tokens
list | ner_tags
list |
|---|---|
[
"Caricature",
"is",
"an",
"artistic",
"representation",
"that",
"deliberately",
"exaggerates",
"the",
"distinctive",
"features",
"of",
"a",
"human",
"face",
"to",
"convey",
"humor",
"or",
"sarcasm.",
"However,",
"reconstructing",
"a",
"3D",
"caricature",
"from",
"a",
"2D",
"caricature",
"image",
"remains",
"a",
"challenging",
"task,",
"mostly",
"due",
"to",
"the",
"lack",
"of",
"data.",
"We",
"propose",
"to",
"fill",
"this",
"gap",
"by",
"introducing",
"3DCaricShop,",
"the",
"first",
"large-scale",
"3D",
"caricature",
"dataset",
"that",
"contains",
"2000",
"high-quality",
"diversified",
"3D",
"caricatures",
"manually",
"crafted",
"by",
"professional",
"artists.",
"3DCaricShop",
"also",
"provides",
"rich",
"annotations",
"including",
"a",
"paired",
"2D",
"caricature",
"image,",
"camera",
"parameters",
"and",
"3D",
"facial",
"landmarks.",
"To",
"demonstrate",
"the",
"advantage",
"of",
"3DCaricShop,",
"we",
"present",
"a",
"novel",
"baseline",
"approach",
"for",
"single-view",
"3D",
"caricature",
"reconstruction.",
"To",
"ensure",
"a",
"faithful",
"reconstruction",
"with",
"plausible",
"face",
"deformations,",
"we",
"propose",
"to",
"connect",
"the",
"good",
"ends",
"of",
"the",
"detailrich",
"implicit",
"functions",
"and",
"the",
"parametric",
"mesh",
"representations.",
"In",
"particular,",
"we",
"first",
"register",
"a",
"template",
"mesh",
"to",
"the",
"output",
"of",
"the",
"implicit",
"generator",
"and",
"iteratively",
"project",
"the",
"registration",
"result",
"onto",
"a",
"pre-trained",
"PCA",
"space",
"to",
"resolve",
"artifacts",
"and",
"self-intersections.",
"To",
"deal",
"with",
"the",
"large",
"deformation",
"during",
"non-rigid",
"registration,",
"we",
"propose",
"a",
"novel",
"view-collaborative",
"graph",
"convolution",
"network",
"(VCGCN)",
"to",
"extract",
"key",
"points",
"from",
"the",
"implicit",
"mesh",
"for",
"accurate",
"alignment.",
"Our",
"method",
"is",
"able",
"to",
"generate",
"highfidelity",
"3D",
"caricature",
"in",
"a",
"pre-defined",
"mesh",
"topology",
"that",
"is",
"animation-ready.",
"Extensive",
"experiments",
"have",
"been",
"conducted",
"on",
"3DCaricShop",
"to",
"verify",
"the",
"significance",
"of",
"the",
"database",
"and",
"the",
"effectiveness",
"of",
"the",
"proposed",
"method."
] |
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[
"We",
"present",
"a",
"new",
"method",
"for",
"detecting",
"and",
"disambiguating",
"named",
"entities",
"in",
"open",
"domain",
"text",
".",
"A",
"disambiguation",
"SVM",
"kernel",
"is",
"trained",
"to",
"exploit",
"the",
"high",
"coverage",
"and",
"rich",
"structure",
"of",
"the",
"knowledge",
"encoded",
"in",
"an",
"online",
"encyclopedia",
".",
"The",
"resulting",
"model",
"significantly",
"outperforms",
"a",
"less",
"informed",
"baseline",
"."
] |
[
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[
"Today,",
"we",
"are",
"seeing",
"an",
"ever-increasing",
"number",
"of",
"clinical",
"notes",
"that",
"contain",
"clinical",
"results,",
"images,",
"and",
"textual",
"descriptions",
"of",
"patient's",
"health",
"state.",
"All",
"these",
"data",
"can",
"be",
"analyzed",
"and",
"employed",
"to",
"cater",
"novel",
"services",
"that",
"can",
"help",
"people",
"and",
"domain",
"experts",
"with",
"their",
"common",
"healthcare",
"tasks.",
"However,",
"many",
"technologies",
"such",
"as",
"Deep",
"Learning",
"and",
"tools",
"like",
"Word",
"Embeddings",
"have",
"started",
"to",
"be",
"investigated",
"only",
"recently,",
"and",
"many",
"challenges",
"remain",
"open",
"when",
"it",
"comes",
"to",
"healthcare",
"domain",
"applications.",
"To",
"address",
"these",
"challenges,",
"we",
"propose",
"the",
"use",
"of",
"Deep",
"Learning",
"and",
"Word",
"Embeddings",
"for",
"identifying",
"sixteen",
"morbidity",
"types",
"within",
"textual",
"descriptions",
"of",
"clinical",
"records.",
"For",
"this",
"purpose,",
"we",
"have",
"used",
"a",
"Deep",
"Learning",
"model",
"based",
"on",
"Bidirectional",
"Long-Short",
"Term",
"Memory",
"(LSTM)",
"layers",
"which",
"can",
"exploit",
"state-of-the-art",
"vector",
"representations",
"of",
"data",
"such",
"as",
"Word",
"Embeddings",
".",
"We",
"have",
"employed",
"pre-trained",
"Word",
"Embeddings",
"namely",
"GloVe",
"and",
"Word2Vec,",
"and",
"our",
"own",
"Word",
"Embeddings",
"trained",
"on",
"the",
"target",
"domain.",
"Furthermore,",
"we",
"have",
"compared",
"the",
"performances",
"of",
"the",
"deep",
"learning",
"approaches",
"against",
"the",
"traditional",
"tf-idf",
"using",
"Support",
"Vector",
"Machine",
"and",
"Multilayer",
"perceptron",
"(our",
"baselines).",
"From",
"the",
"obtained",
"results",
"it",
"seems",
"that",
"the",
"latter",
"outperforms",
"the",
"combination",
"of",
"Deep",
"Learning",
"approaches",
"using",
"any",
"word",
"embeddings.",
"Our",
"preliminary",
"results",
"indicate",
"that",
"there",
"are",
"specific",
"features",
"that",
"make",
"the",
"dataset",
"biased",
"in",
"favour",
"of",
"traditional",
"machine",
"learning",
"approaches."
] |
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[
"Designing",
"rewards",
"for",
"Reinforcement",
"Learning",
"(RL)",
"is",
"challenging",
"because",
"it",
"needs",
"to",
"convey",
"the",
"desired",
"task,",
"be",
"efficient",
"to",
"optimize,",
"and",
"be",
"easy",
"to",
"compute.",
"The",
"latter",
"is",
"particularly",
"problematic",
"when",
"applying",
"RL",
"to",
"robotics,",
"where",
"detecting",
"whether",
"the",
"desired",
"configuration",
"is",
"reached",
"might",
"require",
"considerable",
"supervision",
"and",
"instrumentation.",
"Furthermore,",
"we",
"are",
"often",
"interested",
"in",
"being",
"able",
"to",
"reach",
"a",
"wide",
"range",
"of",
"configurations,",
"hence",
"setting",
"up",
"a",
"different",
"reward",
"every",
"time",
"might",
"be",
"unpractical.",
"Methods",
"like",
"Hindsight",
"Experience",
"Replay",
"(HER)",
"have",
"recently",
"shown",
"promise",
"to",
"learn",
"policies",
"able",
"to",
"reach",
"many",
"goals,",
"without",
"the",
"need",
"of",
"a",
"reward.",
"Unfortunately,",
"without",
"tricks",
"like",
"resetting",
"to",
"points",
"along",
"the",
"trajectory,",
"HER",
"might",
"require",
"many",
"samples",
"to",
"discover",
"how",
"to",
"reach",
"certain",
"areas",
"of",
"the",
"state-space.",
"In",
"this",
"work",
"we",
"investigate",
"different",
"approaches",
"to",
"incorporate",
"demonstrations",
"to",
"drastically",
"speed",
"up",
"the",
"convergence",
"to",
"a",
"policy",
"able",
"to",
"reach",
"any",
"goal,",
"also",
"surpassing",
"the",
"performance",
"of",
"an",
"agent",
"trained",
"with",
"other",
"Imitation",
"Learning",
"algorithms.",
"Furthermore,",
"we",
"show",
"our",
"method",
"can",
"also",
"be",
"used",
"when",
"the",
"available",
"expert",
"trajectories",
"do",
"not",
"contain",
"the",
"actions,",
"which",
"can",
"leverage",
"kinesthetic",
"or",
"third",
"person",
"demonstration.",
"The",
"code",
"is",
"available",
"at",
"https://sites.google.com/view/goalconditioned-il/."
] |
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[
"Recurrent",
"Neural",
"Networks",
"(RNN)",
"are",
"widely",
"used",
"for",
"learning",
"sequences",
"in",
"applications",
"such",
"as",
"EEG",
"classification.",
"Complex",
"RNNs",
"could",
"be",
"hardly",
"deployed",
"on",
"wearable",
"devices",
"due",
"to",
"their",
"computation",
"and",
"memory-intensive",
"processing",
"patterns.",
"Generally,",
"reduction",
"in",
"precision",
"leads",
"much",
"more",
"efficiency",
"and",
"binarized",
"RNNs",
"are",
"introduced",
"as",
"energy-efficient",
"solutions.",
"However,",
"naive",
"binarization",
"methods",
"lead",
"to",
"significant",
"accuracy",
"loss",
"in",
"EEG",
"classification.",
"In",
"this",
"paper,",
"we",
"propose",
"a",
"multi-level",
"binarized",
"LSTM",
",",
"which",
"significantly",
"reduces",
"computations",
"whereas",
"ensuring",
"an",
"accuracy",
"pretty",
"close",
"to",
"the",
"full",
"precision",
"LSTM",
".",
"Our",
"method",
"reduces",
"the",
"delay",
"of",
"the",
"3-bit",
"LSTM",
"cell",
"operation",
"47*",
"with",
"less",
"than",
"0.01%",
"accuracy",
"loss."
