",
"them",
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"for",
"AOS",
"problem,",
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"Inference",
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"model,",
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"JST",
"model,",
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"The",
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"show",
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"models",
"enjoy",
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"topic",
"coherent,",
"faster",
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"time",
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"better",
"accuracy",
"on",
"sentiment",
"classification,",
"as",
"compared",
"to",
"their",
"LDA",
"#NAME?",
"counterparts."
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"The",
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")",
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"controls",
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"Validity",
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"2",
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"investigated.",
"Convolutional",
"Neural",
"Networks",
"(CNN)",
"werefound",
"to",
"provide",
"much",
"better",
"performance",
"than",
"SVM",
"and",
"kNNs."
] |
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[
"Reverse",
"Engineering(RE)",
"has",
"been",
"a",
"fundamental",
"task",
"in",
"software",
"engineering.",
"However,",
"most",
"of",
"the",
"traditional",
"Java",
"reverse",
"engineering",
"tools",
"are",
"strictly",
"rule",
"defined,",
"thus",
"are",
"not",
"fault-tolerant,",
"which",
"pose",
"serious",
"problem",
"when",
"noise",
"and",
"interference",
"were",
"introduced",
"into",
"the",
"system.",
"In",
"this",
"paper,",
"we",
"view",
"reverse",
"engineering",
"as",
"a",
"statistical",
"machine",
"translation",
"task",
"instead",
"of",
"rule-based",
"task,",
"and",
"propose",
"a",
"fault-tolerant",
"Java",
"decompiler",
"based",
"on",
"machine",
"translation",
"models.",
"Our",
"model",
"is",
"based",
"on",
"attention-based",
"Neural",
"Machine",
"Translation",
"(NMT)",
"and",
"Transformer",
"architectures.",
"First,",
"we",
"measure",
"the",
"translation",
"quality",
"on",
"both",
"the",
"redundant",
"and",
"purified",
"datasets.",
"Next,",
"we",
"evaluate",
"the",
"fault-tolerance(anti-noise",
"ability)",
"of",
"our",
"framework",
"on",
"test",
"sets",
"with",
"different",
"unit",
"error",
"probability",
"(UEP).",
"In",
"addition,",
"we",
"compare",
"the",
"suitability",
"of",
"different",
"word",
"segmentation",
"algorithms",
"for",
"decompilation",
"task.",
"Experimental",
"results",
"demonstrate",
"that",
"our",
"model",
"is",
"more",
"robust",
"and",
"fault-tolerant",
"compared",
"to",
"traditional",
"Abstract",
"Syntax",
"Tree",
"(AST)",
"based",
"decompilers.",
"Specifically,",
"in",
"terms",
"of",
"BLEU-4",
"and",
"Word",
"Error",
"Rate",
"(WER),",
"our",
"performance",
"has",
"reached",
"94.50%",
"and",
"2.65%",
"on",
"the",
"redundant",
"test",
"set;",
"92.30%",
"and",
"3.48%",
"on",
"the",
"purified",
"test",
"set."
] |
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[
"This",
"paper",
"describes",
"the",
"system",
"for",
"the",
"Named",
"Entity",
"Recognition",
"Shared",
"Task",
"of",
"the",
"Third",
"Workshop",
"on",
"Computational",
"Approaches",
"to",
"Linguistic",
"Code-Switching",
"(CALCS)",
"submitted",
"by",
"the",
"Bilingual",
"Annotations",
"Tasks",
"(BATs)",
"research",
"group",
"of",
"the",
"University",
"of",
"Texas.",
"Our",
"system",
"uses",
"several",
"features",
"to",
"train",
"a",
"Conditional",
"Random",
"Field",
"(CRF",
")",
"model",
"for",
"classifying",
"input",
"words",
"as",
"Named",
"Entities",
"(NEs)",
"using",
"the",
"Inside-Outside-Beginning",
"(IOB)",
"tagging",
"scheme.",
"We",
"participated",
"in",
"the",
"Modern",
"Standard",
"Arabic-Egyptian",
"Arabic",
"(MSA-EGY)",
"and",
"English-Spanish",
"(ENG-SPA)",
"tasks,",
"achieving",
"weighted",
"average",
"F-scores",
"of",
"65.62",
"and",
"54.16",
"respectively.",
"We",
"also",
"describe",
"the",
"performance",
"of",
"a",
"deep",
"neural",
"network",
"(NN)",
"trained",
"on",
"a",
"subset",
"of",
"the",
"CRF",
"features,",
"which",
"did",
"not",
"surpass",
"CRF",
"performance."