] |
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[
"How",
"can",
"we",
"efficiently",
"compress",
"a",
"model",
"while",
"maintaining",
"its",
"performance?",
"Knowledge",
"Distillation",
"(KD)",
"is",
"one",
"of",
"the",
"widely",
"known",
"methods",
"for",
"model",
"compression.",
"In",
"essence,",
"KD",
"trains",
"a",
"smaller",
"student",
"model",
"based",
"on",
"a",
"larger",
"teacher",
"model",
"and",
"tries",
"to",
"retain",
"the",
"teacher",
"model's",
"level",
"of",
"performance",
"as",
"much",
"as",
"possible.",
"However,",
"existing",
"KD",
"methods",
"suffer",
"from",
"the",
"following",
"limitations.",
"First,",
"since",
"the",
"student",
"model",
"is",
"smaller",
"in",
"absolute",
"size,",
"it",
"inherently",
"lacks",
"model",
"capacity.",
"Second,",
"the",
"absence",
"of",
"an",
"initial",
"guide",
"for",
"the",
"student",
"model",
"makes",
"it",
"difficult",
"for",
"the",
"student",
"to",
"imitate",
"the",
"teacher",
"model",
"to",
"its",
"fullest.",
"Conventional",
"KD",
"methods",
"yield",
"low",
"performance",
"due",
"to",
"these",
"limitations.",
"In",
"this",
"paper,",
"we",
"propose",
"Pea-KD",
"(Parameter-efficient",
"and",
"accurate",
"Knowledge",
"Distillation",
"),",
"a",
"novel",
"approach",
"to",
"KD.",
"Pea-KD",
"consists",
"of",
"two",
"main",
"parts:",
"Shuffled",
"Parameter",
"Sharing",
"(SPS)",
"and",
"Pretraining",
"with",
"Teacher's",
"Predictions",
"(PTP).",
"Using",
"this",
"combination,",
"we",
"are",
"capable",
"of",
"alleviating",
"the",
"KD's",
"limitations.",
"SPS",
"is",
"a",
"new",
"parameter",
"sharing",
"method",
"that",
"increases",
"the",
"student",
"model",
"capacity.",
"PTP",
"is",
"a",
"KD-specialized",
"initialization",
"method,",
"which",
"can",
"act",
"as",
"a",
"good",
"initial",
"guide",
"for",
"the",
"student.",
"When",
"combined,",
"this",
"method",
"yields",
"a",
"significant",
"increase",
"in",
"student",
"model's",
"performance.",
"Experiments",
"conducted",
"on",
"BERT",
"with",
"different",
"datasets",
"and",
"tasks",
"show",
"that",
"the",
"proposed",
"approach",
"improves",
"the",
"student",
"model's",
"performance",
"by",
"4.4\\%",
"on",
"average",
"in",
"four",
"GLUE",
"tasks,",
"outperforming",
"existing",
"KD",
"baselines",
"by",
"significant",
"margins."
] |
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6
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[
"Text-based",
"Question",
"Generation",
"(QG)",
"aims",
"at",
"generating",
"natural",
"and",
"relevant",
"questions",
"that",
"can",
"be",
"answered",
"by",
"a",
"given",
"answer",
"in",
"some",
"context.",
"Existing",
"QG",
"models",
"suffer",
"from",
"a",
"semantic\tO\ndrift",
"problem,",
"i.e.,",
"the",
"semantics",
"of",
"the",
"model-generated",
"question",
"drifts",
"away",
"from",
"the",
"given",
"context",
"and",
"answer.",
"In",
"this",
"paper,",
"we",
"first",
"propose",
"two",
"semantics-enhanced",
"rewards",
"obtained",
"from",
"downstream",
"question",
"paraphrasing",
"and",
"question",
"answering",
"tasks",
"to",
"regularize",
"the",
"QG",
"model",
"to",
"generate",
"semantically",
"valid",
"questions.",
"Second,",
"since",
"the",
"traditional",
"evaluation",
"metrics",
"(e.g.,",
"BLEU)",
"often",
"fall",
"short",
"in",
"evaluating",
"the",
"quality",
"of",
"generated",
"questions,",
"we",
"propose",
"a",
"QA-based",
"evaluation",
"method",
"which",
"measures",
"the",
"QG",
"model's",
"ability",
"to",
"mimic",
"human",
"annotators",
"in",
"generating",
"QA",
"training",
"data.",
"Experiments",
"show",
"that",
"our",
"method",
"achieves",
"the",
"new",
"state-of-the-art",
"performance",
"w.r.t.",
"traditional",
"metrics,",
"and",
"also",
"performs",
"best",
"on",
"our",
"QA-based",
"evaluation",
"metrics.",
"Further,",
"we",
"investigate",
"how",
"to",
"use",
"our",
"QG",
"model",
"to",
"augment",
"QA",
"datasets",
"and",
"enable",
"semi-supervised",
"QA.",
"We",
"propose",
"two",
"ways",
"to",
"generate",
"synthetic",
"QA",
"pairs:",
"generate",
"new",
"questions",
"from",
"existing",
"articles",
"or",
"collect",
"QA",
"pairs",
"from",
"new",
"articles.",
"We",
"also",
"propose",
"two",
"empirically",
"effective",
"strategies,",
"a",
"data",
"filter",
"and",
"mixing",
"mini-batch",
"training,",
"to",
"properly",
"use",
"the",
"QG-generated",
"data",
"for",
"QA.",
"Experiments",
"show",
"that",
"our",
"method",
"improves",
"over",
"both",
"BiDAF",
"and",
"BERT",
"QA",
"baselines,",
"even",
"without",
"introducing",
"new",
"articles."
] |
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[
"This",
"work",
"improves",
"the",
"quality",
"of",
"automated",
"machine",
"learning",
"(AutoML",
")",
"systems",
"by",
"using",
"dataset",
"and",
"function",
"descriptions",
"while",
"significantly",
"decreasing",
"computation",
"time",
"from",
"minutes",
"to",
"milliseconds",
"by",
"using",
"a",
"zero-shot",
"approach.",
"Given",
"a",
"new",
"dataset",
"and",
"a",
"well-defined",
"machine",
"learning",
"task,",
"humans",
"begin",
"by",
"reading",
"a",
"description",
"of",
"the",
"dataset",
"and",
"documentation",
"for",
"the",
"algorithms",
"to",
"be",
"used.",
"This",
"work",
"is",
"the",
"first",
"to",
"use",
"these",
"textual",
"descriptions,",
"which",
"we",
"call",
"privileged",
"information,",
"for",
"AutoML",
".",
"We",
"use",
"a",
"pre-trained",
"Transformer",
"model",
"to",
"process",
"the",
"privileged",
"text",
"and",
"demonstrate",
"that",
"using",
"this",
"information",
"improves",
"AutoML",
"performance.",
"Thus,",
"our",
"approach",
"leverages",
"the",
"progress",
"of",
"unsupervised",
"representation",
"learning",
"in",
"natural",
"language",
"processing",
"to",
"provide",
"a",
"significant",
"boost",
"to",
"AutoML",
".",
"We",
"demonstrate",
"that",
"using",
"only",
"textual",
"descriptions",
"of",
"the",
"data",
"and",
"functions",
"achieves",
"reasonable",
"classification",
"performance,",
"and",
"adding",
"textual",
"descriptions",
"to",
"data",
"meta-features",
"improves",
"classification",
"across",
"tabular",
"datasets.",
"To",
"achieve",
"zero-shot",
"AutoML",
"we",
"train",
"a",
"graph",
"neural",
"network",
"with",
"these",
"description",
"embeddings",
"and",
"the",
"data",
"meta-features.",
"Each",
"node",
"represents",
"a",
"training",
"dataset,",
"which",
"we",
"use",
"to",
"predict",
"the",
"best",
"machine",
"learning",
"pipeline",
"for",
"a",
"new",
"test",
"dataset",
"in",
"a",
"zero-shot",
"fashion.",
"Our",
"zero-shot",
"approach",
"rapidly",
"predicts",
"a",
"high-quality",
"pipeline",
"for",
"a",
"supervised",
"learning",
"task",
"and",
"dataset.",
"In",
"contrast,",
"most",
"AutoML",
"systems",
"require",
"tens",
"or",
"hundreds",
"of",
"pipeline",
"evaluations.",
"We",
"show",
"that",
"zero-shot",
"AutoML",
"reduces",
"running",
"and",
"prediction",
"times",
"from",
"minutes",
"to",
"milliseconds,",
"consistently",
"across",
"datasets.",
"By",
"speeding",
"up",
"AutoML",
"by",
"orders",
"of",
"magnitude",
"this",
"work",
"demonstrates",
"real-time",
"AutoML",
"."