] |
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[
"The",
"success",
"of",
"pre-trained",
"word",
"embeddings",
"has",
"motivated",
"its",
"use",
"in",
"tasks",
"in",
"the",
"biomedical",
"domain.",
"The",
"BERT",
"language",
"model",
"has",
"shown",
"remarkable",
"results",
"on",
"standard",
"performance",
"metrics",
"in",
"tasks",
"such",
"as",
"Named",
"Entity",
"Recognition",
"(NER",
")",
"and",
"Semantic",
"Textual",
"Similarity",
"(STS),",
"which",
"has",
"brought",
"significant",
"progress",
"in",
"the",
"field",
"of",
"NLP.",
"However,",
"it",
"is",
"unclear",
"whether",
"these",
"systems",
"work",
"seemingly",
"well",
"in",
"critical",
"domains,",
"such",
"as",
"legal",
"or",
"medical.",
"For",
"that",
"reason,",
"in",
"this",
"work,",
"we",
"propose",
"an",
"adversarial",
"evaluation",
"scheme",
"on",
"two",
"well-known",
"datasets",
"for",
"medical",
"NER",
"and",
"STS.",
"We",
"propose",
"two",
"types",
"of",
"attacks",
"inspired",
"by",
"natural",
"spelling",
"errors",
"and",
"typos",
"made",
"by",
"humans.",
"We",
"also",
"propose",
"another",
"type",
"of",
"attack",
"that",
"uses",
"synonyms",
"of",
"medical",
"terms.",
"Under",
"these",
"adversarial",
"settings,",
"the",
"accuracy",
"of",
"the",
"models",
"drops",
"significantly,",
"and",
"we",
"quantify",
"the",
"extent",
"of",
"this",
"performance",
"loss.",
"We",
"also",
"show",
"that",
"we",
"can",
"significantly",
"improve",
"the",
"robustness",
"of",
"the",
"models",
"by",
"training",
"them",
"with",
"adversarial",
"examples.",
"We",
"hope",
"our",
"work",
"will",
"motivate",
"the",
"use",
"of",
"adversarial",
"examples",
"to",
"evaluate",
"and",
"develop",
"models",
"with",
"increased",
"robustness",
"for",
"medical",
"tasks."
] |
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[
"To",
"effectively",
"perform",
"the",
"task",
"of",
"next-word",
"prediction,",
"long",
"short-term",
"memory",
"networks",
"(LSTM",
"s)",
"must",
"keep",
"track",
"of",
"many",
"types",
"of",
"information.",
"Some",
"information",
"is",
"directly",
"related",
"to",
"the",
"next",
"word's",
"identity,",
"but",
"some",
"is",
"more",
"secondary",
"(e.g.",
"discourse-level",
"features",
"or",
"features",
"of",
"downstream",
"words).",
"Correlates",
"of",
"secondary",
"information",
"appear",
"in",
"LSTM",
"representations",
"even",
"though",
"they",
"are",
"not",
"part",
"of",
"an",
"\\emph{explicitly}",
"supervised",
"prediction",
"task.",
"In",
"contrast,",
"in",
"reinforcement",
"learning",
"(RL),",
"techniques",
"that",
"explicitly",
"supervise",
"representations",
"to",
"predict",
"secondary",
"information",
"have",
"been",
"shown",
"to",
"be",
"beneficial.",
"Inspired",
"by",
"that",
"success,",
"we",
"propose",
"Predictive",
"Representation",
"Learning",
"(PRL),",
"which",
"explicitly",
"constrains",
"LSTM",
"s",
"to",
"encode",
"specific",
"predictions,",
"like",
"those",
"that",
"might",
"need",
"to",
"be",
"learned",
"implicitly.",
"We",
"show",
"that",
"PRL",
"1)",
"significantly",
"improves",
"two",
"strong",
"language",
"modeling",
"methods,",
"2)",
"converges",
"more",
"quickly,",
"and",
"3)",
"performs",
"better",
"when",
"data",
"is",
"limited.",
"Our",
"work",
"shows",
"that",
"explicitly",
"encoding",
"a",
"simple",
"predictive",
"task",
"facilitates",
"the",
"search",
"for",
"a",
"more",
"effective",
"language",
"model."