] |
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[
"Aspect-based",
"Sentiment",
"Analysis",
"(ABSA)",
"aims",
"to",
"identify",
"the",
"aspect",
"terms,",
"their",
"corresponding",
"sentiment",
"polarities,",
"and",
"the",
"opinion",
"terms.",
"There",
"exist",
"seven",
"subtasks",
"in",
"ABSA.",
"Most",
"studies",
"only",
"focus",
"on",
"the",
"subsets",
"of",
"these",
"subtasks,",
"which",
"leads",
"to",
"various",
"complicated",
"ABSA",
"models",
"while",
"hard",
"to",
"solve",
"these",
"subtasks",
"in",
"a",
"unified",
"framework.",
"In",
"this",
"paper,",
"we",
"redefine",
"every",
"subtask",
"target",
"as",
"a",
"sequence",
"mixed",
"by",
"pointer",
"indexes",
"and",
"sentiment",
"class",
"indexes,",
"which",
"converts",
"all",
"ABSA",
"subtasks",
"into",
"a",
"unified",
"generative",
"formulation.",
"Based",
"on",
"the",
"unified",
"formulation,",
"we",
"exploit",
"the",
"pre-training",
"sequence-to-sequence",
"model",
"BART",
"to",
"solve",
"all",
"ABSA",
"subtasks",
"in",
"an",
"end-to-end",
"framework.",
"Extensive",
"experiments",
"on",
"four",
"ABSA",
"datasets",
"for",
"seven",
"subtasks",
"demonstrate",
"that",
"our",
"framework",
"achieves",
"substantial",
"performance",
"gain",
"and",
"provides",
"a",
"real",
"unified",
"end-to-end",
"solution",
"for",
"the",
"whole",
"ABSA",
"subtasks,",
"which",
"could",
"benefit",
"multiple",
"tasks."
] |
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[
"Even",
"though",
"model",
"predictive",
"control",
"(MPC)",
"is",
"currently",
"the",
"main",
"algorithm",
"for",
"insulin",
"control",
"in",
"the",
"artificial",
"pancreas",
"(AP),",
"it",
"usually",
"requires",
"complex",
"online",
"optimizations,",
"which",
"are",
"infeasible",
"for",
"resource-constrained",
"medical",
"devices.",
"MPC",
"also",
"typically",
"relies",
"on",
"state",
"estimation,",
"an",
"error-prone",
"process.",
"In",
"this",
"paper,",
"we",
"introduce",
"a",
"novel",
"approach",
"to",
"AP",
"control",
"that",
"uses",
"Imitation",
"Learning",
"to",
"synthesize",
"neural-network",
"insulin",
"policies",
"from",
"MPC-computed",
"demonstrations.",
"Such",
"policies",
"are",
"computationally",
"efficient",
"and,",
"by",
"instrumenting",
"MPC",
"at",
"training",
"time",
"with",
"full",
"state",
"information,",
"they",
"can",
"directly",
"map",
"measurements",
"into",
"optimal",
"therapy",
"decisions,",
"thus",
"bypassing",
"state",
"estimation.",
"We",
"apply",
"Bayesian",
"inference",
"via",
"Monte",
"Carlo",
"Dropout",
"to",
"learn",
"policies,",
"which",
"allows",
"us",
"to",
"quantify",
"prediction",
"uncertainty",
"and",
"thereby",
"derive",
"safer",
"therapy",
"decisions.",
"We",
"show",
"that",
"our",
"control",
"policies",
"trained",
"under",
"a",
"specific",
"patient",
"model",
"readily",
"generalize",
"(in",
"terms",
"of",
"model",
"parameters",
"and",
"disturbance",
"distributions)",
"to",
"patient",
"cohorts,",
"consistently",
"outperforming",
"traditional",
"MPC",
"with",
"state",
"estimation."
] |
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[
"This",
"is",
"a",
"short",
"technical",
"report",
"introducing",
"the",
"solution",
"of",
"the",
"Team",
"TCParser",
"for",
"Short-video",
"Face",
"Parsing",
"Track",
"of",
"The",
"3rd",
"Person",
"in",
"Context",
"(PIC)",
"Workshop",
"and",
"Challenge",
"at",
"CVPR",
"2021",
"In",
"this",
"paper,",
"we",
"introduce",
"a",
"strong",
"backbone",
"which",
"is",
"cross-window",
"based",
"Shuffle",
"Transformer",
"for",
"presenting",
"accurate",
"face",
"parsing",
"representation.",
"To",
"further",
"obtain",
"the",
"finer",
"segmentation",
"results,",
"especially",
"on",
"the",
"edges,",
"we",
"introduce",
"a",
"Feature",
"Alignment",
"Aggregation",
"(FAA)",
"module.",
"It",
"can",
"effectively",
"relieve",
"the",
"feature",
"misalignment",
"issue",
"caused",
"by",
"multi-resolution",
"feature",
"aggregation.",
"Benefiting",
"from",
"the",
"stronger",
"backbone",
"and",
"better",
"feature",
"aggregation,",
"the",
"proposed",
"method",
"achieves",
"86.95%",
"score",
"in",
"the",
"Short-video",
"Face",
"Parsing",
"track",
"of",
"the",
"3rd",
"Person",
"in",
"Context",
"(PIC)",
"Workshop",
"and",
"Challenge,",
"ranked",
"the",
"first",
"place."
] |
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[
"Portrait",
"matting",
"is",
"an",
"important",
"research",
"problem",
"with",
"a",
"wide",
"range",
"of",
"applications,",
"such",
"as",
"video",
"conference",
"app,",
"image/video",
"editing,",
"and",
"post-production.",
"The",
"goal",
"is",
"to",
"predict",
"an",
"alpha",
"matte",
"that",
"identifies",
"the",
"effect",
"of",
"each",
"pixel",
"on",
"the",
"foreground",
"subject.",
"Traditional",
"approaches",
"and",
"most",
"of",
"the",
"existing",
"works",
"utilized",
"an",
"additional",
"input,",
"e.g.,",
"trimap,",
"background",
"image,",
"to",
"predict",
"alpha",
"matte.",
"However,",
"providing",
"additional",
"input",
"is",
"not",
"always",
"practical.",
"Besides,",
"models",
"are",
"too",
"sensitive",
"to",
"these",
"additional",
"inputs.",
"In",
"this",
"paper,",
"we",
"introduce",
"an",
"additional",
"input-free",
"approach",
"to",
"perform",
"portrait",
"matting",
"using",
"Generative",
"Adversarial",
"Nets",
"(GANs).",
"We",
"divide",
"the",
"main",
"task",
"into",
"two",
"subtasks.",
"For",
"this,",
"we",
"propose",
"a",
"segmentation",
"network",
"for",
"the",
"person",
"segmentation",
"and",
"the",
"alpha",
"generation",
"network",
"for",
"alpha",
"matte",
"prediction.",
"While",
"the",
"segmentation",
"network",
"takes",
"an",
"input",
"image",
"and",
"produces",
"a",
"coarse",
"segmentation",
"map,",
"the",
"alpha",
"generation",
"network",
"utilizes",
"the",
"same",
"input",
"image",
"as",
"well",
"as",
"a",
"coarse",
"segmentation",
"map",
"that",
"is",
"produced",
"by",
"the",
"segmentation",
"network",
"to",
"predict",
"the",
"alpha",
"matte.",
"Besides,",
"we",
"present",
"a",
"segmentation",
"encoding",
"block",
"to",
"downsample",
"the",
"coarse",
"segmentation",
"map",
"and",
"provide",
"feature",
"representation",
"to",
"the",
"residual",
"block.",
"Furthermore,",
"we",
"propose",
"border",
"loss",
"to",
"penalize",
"only",
"the",
"borders",
"of",
"the",
"subject",
"separately",
"which",
"is",
"more",
"likely",
"to",
"be",
"challenging",
"and",
"we",
"also",
"adapt",
"perceptual",
"loss",
"for",
"portrait",
"matting.",
"To",
"train",
"the",
"proposed",
"system,",
"we",
"combine",
"two",
"different",
"popular",
"training",
"datasets",
"to",
"improve",
"the",
"amount",
"of",
"data",
"as",
"well",
"as",
"diversity",
"to",
"address",
"domain",
"shift",
"problems",
"in",
"the",
"inference",
"time.",
"We",
"tested",
"our",
"model",
"on",
"three",
"different",
"benchmark",
"datasets,",
"namely",
"Adobe",
"Image",
"Matting",
"dataset,",
"Portrait",
"Matting",
"dataset,",
"and",
"Distinctions",
"dataset.",
"The",
"proposed",
"method",
"outperformed",
"the",
"MODNet",
"method",
"that",
"also",
"takes",
"a",
"single",
"input."
] |
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[
"To",
"account",
"for",
"the",
"semi-free",
"word",
"order",
"of",
"French",
",",
"Unification",
"Categorial",
"Grammar",
"is",
"extended",
"in",
"two",
"ways",
".",
"First",
",",
"verbal",
"valencies",
"are",
"contained",
"in",
"a",
"set",
"rather",
"than",
"in",
"a",
"list",
".",
"Second",
",",
"type-raised",
"NP",
"'s",
"are",
"described",
"as",
"two-sided",
"functors",
".",
"The",
"new",
"framework",
"does",
"not",
"overgenerate",
"i.e.",
",",
"it",
"accepts",
"all",
"and",
"only",
"the",
"sentences",
"which",
"are",
"grammatical",
".",
"This",
"follows",
"partly",
"from",
"the",
"elimination",
"of",
"FALSE",
"lexical",
"ambiguities",
"-",
"i.e.",
",",
"ambiguities",
"introduced",
"in",
"order",
"to",
"account",
"for",
"all",
"the",
"possible",
"positions",
"a",
"word",
"can",
"be",
"in",
"within",
"a",
"sentence",
"-",
"and",
"partly",
"from",
"a",
"system",
"of",
"features",
"constraining",
"the",
"possible",
"combinations",
"."