] |
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[
"Recognizing",
"Textual",
"Entailment",
"(RTE)",
"is",
"a",
"fundamentally",
"important",
"task",
"in",
"natural",
"language",
"processing",
"that",
"has",
"many",
"applications.",
"The",
"recently",
"released",
"Stanford",
"Natural",
"Language",
"Inference",
"(SNLI)",
"corpus",
"has",
"made",
"it",
"possible",
"to",
"develop",
"and",
"evaluate",
"deep",
"neural",
"network",
"methods",
"for",
"the",
"RTE",
"task.",
"Previous",
"neural",
"network",
"based",
"methods",
"usually",
"try",
"to",
"encode",
"the",
"two",
"sentences",
"(premise",
"and",
"hypothesis)",
"and",
"send",
"them",
"together",
"into",
"a",
"multi-layer",
"perceptron",
"to",
"get",
"their",
"entailment",
"type,",
"or",
"use",
"LSTM",
"#NAME?",
"to",
"link",
"two",
"sentences",
"together",
"while",
"using",
"attention",
"mechanic",
"to",
"enhance",
"the",
"model{'}s",
"ability.",
"In",
"this",
"paper,",
"we",
"propose",
"to",
"use",
"the",
"re-read",
"mechanic,",
"which",
"means",
"to",
"read",
"the",
"premise",
"again",
"and",
"again",
"while",
"reading",
"the",
"hypothesis.",
"After",
"read",
"the",
"premise",
"again,",
"the",
"model",
"can",
"get",
"a",
"better",
"understanding",
"of",
"the",
"premise,",
"which",
"can",
"also",
"affect",
"the",
"understanding",
"of",
"the",
"hypothesis.",
"On",
"the",
"contrary,",
"a",
"better",
"understanding",
"of",
"the",
"hypothesis",
"can",
"also",
"affect",
"the",
"understanding",
"of",
"the",
"premise.",
"With",
"the",
"alternative",
"re-read",
"process,",
"the",
"model",
"can",
"{``}think{''}",
"of",
"a",
"better",
"decision",
"of",
"entailment",
"type.",
"We",
"designed",
"a",
"new",
"LSTM",
"unit",
"called",
"re-read",
"LSTM",
"(rLSTM",
")",
"to",
"implement",
"this",
"{``}thinking{''}",
"process.",
"Experiments",
"show",
"that",
"we",
"achieve",
"results",
"better",
"than",
"current",
"state-of-the-art",
"equivalents."
] |
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[
"In",
"this",
"paper",
"we",
"investigate",
"several",
"nonprojective",
"parsing",
"algorithms",
"for",
"dependency",
"parsing",
",",
"providing",
"novel",
"polynomial",
"time",
"solutions",
"under",
"the",
"assumption",
"that",
"each",
"dependency",
"decision",
"is",
"independent",
"of",
"all",
"the",
"others",
",",
"called",
"here",
"the",
"edge-factored",
"model",
".",
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"also",
"investigate",
"algorithms",
"for",
"non-projective",
"parsing",
"that",
"account",
"for",
"nonlocal",
"information",
",",
"and",
"present",
"several",
"hardness",
"results",
".",
"This",
"suggests",
"that",
"it",
"is",
"unlikely",
"that",
"exact",
"non-projective",
"dependency",
"parsing",
"is",
"tractable",
"for",
"any",
"model",
"richer",
"than",
"the",
"edge-factored",
"model",
"."
] |
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[
"Various",
"Seq2Seq",
"learning",
"models",
"designed",
"for",
"machine",
"translation",
"were",
"applied",
"for",
"abstractive",
"summarization",
"task",
"recently.",
"Despite",
"these",
"models",
"provide",
"high",
"ROUGE",
"scores,",
"they",
"are",
"limited",
"to",
"generate",
"comprehensive",
"summaries",
"with",
"a",
"high",
"level",
"of",
"abstraction",
"due",
"to",
"its",
"degenerated",
"attention",
"distribution.",
"We",
"introduce",
"Diverse",
"Convolutional",
"Seq2Seq",
"Model(DivCNN",
"Seq2Seq",
")",
"using",
"Determinantal",
"Point",
"Processes",
"methods(Micro",
"DPPs",
"and",
"Macro",
"DPPs)",
"to",
"produce",
"attention",
"distribution",
"considering",
"both",
"quality",
"and",
"diversity.",
"Without",
"breaking",
"the",
"end",
"to",
"end",
"architecture,",
"DivCNN",
"Seq2Seq",
"achieves",
"a",
"higher",
"level",
"of",
"comprehensiveness",
"compared",
"to",
"vanilla",
"models",
"and",
"strong",
"baselines.",
"All",
"the",
"reproducible",
"codes",
"and",
"datasets",
"are",
"available",
"online."
] |
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[
"Clinical",
"notes",
"often",
"describe",
"important",
"aspects",
"of",
"a",
"patient's",
"stay",
"and",
"aretherefore",
"critical",
"to",
"medical",
"research.",
"Clinical",
"concept",
"extraction",
"(CCE)",
"ofnamed",
"entities",
"-",
"such",
"as",
"problems,",
"tests,",
"and",
"treatments",
"-",
"aids",
"in",
"forming",
"anunderstanding",
"of",
"notes",
"and",
"provides",
"a",
"foundation",
"for",
"many",
"downstream",
"clinicaldecision-making",
"tasks.",
"Historically,",
"this",
"task",
"has",
"been",
"posed",
"as",
"a",
"standardnamed",
"entity",
"recognition",
"(NER",
")",
"sequence",
"tagging",
"problem,",
"and",
"solved",
"withfeature-based",
"methods",
"using",
"handengineered",
"domain",
"knowledge.",
"Recent",
"advances,however,",
"have",
"demonstrated",
"the",
"efficacy",
"of",
"LSTM",
"#NAME?",
"models",
"for",
"NER",
"tasks,including",
"CCE.",
"This",
"work",
"presents",
"CliNER",
"2.0,",
"a",
"simple-to-install,",
"open-sourcetool",
"for",
"extracting",
"concepts",
"from",
"clinical",
"text.",
"CliNER",
"2",
"uses",
"a",
"word-",
"andcharacter-",
"level",
"LSTM",
"model,",
"and",
"achieves",
"state-of-the-art",
"performance.",
"Forease",
"of",
"use,",
"the",
"tool",
"also",
"includes",
"pre-trained",
"models",
"available",
"for",
"publicuse."
] |
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[
"This",
"paper",
"describes",
"Unbabel's",
"submission",
"to",
"the",
"WMT2019",
"APE",
"Shared",
"Task",
"for",
"the",
"English-German",
"language",
"pair.",
"Following",
"the",
"recent",
"rise",
"of",
"large,",
"powerful,",
"pre-trained",
"models,",
"we",
"adapt",
"the",
"BERT",
"pretrained",
"model",
"to",
"perform",
"Automatic",
"Post-Editing",
"in",
"an",
"encoder-decoder",
"framework.",
"Analogously",
"to",
"dual-encoder",
"architectures",
"we",
"develop",
"a",
"BERT",
"#NAME?",
"encoder-decoder",
"(BED)",
"model",
"in",
"which",
"a",
"single",
"pretrained",
"BERT",
"encoder",
"receives",
"both",
"the",
"source",
"src",
"and",
"machine",
"translation",
"tgt",
"strings.",
"Furthermore,",
"we",
"explore",
"a",
"conservativeness",
"factor",
"to",
"constrain",
"the",
"APE",
"system",
"to",
"perform",
"fewer",
"edits.",
"As",
"the",
"official",
"results",
"show,",
"when",
"trained",
"on",
"a",
"weighted",
"combination",
"of",
"in-domain",
"and",
"artificial",
"training",
"data,",
"our",
"BED",
"system",
"with",
"the",
"conservativeness",
"penalty",
"improves",
"significantly",
"the",
"translations",
"of",
"a",
"strong",
"Neural",
"Machine",
"Translation",
"system",
"by",
"$-0.78$",
"and",
"$+1.23$",
"in",
"terms",
"of",
"TER",
"and",
"BLEU,",
"respectively.",
"Finally,",
"our",
"submission",
"achieves",
"a",
"new",
"state-of-the-art,",
"ex-aequo,",
"in",
"English-German",
"APE",
"of",
"NMT."