] |
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[
"Classification",
"and",
"localization",
"are",
"two",
"pillars",
"of",
"visual",
"object",
"detectors.",
"However,",
"in",
"CNN-based",
"detectors,",
"these",
"two",
"modules",
"are",
"usually",
"optimized",
"under",
"a",
"fixed",
"set",
"of",
"candidate",
"(or",
"anchor)",
"bounding",
"boxes.",
"This",
"configuration",
"significantly",
"limits",
"the",
"possibility",
"to",
"jointly",
"optimize",
"classification",
"and",
"localization.",
"In",
"this",
"paper,",
"we",
"propose",
"a",
"Multiple",
"Instance",
"Learning",
"(MIL)",
"approach",
"that",
"selects",
"anchors",
"and",
"jointly",
"optimizes",
"the",
"two",
"modules",
"of",
"a",
"CNN-based",
"object",
"detector.",
"Our",
"approach,",
"referred",
"to",
"as",
"Multiple",
"Anchor",
"Learning",
"(MAL),",
"constructs",
"anchor",
"bags",
"and",
"selects",
"the",
"most",
"representative",
"anchors",
"from",
"each",
"bag.",
"Such",
"an",
"iterative",
"selection",
"process",
"is",
"potentially",
"NP-hard",
"to",
"optimize.",
"To",
"address",
"this",
"issue,",
"we",
"solve",
"MAL",
"by",
"repetitively",
"depressing",
"the",
"confidence",
"of",
"selected",
"anchors",
"by",
"perturbing",
"their",
"corresponding",
"features.",
"In",
"an",
"adversarial",
"selection-depression",
"manner,",
"MAL",
"not",
"only",
"pursues",
"optimal",
"solutions",
"but",
"also",
"fully",
"leverages",
"multiple",
"anchors/features",
"to",
"learn",
"a",
"detection",
"model.",
"Experiments",
"show",
"that",
"MAL",
"improves",
"the",
"baseline",
"RetinaNet",
"with",
"significant",
"margins",
"on",
"the",
"commonly",
"used",
"MS-COCO",
"object",
"detection",
"benchmark",
"and",
"achieves",
"new",
"state-of-the-art",
"detection",
"performance",
"compared",
"with",
"recent",
"methods."
] |
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[
"Gaussian",
"Process",
"is",
"a",
"non-parametric",
"prior",
"which",
"can",
"be",
"understood",
"as",
"a",
"distribution",
"on",
"the",
"function",
"space",
"intuitively.",
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"is",
"known",
"that",
"by",
"introducing",
"appropriate",
"prior",
"to",
"the",
"weights",
"of",
"the",
"neural",
"networks,",
"Gaussian",
"Process",
"can",
"be",
"obtained",
"by",
"taking",
"the",
"infinite-width",
"limit",
"of",
"the",
"Bayesian",
"neural",
"networks",
"from",
"a",
"Bayesian",
"perspective.",
"In",
"this",
"paper,",
"we",
"explore",
"the",
"infinitely",
"wide",
"Tensor",
"Networks",
"and",
"show",
"the",
"equivalence",
"of",
"the",
"infinitely",
"wide",
"Tensor",
"Networks",
"and",
"the",
"Gaussian",
"Process",
".",
"We",
"study",
"the",
"pure",
"Tensor",
"Network",
"and",
"another",
"two",
"extended",
"Tensor",
"Network",
"structures:",
"Neural",
"Kernel",
"Tensor",
"Network",
"and",
"Tensor",
"Network",
"hidden",
"layer",
"Neural",
"Network",
"and",
"prove",
"that",
"each",
"one",
"will",
"converge",
"to",
"the",
"Gaussian",
"Process",
"as",
"the",
"width",
"of",
"each",
"model",
"goes",
"to",
"infinity.",
"(We",
"note",
"here",
"that",
"Gaussian",
"Process",
"can",
"also",
"be",
"obtained",
"by",
"taking",
"the",
"infinite",
"limit",
"of",
"at",
"least",
"one",
"of",
"the",
"bond",
"dimensions",
"$\\alpha_{i}$",
"in",
"the",
"product",
"of",
"tensor",
"nodes,",
"and",
"the",
"proofs",
"can",
"be",
"done",
"with",
"the",
"same",
"ideas",
"in",
"the",
"proofs",
"of",
"the",
"infinite-width",
"cases.)",
"We",
"calculate",
"the",
"mean",
"function",
"(mean",
"vector)",
"and",
"the",
"covariance",
"function",
"(covariance",
"matrix)",
"of",
"the",
"finite",
"dimensional",
"distribution",
"of",
"the",
"induced",
"Gaussian",
"Process",
"by",
"the",
"infinite-width",
"tensor",
"network",
"with",
"a",
"general",
"set-up.",
"We",
"study",
"the",
"properties",
"of",
"the",
"covariance",
"function",
"and",
"derive",
"the",
"approximation",
"of",
"the",
"covariance",
"function",
"when",
"the",
"integral",
"in",
"the",
"expectation",
"operator",
"is",
"intractable.",
"In",
"the",
"numerical",
"experiments,",
"we",
"implement",
"the",
"Gaussian",
"Process",
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"find",
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"60-70%",
"of",
"test-time",
"answers",
"are",
"also",
"present",
"somewhere",
"in",
"the",
"training",
"sets.",
"We",
"also",
"find",
"that",
"30%",
"of",
"test-set",
"questions",
"have",
"a",
"near-duplicate",
"paraphrase",
"in",
"their",
"corresponding",
"training",
"sets.",
"Using",
"these",
"findings,",
"we",
"evaluate",
"a",
"variety",
"of",
"popular",
"open-domain",
"models",
"to",
"obtain",
"greater",
"insight",
"into",
"what",
"extent",
"they",
"can",
"actually",
"generalize,",
"and",
"what",
"drives",
"their",
"overall",
"performance.",
"We",
"find",
"that",
"all",
"models",
"perform",
"dramatically",
"worse",
"on",
"questions",
"that",
"cannot",
"be",
"memorized",
"from",
"training",
"sets,",
"with",
"a",
"mean",
"absolute",
"performance",
"difference",
"of",
"63%",
"between",
"repeated",
"and",
"non-repeated",
"data.",
"Finally",
"we",
"show",
"that",
"simple",
"nearest-neighbor",
"models",
"out-perform",
"a",
"BART",
"closed-book",
"QA",
"model,",
"further",
"highlighting",
"the",
"role",
"that",
"training",
"set",
"memorization",
"plays",
"in",
"these",
"benchmarks"
] |
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[
"Vision-Language",
"Pre-training",
"(VLP)",
"aims",
"to",
"learn",
"multi-modal",
"representations",
"from",
"image-text",
"pairs",
"and",
"serves",
"for",
"downstream",
"vision-language",
"tasks",
"in",
"a",
"fine-tuning",
"fashion.",
"The",
"dominant",
"VLP",
"models",
"adopt",
"a",
"CNN-Transformer",
"architecture,",
"which",
"embeds",
"images",
"with",
"a",
"CNN,",
"and",
"then",
"aligns",
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"and",
"text",
"with",
"a",
"Transformer",
".",
"Visual",
"relationship",
"between",
"visual",
"contents",
"plays",
"an",
"important",
"role",
"in",
"image",
"understanding",
"and",
"is",
"the",
"basic",
"for",
"inter-modal",
"alignment",
"learning.",
"However,",
"CNNs",
"have",
"limitations",
"in",
"visual",
"relation",
"learning",
"due",
"to",
"local",
"receptive",
"field's",
"weakness",
"in",
"modeling",
"long-range",
"dependencies.",
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"the",
"two",
"objectives",
"of",
"learning",
"visual",
"relation",
"and",
"inter-modal",
"alignment",
"are",
"encapsulated",
"in",
"the",
"same",
"Transformer",
"network.",
"Such",
"design",
"might",
"restrict",
"the",
"inter-modal",
"alignment",
"learning",
"in",
"the",
"Transformer",
"by",
"ignoring",
"the",
"specialized",
"characteristic",
"of",
"each",
"objective.",
"To",
"tackle",
"this,",
"we",
"propose",
"a",
"fully",
"Transformer",
"visual",
"embedding",
"for",
"VLP",
"to",
"better",
"learn",
"visual",
"relation",
"and",
"further",
"promote",
"inter-modal",
"alignment.",
"Specifically,",
"we",
"propose",
"a",
"metric",
"named",
"Inter-Modality",
"Flow",
"(IMF)",
"to",
"measure",
"the",
"interaction",
"between",
"vision",
"and",
"language",
"modalities",
"(i.e.,",
"inter-modality).",
"We",
"also",
"design",
"a",
"novel",
"masking",
"optimization",
"mechanism",
"named",
"Masked",
"Feature",
"Regression",
"(MFR)",
"in",
"Transformer",
"to",
"further",
"promote",
"the",
"inter-modality",
"learning.",
"To",
"the",
"best",
"of",
"our",
"knowledge,",
"this",
"is",
"the",
"first",
"study",
"to",
"explore",
"the",
"benefit",
"of",
"Transformer",
"for",
"visual",
"feature",
"learning",
"in",
"VLP.",
"We",
"verify",
"our",
"method",
"on",
"a",
"wide",
"range",
"of",
"vision-language",
"tasks,",
"including",
"Image-Text",
"Retrieval,",
"Visual",
"Question",
"Answering",
"(VQA),",
"Visual",
"Entailment",
"and",
"Visual",
"Reasoning.",
"Our",
"approach",
"not",
"only",
"outperforms",
"the",
"state-of-the-art",
"VLP",
"performance,",
"but",
"also",
"shows",
"benefits",
"on",
"the",
"IMF",
"metric."