] |
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[
"Neural",
"Machine",
"Translation",
"(NMT)",
"for",
"low-resource",
"languages",
"suffers",
"from",
"low",
"performance",
"because",
"of",
"the",
"lack",
"of",
"large",
"amounts",
"of",
"parallel",
"data",
"and",
"language",
"diversity.",
"To",
"contribute",
"to",
"ameliorating",
"this",
"problem,",
"we",
"built",
"a",
"baseline",
"model",
"for",
"English{--}Hausa",
"machine",
"translation,",
"which",
"is",
"considered",
"a",
"task",
"for",
"low{--}resource",
"language.",
"The",
"Hausa",
"language",
"is",
"the",
"second",
"largest",
"Afro{--}Asiatic",
"language",
"in",
"the",
"world",
"after",
"Arabic",
"and",
"it",
"is",
"the",
"third",
"largest",
"language",
"for",
"trading",
"across",
"a",
"larger",
"swath",
"of",
"West",
"Africa",
"countries,",
"after",
"English",
"and",
"French.",
"In",
"this",
"paper,",
"we",
"curated",
"different",
"datasets",
"containing",
"Hausa{--}English",
"parallel",
"corpus",
"for",
"our",
"translation.",
"We",
"trained",
"baseline",
"models",
"and",
"evaluated",
"the",
"performance",
"of",
"our",
"models",
"using",
"the",
"Recurrent",
"and",
"Transformer",
"encoder{--}decoder",
"architecture",
"with",
"two",
"tokenization",
"approaches:",
"standard",
"word{--}level",
"tokenization",
"and",
"Byte",
"Pair",
"Encoding",
"(BPE)",
"subword",
"tokenization."
] |
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[
"Sarcasm",
"Detection",
"with",
"Context,",
"a",
"shared",
"task",
"of",
"Second",
"Workshop",
"on",
"Figurative",
"Language",
"Processing",
"(co-located",
"with",
"ACL",
"2020),",
"is",
"study",
"of",
"effect",
"of",
"context",
"on",
"Sarcasm",
"detection",
"in",
"conversations",
"of",
"Social",
"media.",
"We",
"present",
"different",
"techniques",
"and",
"models,",
"mostly",
"based",
"on",
"transformer",
"for",
"Sarcasm",
"Detection",
"with",
"Context.",
"We",
"extended",
"latest",
"pre-trained",
"transformers",
"like",
"BERT,",
"RoBERTa,",
"spanBERT",
"on",
"different",
"task",
"objectives",
"like",
"single",
"sentence",
"classification,",
"sentence",
"pair",
"classification,",
"etc.",
"to",
"understand",
"role",
"of",
"conversation",
"context",
"for",
"sarcasm",
"detection",
"on",
"Twitter",
"conversations",
"and",
"conversation",
"threads",
"from",
"Reddit.",
"We",
"also",
"present",
"our",
"own",
"architecture",
"consisting",
"of",
"LSTM",
"and",
"Transformers",
"to",
"achieve",
"the",
"objective."