] |
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[
"Content-based",
"histopathological",
"image",
"retrieval",
"(CBHIR)",
"has",
"become",
"popular",
"in",
"recent",
"years",
"in",
"the",
"domain",
"of",
"histopathological",
"image",
"analysis.",
"CBHIR",
"systems",
"provide",
"auxiliary",
"diagnosis",
"information",
"for",
"pathologists",
"by",
"searching",
"for",
"and",
"returning",
"regions",
"that",
"are",
"contently",
"similar",
"to",
"the",
"region",
"of",
"interest",
"(ROI)",
"from",
"a",
"pre-established",
"database.",
"While,",
"it",
"is",
"challenging",
"and",
"yet",
"significant",
"in",
"clinical",
"applications",
"to",
"retrieve",
"diagnostically",
"relevant",
"regions",
"from",
"a",
"database",
"that",
"consists",
"of",
"histopathological",
"whole",
"slide",
"images",
"(WSIs)",
"for",
"a",
"query",
"ROI.",
"In",
"this",
"paper,",
"we",
"propose",
"a",
"novel",
"framework",
"for",
"regions",
"retrieval",
"from",
"WSI-database",
"based",
"on",
"hierarchical",
"graph",
"convolutional",
"networks",
"(GCN",
"s)",
"and",
"Hash",
"technique.",
"Compared",
"to",
"the",
"present",
"CBHIR",
"framework,",
"the",
"structural",
"information",
"of",
"WSI",
"is",
"preserved",
"through",
"graph",
"embedding",
"of",
"GCN",
"s,",
"which",
"makes",
"the",
"retrieval",
"framework",
"more",
"sensitive",
"to",
"regions",
"that",
"are",
"similar",
"in",
"tissue",
"distribution.",
"Moreover,",
"benefited",
"from",
"the",
"hierarchical",
"GCN",
"structures,",
"the",
"proposed",
"framework",
"has",
"good",
"scalability",
"for",
"both",
"the",
"size",
"and",
"shape",
"variation",
"of",
"ROIs.",
"It",
"allows",
"the",
"pathologist",
"defining",
"query",
"regions",
"using",
"free",
"curves",
"according",
"to",
"the",
"appearance",
"of",
"tissue.",
"Thirdly,",
"the",
"retrieval",
"is",
"achieved",
"based",
"on",
"Hash",
"technique,",
"which",
"ensures",
"the",
"framework",
"is",
"efficient",
"and",
"thereby",
"adequate",
"for",
"practical",
"large-scale",
"WSI-database.",
"The",
"proposed",
"method",
"was",
"validated",
"on",
"two",
"public",
"datasets",
"for",
"histopathological",
"WSI",
"analysis",
"and",
"compared",
"to",
"the",
"state-of-the-art",
"methods.",
"The",
"proposed",
"method",
"achieved",
"mean",
"average",
"precision",
"above",
"0.857",
"on",
"the",
"ACDC-LungHP",
"dataset",
"and",
"above",
"0.864",
"on",
"the",
"Camelyon16",
"dataset",
"in",
"the",
"irregular",
"region",
"retrieval",
"tasks,",
"which",
"are",
"superior",
"to",
"the",
"state-of-the-art",
"methods.",
"The",
"average",
"retrieval",
"time",
"from",
"a",
"database",
"within",
"120",
"WSIs",
"is",
"0.802",
"ms."
] |
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[
"The",
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"RLSCCOMB",
"systems",
"which",
"participated",
"in",
"the",
"Senseval-3",
"English",
"lexical",
"sample",
"task",
".",
"These",
"systems",
"are",
"based",
"on",
"Regularized",
"Least-Squares",
"Classification",
"-LRB-",
"RLSC",
"-RRB-",
"learning",
"method",
".",
"We",
"describe",
"the",
"reasons",
"of",
"choosing",
"this",
"method",
",",
"how",
"we",
"applied",
"it",
"to",
"word",
"sense",
"disambiguation",
",",
"what",
"results",
"we",
"obtained",
"on",
"Senseval1",
",",
"Senseval-2",
"and",
"Senseval-3",
"data",
"and",
"discuss",
"some",
"possible",
"improvements",
"."
] |
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[
"This",
"paper",
"describes",
"our",
"submissions",
"for",
"the",
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"Media",
"Mining",
"for",
"Health",
"(SMM4H)2021",
"shared",
"tasks.",
"We",
"participated",
"in",
"2",
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"Classification",
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"extraction",
"and",
"normalization",
"of",
"adverse",
"drug",
"effect",
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"mentions",
"in",
"English",
"tweets",
"(Task-1)",
"and",
"-2",
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"of",
"COVID-19",
"tweets",
"containing",
"symptoms(Task-6).",
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"for",
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"the",
"language",
"representation",
"model",
"RoBERTa",
"with",
"a",
"binary",
"classification",
"head.",
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"the",
"second",
"task,",
"we",
"use",
"BERTweet,",
"based",
"on",
"RoBERTa",
".",
"Fine-tuning",
"is",
"performed",
"on",
"the",
"pre-trained",
"models",
"for",
"both",
"tasks.",
"The",
"models",
"are",
"placed",
"on",
"top",
"of",
"a",
"custom",
"domain-specific",
"processing",
"pipeline.",
"Our",
"system",
"ranked",
"first",
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"all",
"the",
"submissions",
"for",
"subtask-1(a)",
"with",
"an",
"F1-score",
"of",
"61%.",
"For",
"subtask-1(b),",
"our",
"system",
"obtained",
"an",
"F1-score",
"of",
"50%",
"with",
"improvements",
"up",
"to",
"8%",
"F1",
"over",
"the",
"score",
"averaged",
"across",
"all",
"submissions.",
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"model",
"achieved",
"an",
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"score",
"of",
"94%",
"on",
"SMM4H",
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[
"This",
"paper",
"presents",
"the",
"Graded",
"Word",
"Similarity",
"in",
"Context",
"(GWSC)",
"task",
"which",
"asked",
"participants",
"to",
"predict",
"the",
"effects",
"of",
"context",
"on",
"human",
"perception",
"of",
"similarity",
"in",
"English,",
"Croatian,",
"Slovene",
"and",
"Finnish.",
"We",
"received",
"15",
"submissions",
"and",
"11",
"system",
"description",
"papers.",
"A",
"new",
"dataset",
"(CoSimLex)",
"was",
"created",
"for",
"evaluation",
"in",
"this",
"task:",
"it",
"contains",
"pairs",
"of",
"words,",
"each",
"annotated",
"within",
"two",
"different",
"contexts.",
"Systems",
"beat",
"the",
"baselines",
"by",
"significant",
"margins,",
"but",
"few",
"did",
"well",
"in",
"more",
"than",
"one",
"language",
"or",
"subtask.",
"Almost",
"every",
"system",
"employed",
"a",
"Transformer",
"model,",
"but",
"with",
"many",
"variations",
"in",
"the",
"details:",
"WordNet",
"sense",
"embeddings,",
"translation",
"of",
"contexts,",
"TF-IDF",
"weightings,",
"and",
"the",
"automatic",
"creation",
"of",
"datasets",
"for",
"fine-tuning",
"were",
"all",
"used",
"to",
"good",
"effect."
] |
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[
"Purpose:",
"To",
"improve",
"reconstruction",
"fidelity",
"of",
"fine",
"structures",
"and",
"textures",
"in",
"deep",
"learning",
"(DL)",
"based",
"reconstructions.",
"Methods:",
"A",
"novel",
"patch-based",
"Unsupervised",
"Feature",
"Loss",
"(UFLoss",
")",
"is",
"proposed",
"and",
"incorporated",
"into",
"the",
"training",
"of",
"DL-based",
"reconstruction",
"frameworks",
"in",
"order",
"to",
"preserve",
"perceptual",
"similarity",
"and",
"high-order",
"statistics.",
"The",
"UFLoss",
"provides",
"instance-level",
"discrimination",
"by",
"mapping",
"similar",
"instances",
"to",
"similar",
"low-dimensional",
"feature",
"vectors",
"and",
"is",
"trained",
"without",
"any",
"human",
"annotation.",
"By",
"adding",
"an",
"additional",
"loss",
"function",
"on",
"the",
"low-dimensional",
"feature",
"space",
"during",
"training,",
"the",
"reconstruction",
"frameworks",
"from",
"under-sampled",
"or",
"corrupted",
"data",
"can",
"reproduce",
"more",
"realistic",
"images",
"that",
"are",
"closer",
"to",
"the",
"original",
"with",
"finer",
"textures,",
"sharper",
"edges,",
"and",
"improved",
"overall",
"image",
"quality.",
"The",
"performance",
"of",
"the",
"proposed",
"UFLoss",
"is",
"demonstrated",
"on",
"unrolled",
"networks",
"for",
"accelerated",
"2D",
"and",
"3D",
"knee",
"MRI",
"reconstruction",
"with",
"retrospective",
"under-sampling.",
"Quantitative",
"metrics",
"including",
"NRMSE,",
"SSIM",
",",
"and",
"our",
"proposed",
"UFLoss",
"were",
"used",
"to",
"evaluate",
"the",
"performance",
"of",
"the",
"proposed",
"method",
"and",
"compare",
"it",
"with",
"others.",
"Results:",
"In-vivo",
"experiments",
"indicate",
"that",
"adding",
"the",
"UFLoss",
"encourages",
"sharper",
"edges",
"and",
"more",
"faithful",
"contrasts",
"compared",
"to",
"traditional",
"and",
"learning-based",
"methods",
"with",
"pure",
"l2",
"loss.",
"More",
"detailed",
"textures",
"can",
"be",
"seen",
"in",
"both",
"2D",
"and",
"3D",
"knee",
"MR",
"images.",
"Quantitative",
"results",
"indicate",
"that",
"reconstruction",
"with",
"UFLoss",
"can",
"provide",
"comparable",
"NRMSE",
"and",
"a",
"higher",
"SSIM",
"while",
"achieving",
"a",
"much",
"lower",
"UFLoss",
"value.",
"Conclusion:",
"We",
"present",
"UFLoss",
",",
"a",
"patch-based",
"unsupervised",
"learned",
"feature",
"loss,",
"which",
"allows",
"the",
"training",
"of",
"DL-based",
"reconstruction",
"to",
"obtain",
"more",
"detailed",
"texture,",
"finer",
"features,",
"and",
"sharper",
"edges",
"with",
"higher",
"overall",
"image",
"quality",
"under",
"DL-based",
"reconstruction",
"frameworks."
] |
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[
"Automatic",
"Music",
"Transcription",
"(AMT),",
"inferring",
"musical",
"notes",
"from",
"raw",
"audio,",
"is",
"a",
"challenging",
"task",
"at",
"the",
"core",
"of",
"music",
"understanding.",
"Unlike",
"Automatic",
"Speech",
"Recognition",
"(ASR),",
"which",
"typically",
"focuses",
"on",
"the",
"words",
"of",
"a",
"single",
"speaker,",
"AMT",
"often",
"requires",
"transcribing",
"multiple",
"instruments",
"simultaneously,",
"all",
"while",
"preserving",
"fine-scale",
"pitch",
"and",
"timing",
"information.",
"Further,",
"many",
"AMT",
"datasets",
"are",
"``low-resource'',",
"as",
"even",
"expert",
"musicians",
"find",
"music",
"transcription",
"difficult",
"and",
"time-consuming.",
"Thus,",
"prior",
"work",
"has",
"focused",
"on",
"task-specific",
"architectures,",
"tailored",
"to",
"the",
"individual",
"instruments",
"of",
"each",
"task.",
"In",
"this",
"work,",
"motivated",
"by",
"the",
"promising",
"results",
"of",
"sequence-to-sequence",
"transfer",
"learning",
"for",
"low-resource",
"Natural",
"Language",
"Processing",
"(NLP),",
"we",
"demonstrate",
"that",
"a",
"general-purpose",
"Transformer",
"model",
"can",
"perform",
"multi-task",
"AMT,",
"jointly",
"transcribing",
"arbitrary",
"combinations",
"of",
"musical",
"instruments",
"across",
"several",
"transcription",
"datasets.",
"We",
"show",
"this",
"unified",
"training",
"framework",
"achieves",
"high-quality",
"transcription",
"results",
"across",
"a",
"range",
"of",
"datasets,",
"dramatically",
"improving",
"performance",
"for",
"low-resource",
"instruments",
"(such",
"as",
"guitar),",
"while",
"preserving",
"strong",
"performance",
"for",
"abundant",
"instruments",
"(such",
"as",
"piano).",
"Finally,",
"by",
"expanding",
"the",
"scope",
"of",
"AMT,",
"we",
"expose",
"the",
"need",
"for",
"more",
"consistent",
"evaluation",
"metrics",
"and",
"better",
"dataset",
"alignment,",
"and",
"provide",
"a",
"strong",
"baseline",
"for",
"this",
"new",
"direction",
"of",
"multi-task",
"AMT."
] |
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[
"Neural",
"Machine",
"Translation",
"often",
"suffers",
"from",
"an",
"under-translation",
"problem",
"due",
"to",
"its",
"limited",
"modeling",
"of",
"output",
"sequence",
"lengths.",
"In",
"this",
"work,",
"we",
"propose",
"a",
"novel",
"approach",
"to",
"training",
"a",
"Transformer",
"model",
"using",
"length",
"constraints",
"based",
"on",
"length-aware",
"positional",
"encoding",
"(PE).",
"Since",
"length",
"constraints",
"with",
"exact",
"target",
"sentence",
"lengths",
"degrade",
"translation",
"performance,",
"we",
"add",
"random",
"noise",
"within",
"a",
"certain",
"window",
"size",
"to",
"the",
"length",
"constraints",
"in",
"the",
"PE",
"during",
"the",
"training.",
"In",
"the",
"inference",
"step,",
"we",
"predict",
"the",
"output",
"lengths",
"using",
"input",
"sequences",
"and",
"a",
"BERT-based",
"length",
"prediction",
"model.",
"Experimental",
"results",
"in",
"an",
"ASPEC",
"English-to-Japanese",
"translation",
"showed",
"the",
"proposed",
"method",
"produced",
"translations",
"with",
"lengths",
"close",
"to",
"the",
"reference",
"ones",
"and",
"outperformed",
"a",
"vanilla",
"Transformer",
"(especially",
"in",
"short",
"sentences)",
"by",
"3.22",
"points",
"in",
"BLEU.",
"The",
"average",
"translation",
"results",
"using",
"our",
"length",
"prediction",
"model",
"were",
"also",
"better",
"than",
"another",
"baseline",
"method",
"using",
"input",
"lengths",
"for",
"the",
"length",
"constraints.",
"The",
"proposed",
"noise",
"injection",
"improved",
"robustness",
"for",
"length",
"prediction",
"errors,",
"especially",
"within",
"the",
"window",
"size."
] |
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[
"The",
"ability",
"to",
"reliably",
"perceive",
"the",
"environmental",
"states,",
"particularly",
"the",
"existence",
"of",
"objects",
"and",
"their",
"motion",
"behavior,",
"is",
"crucial",
"for",
"autonomous",
"driving.",
"In",
"this",
"work,",
"we",
"propose",
"an",
"efficient",
"deep",
"model,",
"called",
"MotionNet",
",",
"to",
"jointly",
"perform",
"perception",
"and",
"motion",
"prediction",
"from",
"3D",
"point",
"clouds.",
"MotionNet",
"takes",
"a",
"sequence",
"of",
"LiDAR",
"sweeps",
"as",
"input",
"and",
"outputs",
"a",
"bird's",
"eye",
"view",
"(BEV)",
"map,",
"which",
"encodes",
"the",
"object",
"category",
"and",
"motion",
"information",
"in",
"each",
"grid",
"cell.",
"The",
"backbone",
"of",
"MotionNet",
"is",
"a",
"novel",
"spatio-temporal",
"pyramid",
"network,",
"which",
"extracts",
"deep",
"spatial",
"and",
"temporal",
"features",
"in",
"a",
"hierarchical",
"fashion.",
"To",
"enforce",
"the",
"smoothness",
"of",
"predictions",
"over",
"both",
"space",
"and",
"time,",
"the",
"training",
"of",
"MotionNet",
"is",
"further",
"regularized",
"with",
"novel",
"spatial",
"and",
"temporal",
"consistency",
"losses.",
"Extensive",
"experiments",
"show",
"that",
"the",
"proposed",
"method",
"overall",
"outperforms",
"the",
"state-of-the-arts,",
"including",
"the",
"latest",
"scene-flow-",
"and",
"3D-object-detection-based",
"methods.",
"This",
"indicates",
"the",
"potential",
"value",
"of",
"the",
"proposed",
"method",
"serving",
"as",
"a",
"backup",
"to",
"the",
"bounding-box-based",
"system,",
"and",
"providing",
"complementary",
"information",
"to",
"the",
"motion",
"planner",
"in",
"autonomous",
"driving.",
"Code",
"is",
"available",
"at",
"https://github.com/pxiangwu/MotionNet",
"."