] |
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[
"The",
"novel",
"corona-virus",
"disease",
"(COVID-19)",
"pandemic",
"has",
"caused",
"a",
"major",
"outbreak",
"in",
"more",
"than",
"200",
"countries",
"around",
"the",
"world,",
"leading",
"to",
"a",
"severe",
"impact",
"on",
"the",
"health",
"and",
"life",
"of",
"many",
"people",
"globally.",
"As",
"of",
"mid-July",
"2020,",
"more",
"than",
"12",
"million",
"people",
"were",
"infected,",
"and",
"more",
"than",
"570,000",
"death",
"were",
"reported.",
"Computed",
"Tomography",
"(CT)",
"images",
"can",
"be",
"used",
"as",
"an",
"alternative",
"to",
"the",
"time-consuming",
"RT-PCR",
"test,",
"to",
"detect",
"COVID-19.",
"In",
"this",
"work",
"we",
"propose",
"a",
"segmentation",
"framework",
"to",
"detect",
"chest",
"regions",
"in",
"CT",
"images,",
"which",
"are",
"infected",
"by",
"COVID-19.",
"We",
"use",
"an",
"architecture",
"similar",
"to",
"U-Net",
"model,",
"and",
"train",
"it",
"to",
"detect",
"ground",
"glass",
"regions,",
"on",
"pixel",
"level.",
"As",
"the",
"infected",
"regions",
"tend",
"to",
"form",
"a",
"connected",
"component",
"(rather",
"than",
"randomly",
"distributed",
"pixels),",
"we",
"add",
"a",
"suitable",
"regularization",
"term",
"to",
"the",
"loss",
"function,",
"to",
"promote",
"connectivity",
"of",
"the",
"segmentation",
"map",
"for",
"COVID-19",
"pixels.",
"2D-anisotropic",
"total-variation",
"is",
"used",
"for",
"this",
"purpose,",
"and",
"therefore",
"the",
"proposed",
"model",
"is",
"called",
"TV-UNet.",
"Through",
"experimental",
"results",
"on",
"a",
"relatively",
"large-scale",
"CT",
"segmentation",
"dataset",
"of",
"around",
"900",
"images,",
"we",
"show",
"that",
"adding",
"this",
"new",
"regularization",
"term",
"leads",
"to",
"2\\%",
"gain",
"on",
"overall",
"segmentation",
"performance",
"compared",
"to",
"the",
"U-Net",
"model.",
"Our",
"experimental",
"analysis,",
"ranging",
"from",
"visual",
"evaluation",
"of",
"the",
"predicted",
"segmentation",
"results",
"to",
"quantitative",
"assessment",
"of",
"segmentation",
"performance",
"(precision,",
"recall,",
"Dice",
"score,",
"and",
"mIoU)",
"demonstrated",
"great",
"ability",
"to",
"identify",
"COVID-19",
"associated",
"regions",
"of",
"the",
"lungs,",
"achieving",
"a",
"mIoU",
"rate",
"of",
"over",
"99\\%,",
"and",
"a",
"Dice",
"score",
"of",
"around",
"86\\%."
] |
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[
"Scalable",
"Data",
"Augmentation",
"(SDA)",
"provides",
"a",
"framework",
"for",
"training",
"deeplearning",
"models",
"using",
"auxiliary",
"hidden",
"layers.",
"Scalable",
"MCMC",
"is",
"available",
"fornetwork",
"training",
"and",
"inference.",
"SDA",
"provides",
"a",
"number",
"of",
"computationaladvantages",
"over",
"traditional",
"algorithms,",
"such",
"as",
"avoiding",
"backtracking,",
"localmodes",
"and",
"can",
"perform",
"optimization",
"with",
"stochastic",
"gradient",
"descent",
"(SGD)",
"inTensorFlow.",
"Standard",
"deep",
"neural",
"networks",
"with",
"logit,",
"ReLU",
"and",
"SVM",
"activationfunctions",
"are",
"straightforward",
"to",
"implement.",
"To",
"illustrate",
"our",
"architectures",
"andmethodology,",
"we",
"use",
"P\\'{o}lya-Gamma",
"logit",
"data",
"augmentation",
"for",
"a",
"number",
"ofstandard",
"datasets.",
"Finally,",
"we",
"conclude",
"with",
"directions",
"for",
"future",
"research."