] |
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"We",
"present",
"OpinionDigest,",
"an",
"abstractive",
"opinion",
"summarization",
"framework,",
"which",
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"not",
"rely",
"on",
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"summaries",
"for",
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"The",
"framework",
"uses",
"an",
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"model",
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"shows",
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"our",
"framework",
"outperforms",
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"baselines.",
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"learning",
"threats",
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"data",
"set,",
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"machine",
"learning",
"model's",
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"space,",
"data",
"labels,",
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"different",
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"approaches",
"have",
"recently",
"emerged,",
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"focusing",
"on",
"one",
"attack",
"strategy.",
"The",
"Achilles",
"heel",
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"many",
"of",
"these",
"detection",
"approaches",
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"their",
"dependence",
"on",
"having",
"access",
"to",
"a",
"clean,",
"untampered",
"data",
"set.",
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"this",
"paper,",
"we",
"propose",
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"a",
"Classification",
"Auto-Encoder",
"based",
"detector",
"against",
"diverse",
"poisoned",
"data.",
"CAE",
"can",
"detect",
"all",
"forms",
"of",
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"attacks",
"using",
"a",
"combination",
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"reconstruction",
"and",
"classification",
"errors",
"without",
"having",
"any",
"prior",
"knowledge",
"of",
"the",
"attack",
"strategy.",
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"show",
"that",
"an",
"enhanced",
"version",
"of",
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"does",
"not",
"have",
"to",
"employ",
"a",
"clean",
"data",
"set",
"to",
"train",
"the",
"defense",
"model.",
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"experimental",
"results",
"on",
"three",
"real",
"datasets",
"MNIST,",
"Fashion-MNIST",
"and",
"CIFAR",
"demonstrate",
"that",
"our",
"proposed",
"method",
"can",
"maintain",
"its",
"functionality",
"under",
"up",
"to",
"30%",
"contaminated",
"data",
"and",
"help",
"the",
"defended",
"SVM",
"classifier",
"to",
"regain",
"its",
"best",
"accuracy."
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"We",
"propose",
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"into",
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"learning",
"through",
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"state",
"values",
"and",
"action",
"advantages.",
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"Adversarial",
"Imitation",
"Learning",
"and",
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"from",
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"0,",
"1},",
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"example",
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"copies",
"of",
"the",
"Q-network",
"and",
"expert",
"network,",
"predicting",
"the",
"target",
"values",
"using",
"the",
"same",
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".",
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"the",
"game",
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"the",
"state-of-the-art",
"Q-learning",
"algorithm,",
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"combination",
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"Q-learning.",
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"results",
"showed",
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"Q-learning",
"was",
"indeed",
"useful",
"and",
"more",
"resistant",
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"bias",
"of",
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"The",
"baseline",
"Q-learning",
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"exhibited",
"unstable",
"and",
"suboptimal",
"behavior,",
"especially",
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"playing",
"against",
"a",
"stochastic",
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"demonstrated",
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"performance",
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"Expert",
"Q-learning",
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"examples",
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"gained",
"better",
"results",
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"the",
"baseline",
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"when",
"trained",
"and",
"tested",
"against",
"a",
"fixed",
"player.",
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"the",
"other",
"hand,",
"Expert",
"Q-learning",
"without",
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"cannot",
"win",
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"the",
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"in",
"direct",
"game",
"competitions",
"despite",
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"it",
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"shown",
"the",
"strength",
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"reducing",
"the",
"overestimation",
"bias."
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",",
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"-LRB-",
"MTS",
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"that",
"offers",
"the",
"linguistic",
"flexibility",
"desired",
"for",
"spoken",
"dialogue",
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"message",
"generating",
"systems",
".",
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"use",
"of",
"prosody",
"transplantation",
"and",
"special",
"purpose",
"prosody",
"models",
"results",
"in",
"highly",
"natural",
"prosody",
"for",
"the",
"synthesised",
"speech",
"."
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"This",
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"the",
"Transformer",
"architecture",
"in",
"the",
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"Machine",
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"setting.",
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"on",
"the",
"encoder-decoder",
"attention",
"mechanism,",
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"prove",
"that",
"attention",
"weights",
"systematically",
"make",
"alignment",
"errors",
"by",
"relying",
"mainly",
"on",
"uninformative",
"tokens",
"from",
"the",
"source",
"sequence.",
"However,",
"we",
"observe",
"that",
"NMT",
"models",
"assign",
"attention",
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"these",
"tokens",
"to",
"regulate",
"the",
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"two",
"contexts,",
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"the",
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"provide",
"evidence",
"about",
"the",
"influence",
"of",
"wrong",
"alignments",
"on",
"the",
"model",
"behavior,",
"demonstrating",
"that",
"the",
"encoder-decoder",
"attention",
"mechanism",
"is",
"well",
"suited",
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"an",
"interpretability",
"method",
"for",
"NMT.",
"Finally,",
"based",
"on",
"our",
"analysis,",
"we",
"propose",
"methods",
"that",
"largely",
"reduce",
"the",
"word",
"alignment",
"error",
"rate",
"compared",
"to",
"standard",
"induced",
"alignments",
"from",
"attention",
"weights."
] |
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[
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"quite",
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"user",
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"most",
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"assistants",
"will",
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"message",
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"and",
"send",
"it",
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"Bob,",
"rather",
"than",
"properly",
"converting",
"the",
"message",
"to",
"I\tO\nlove\tO\nyou.",
"We",
"designed",
"a",
"system",
"to",
"allow",
"virtual",
"assistants",
"to",
"take",
"a",
"voice",
"message",
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"user,",
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"of",
"the",
"message,",
"and",
"then",
"deliver",
"the",
"result",
"to",
"its",
"target",
"user.",
"We",
"developed",
"a",
"rule-based",
"model,",
"which",
"integrates",
"a",
"linear",
"text",
"classification",
"model,",
"part-of-speech",
"tagging,",
"and",
"constituency",
"parsing",
"with",
"rule-based",
"transformation",
"methods.",
"We",
"also",
"investigated",
"Neural",
"Machine",
"Translation",
"(NMT)",
"approaches,",
"including",
"LSTMs,",
"CopyNet,",
"and",
"T5",
".",
"We",
"explored",
"5",
"metrics",
"to",
"gauge",
"both",
"naturalness",
"and",
"faithfulness",
"automatically,",
"and",
"we",
"chose",
"to",
"use",
"BLEU",
"plus",
"METEOR",
"for",
"faithfulness",
"and",
"relative",
"perplexity",
"using",
"a",
"separately",
"trained",
"language",
"model",
"(GPT)",
"for",
"naturalness.",
"Transformer-Copynet",
"and",
"T5",
"performed",
"similarly",
"on",
"faithfulness",
"metrics,",
"with",
"T5",
"achieving",
"slight",
"edge,",
"a",
"BLEU",
"score",
"of",
"63.8",
"and",
"a",
"METEOR",
"score",
"of",
"83.0.",
"CopyNet",
"was",
"the",
"most",
"natural,",
"with",
"a",
"relative",
"perplexity",
"of",
"1.59.",
"CopyNet",
"also",
"has",
"37",
"times",
"fewer",
"parameters",
"than",
"T5",
".",
"We",
"have",
"publicly",
"released",
"our",
"dataset,",
"which",
"is",
"composed",
"of",
"46,565",
"crowd-sourced",
"samples."
] |
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[
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"batch",
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"learning",
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"is",
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"fueled",
"by",
"the",
"demand",
"from",
"systems",
"engineers",
"for",
"intelligent",
"control",
"solutions",
"that",
"they",
"can",
"apply",
"within",
"their",
"technical",
"and",
"organizational",
"constraints.",
"Model-based",
"RL",
"(MBRL)",
"suits",
"this",
"scenario",
"well",
"for",
"its",
"sample",
"efficiency",
"and",
"modularity.",
"Recent",
"MBRL",
"techniques",
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"efficient",
"neural",
"system",
"models",
"with",
"classical",
"planning",
"(like",
"model",
"predictive",
"control;",
"MPC).",
"In",
"this",
"paper",
"we",
"add",
"two",
"components",
"to",
"this",
"classical",
"setup.",
"The",
"first",
"is",
"a",
"Dyna-style",
"policy",
"learned",
"on",
"the",
"system",
"model",
"using",
"model-free",
"techniques.",
"We",
"call",
"it",
"the",
"guide",
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"it",
"guides",
"the",
"planner.",
"The",
"second",
"component",
"is",
"the",
"explorer,",
"a",
"strategy",
"to",
"expand",
"the",
"limited",
"knowledge",
"of",
"the",
"guide",
"during",
"planning.",
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"a",
"rigorous",
"ablation",
"study",
"we",
"show",
"that",
"exploration",
"is",
"crucial",
"for",
"optimal",
"performance.",
"We",
"apply",
"this",
"approach",
"with",
"a",
"DQN",
"guide",
"and",
"a",
"heating",
"explorer",
"to",
"improve",
"the",
"state",
"of",
"the",
"art",
"of",
"the",
"resource-limited",
"Acrobot",
"benchmark",
"system",
"by",
"about",
"10%."
] |
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[
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"coronavirus",
"epidemic,",
"almost",
"everyone",
"wears",
"a",
"facial",
"mask,",
"which",
"poses",
"a",
"huge",
"challenge",
"to",
"deep",
"face",
"recognition.",
"In",
"this",
"workshop,",
"we",
"organize",
"Masked",
"Face",
"Recognition",
"(MFR",
")",
"challenge",
"and",
"focus",
"on",
"bench-marking",
"deep",
"face",
"recognition",
"methods",
"under",
"the",
"existence",
"of",
"facial",
"masks.",
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"the",
"MFR",
"challenge,",
"there",
"are",
"two",
"main",
"tracks:",
"the",
"InsightFace",
"track",
"and",
"the",
"WebFace260M",
"track.",
"For",
"the",
"InsightFace",
"track,",
"we",
"manually",
"collect",
"a",
"large-scale",
"masked",
"face",
"test",
"set",
"with",
"7K",
"identities.",
"In",
"addition,",
"we",
"also",
"collect",
"a",
"children",
"test",
"set",
"including",
"14K",
"identities",
"and",
"a",
"multi-racial",
"test",
"set",
"containing",
"242K",
"identities.",
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"using",
"these",
"three",
"test",
"sets,",
"we",
"build",
"up",
"an",
"online",
"model",
"testing",
"system,",
"which",
"can",
"give",
"a",
"comprehensive",
"evaluation",
"of",
"face",
"recognition",
"models.",
"To",
"avoid",
"data",
"privacy",
"problems,",
"no",
"test",
"image",
"is",
"released",
"to",
"the",
"public.",
"As",
"the",
"challenge",
"is",
"still",
"under-going,",
"we",
"will",
"keep",
"on",
"updating",
"the",
"top-ranked",
"solutions",
"as",
"well",
"as",
"this",
"report",
"on",
"the",
"arxiv."