] |
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[
"Recommendation",
"systems",
"have",
"an",
"important",
"place",
"to",
"help",
"online",
"users",
"in",
"theinternet",
"society.",
"Recommendation",
"Systems",
"in",
"computer",
"science",
"are",
"of",
"verypractical",
"use",
"these",
"days",
"in",
"various",
"aspects",
"of",
"the",
"Internet",
"portals,",
"such",
"associal",
"networks,",
"and",
"library",
"websites.",
"There",
"are",
"several",
"approaches",
"toimplement",
"recommendation",
"systems,",
"Latent",
"Dirichlet",
"Allocation",
"(LDA",
")",
"is",
"one",
"thepopular",
"techniques",
"in",
"Topic",
"Modeling.",
"Recently,",
"researchers",
"have",
"proposed",
"manyapproaches",
"based",
"on",
"Recommendation",
"Systems",
"and",
"LDA",
".",
"According",
"to",
"importance",
"ofthe",
"subject,",
"in",
"this",
"paper",
"we",
"discover",
"the",
"trends",
"of",
"the",
"topics",
"and",
"findrelationship",
"between",
"LDA",
"topics",
"and",
"Scholar-Context-documents.",
"In",
"fact,",
"Weapply",
"probabilistic",
"topic",
"modeling",
"based",
"on",
"Gibbs",
"sampling",
"algorithms",
"for",
"asemantic",
"mining",
"from",
"six",
"conference",
"publications",
"in",
"computer",
"science",
"from",
"DBLPdataset.",
"According",
"to",
"our",
"experimental",
"results,",
"our",
"semantic",
"framework",
"can",
"beeffective",
"to",
"help",
"organizations",
"to",
"better",
"organize",
"these",
"conferences",
"and",
"coverfuture",
"research",
"topics."
] |
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[
"With",
"the",
"growing",
"capabilities",
"of",
"autonomous",
"vehicles,",
"there",
"is",
"a",
"higher",
"demand",
"for",
"sophisticated",
"and",
"pragmatic",
"quality",
"assurance",
"approaches",
"for",
"machine",
"learning-enabled",
"systems",
"in",
"the",
"automotive",
"AI",
"context.",
"The",
"use",
"of",
"simulation-based",
"prototyping",
"platforms",
"provides",
"the",
"possibility",
"for",
"early-stage",
"testing,",
"enabling",
"inexpensive",
"testing",
"and",
"the",
"ability",
"to",
"capture",
"critical",
"corner-case",
"test",
"scenarios.",
"Simulation-based",
"testing",
"properly",
"complements",
"conventional",
"on-road",
"testing.",
"However,",
"due",
"to",
"the",
"large",
"space",
"of",
"test",
"input",
"parameters",
"in",
"these",
"systems,",
"the",
"efficient",
"generation",
"of",
"effective",
"test",
"scenarios",
"leading",
"to",
"the",
"unveiling",
"of",
"failures",
"is",
"a",
"challenge.",
"This",
"paper",
"presents",
"a",
"study",
"on",
"testing",
"pedestrian",
"detection",
"and",
"emergency",
"braking",
"system",
"of",
"the",
"Baidu",
"Apollo",
"autonomous",
"driving",
"platform",
"within",
"the",
"SVL",
"simulator.",
"We",
"propose",
"an",
"evolutionary",
"automated",
"test",
"generation",
"technique",
"that",
"generates",
"failure-revealing",
"scenarios",
"for",
"Apollo",
"in",
"the",
"SVL",
"environment.",
"Our",
"approach",
"models",
"the",
"input",
"space",
"using",
"a",
"generic",
"and",
"flexible",
"data",
"structure",
"and",
"benefits",
"a",
"multi-criteria",
"safety-based",
"heuristic",
"for",
"the",
"objective",
"function",
"targeted",
"for",
"optimization.",
"This",
"paper",
"presents",
"the",
"results",
"of",
"our",
"proposed",
"test",
"generation",
"technique",
"in",
"the",
"2021",
"IEEE",
"Autonomous",
"Driving",
"AI",
"Test",
"Challenge.",
"In",
"order",
"to",
"demonstrate",
"the",
"efficiency",
"and",
"effectiveness",
"of",
"our",
"approach,",
"we",
"also",
"report",
"the",
"results",
"from",
"a",
"baseline",
"random",
"generation",
"technique.",
"Our",
"evaluation",
"shows",
"that",
"the",
"proposed",
"evolutionary",
"test",
"case",
"generator",
"is",
"more",
"effective",
"at",
"generating",
"failure-revealing",
"test",
"cases",
"and",
"provides",
"higher",
"diversity",
"between",
"the",
"generated",
"failures",
"than",
"the",
"random",
"baseline."
] |
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6
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