] |
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[
"There",
"have",
"been",
"very",
"few",
"attempts",
"to",
"benchmark",
"performances",
"of",
"state-of-the-art",
"algorithms",
"for",
"Neural",
"Machine",
"Translation",
"task",
"on",
"Indian",
"Languages.",
"Google,",
"Bing,",
"Facebook",
"and",
"Yandex",
"are",
"some",
"of",
"the",
"very",
"few",
"companies",
"which",
"have",
"built",
"translation",
"systems",
"for",
"few",
"of",
"the",
"Indian",
"Languages.",
"Among",
"them,",
"translation",
"results",
"from",
"Google",
"are",
"supposed",
"to",
"be",
"better,",
"based",
"on",
"general",
"inspection.",
"Bing-Translator",
"do",
"not",
"even",
"support",
"Marathi",
"language",
"which",
"has",
"around",
"95",
"million",
"speakers",
"and",
"ranks",
"15th",
"in",
"the",
"world",
"in",
"terms",
"of",
"combined",
"primary",
"and",
"secondary",
"speakers.",
"In",
"this",
"exercise,",
"we",
"trained",
"and",
"compared",
"variety",
"of",
"Neural",
"Machine",
"Marathi",
"to",
"English",
"Translators",
"trained",
"with",
"BERT-tokenizer",
"by",
"huggingface",
"and",
"various",
"Transformer",
"based",
"architectures",
"using",
"Facebook's",
"Fairseq",
"platform",
"with",
"limited",
"but",
"almost",
"correct",
"parallel",
"corpus",
"to",
"achieve",
"better",
"BLEU",
"scores",
"than",
"Google",
"on",
"Tatoeba",
"and",
"Wikimedia",
"open",
"datasets."
] |
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[
"We",
"propose",
"the",
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"Mentions",
"Recall",
"(TMR)",
"metrics",
"to",
"supplement",
"traditional",
"named",
"entity",
"recognition",
"(NER",
")",
"evaluation",
"by",
"examining",
"recall",
"on",
"specific",
"subsets",
"of",
"tough",
"mentions:",
"unseen",
"mentions,",
"those",
"whose",
"tokens",
"or",
"token/type",
"combination",
"were",
"not",
"observed",
"in",
"training,",
"and",
"type-confusable",
"mentions,",
"token",
"sequences",
"with",
"multiple",
"entity",
"types",
"in",
"the",
"test",
"data.",
"We",
"demonstrate",
"the",
"usefulness",
"of",
"these",
"metrics",
"by",
"evaluating",
"corpora",
"of",
"English,",
"Spanish,",
"and",
"Dutch",
"using",
"five",
"recent",
"neural",
"architectures.",
"We",
"identify",
"subtle",
"differences",
"between",
"the",
"performance",
"of",
"BERT",
"and",
"Flair",
"on",
"two",
"English",
"NER",
"corpora",
"and",
"identify",
"a",
"weak",
"spot",
"in",
"the",
"performance",
"of",
"current",
"models",
"in",
"Spanish.",
"We",
"conclude",
"that",
"the",
"TMR",
"metrics",
"enable",
"differentiation",
"between",
"otherwise",
"similar-scoring",
"systems",
"and",
"identification",
"of",
"patterns",
"in",
"performance",
"that",
"would",
"go",
"unnoticed",
"from",
"overall",
"precision,",
"recall,",
"and",
"F1."
] |
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[
"In",
"this",
"paper",
"a",
"new",
"method",
"of",
"image",
"smoothing",
"for",
"satellite",
"imagery",
"and",
"its",
"applications",
"in",
"environmental",
"remote",
"sensing",
"are",
"presented.",
"This",
"method",
"is",
"based",
"on",
"the",
"global",
"gradient",
"minimization",
"over",
"the",
"whole",
"image.",
"With",
"respect",
"to",
"the",
"image",
"discrete",
"identity,",
"the",
"continuous",
"minimization",
"problem",
"is",
"discretized.",
"Using",
"the",
"finite",
"difference",
"numerical",
"method",
"of",
"differentiation,",
"a",
"simple",
"yet",
"efficient",
"5*5-pixel",
"template",
"is",
"derived.",
"Convolution",
"of",
"the",
"derived",
"template",
"with",
"the",
"image",
"in",
"different",
"bands",
"results",
"in",
"the",
"discrimination",
"of",
"various",
"image",
"elements.",
"This",
"method",
"is",
"extremely",
"fast,",
"besides",
"being",
"highly",
"precise.",
"A",
"case",
"study",
"is",
"presented",
"for",
"the",
"northern",
"Iran,",
"covering",
"parts",
"of",
"the",
"Caspian",
"Sea.",
"Comparison",
"of",
"the",
"method",
"with",
"the",
"usual",
"Laplacian",
"template",
"reveals",
"that",
"it",
"is",
"more",
"capable",
"of",
"distinguishing",
"phenomena",
"in",
"the",
"image."
] |
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[
"Brain-Computer",
"Interfaces",
"(BCIs)",
"are",
"systems",
"allowing",
"people",
"to",
"interact",
"with",
"the",
"environment",
"bypassing",
"the",
"natural",
"neuromuscular",
"and",
"hormonal",
"outputs",
"of",
"the",
"peripheral",
"nervous",
"system",
"(PNS).",
"These",
"interfaces",
"record",
"a",
"user's",
"brain",
"activity",
"and",
"translate",
"it",
"into",
"control",
"commands",
"for",
"external",
"devices,",
"thus",
"providing",
"the",
"PNS",
"with",
"additional",
"artificial",
"outputs.",
"In",
"this",
"framework,",
"the",
"BCIs",
"based",
"on",
"the",
"P300",
"Event-Related",
"Potentials",
"(ERP),",
"which",
"represent",
"the",
"electrical",
"responses",
"recorded",
"from",
"the",
"brain",
"after",
"specific",
"events",
"or",
"stimuli,",
"have",
"proven",
"to",
"be",
"particularly",
"successful",
"and",
"robust.",
"The",
"presence",
"or",
"the",
"absence",
"of",
"a",
"P300",
"evoked",
"potential",
"within",
"the",
"EEG",
"features",
"is",
"determined",
"through",
"a",
"classification",
"algorithm.",
"Linear",
"classifiers",
"such",
"as",
"SWLDA",
"and",
"SVM",
"are",
"the",
"most",
"used",
"for",
"ERPs'",
"classification.",
"Due",
"to",
"the",
"low",
"signal-to-noise",
"ratio",
"of",
"the",
"EEG",
"signals,",
"multiple",
"stimulation",
"sequences",
"(a.k.a.",
"iterations)",
"are",
"carried",
"out",
"and",
"then",
"averaged",
"before",
"the",
"signals",
"being",
"classified.",
"However,",
"while",
"augmenting",
"the",
"number",
"of",
"iterations",
"improves",
"the",
"Signal-to-Noise",
"Ratio",
"(SNR),",
"it",
"also",
"slows",
"down",
"the",
"process.",
"In",
"the",
"early",
"studies,",
"the",
"number",
"of",
"iterations",
"was",
"fixed",
"(no",
"stopping),",
"but",
"recently,",
"several",
"early",
"stopping",
"strategies",
"have",
"been",
"proposed",
"in",
"the",
"literature",
"to",
"dynamically",
"interrupt",
"the",
"stimulation",
"sequence",
"when",
"a",
"certain",
"criterion",
"is",
"met",
"to",
"enhance",
"the",
"communication",
"rate.",
"In",
"this",
"work,",
"we",
"explore",
"how",
"to",
"improve",
"the",
"classification",
"performances",
"in",
"P300",
"based",
"BCIs",
"by",
"combining",
"optimization",
"and",
"machine",
"learning.",
"First,",
"we",
"propose",
"a",
"new",
"decision",
"function",
"that",
"aims",
"at",
"improving",
"classification",
"performances",
"in",
"terms",
"of",
"accuracy",
"and",
"Information",
"Transfer",
"Rate",
"both",
"in",
"a",
"no",
"stopping",
"and",
"early",
"stopping",
"environment.",
"Then,",
"we",
"propose",
"a",
"new",
"SVM",
"training",
"problem",
"that",
"aims",
"to",
"facilitate",
"the",
"target-detection",
"process.",
"Our",
"approach",
"proves",
"to",
"be",
"effective",
"on",
"several",
"publicly",
"available",
"datasets."
] |
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[
"Object",
"detection",
"in",
"Ultra",
"High-Resolution",
"(UHR)",
"images",
"has",
"long",
"been",
"a",
"challenging",
"problem",
"in",
"computer",
"vision",
"due",
"to",
"the",
"varying",
"scales",
"of",
"the",
"targeted",
"objects.",
"When",
"it",
"comes",
"to",
"barcode",
"detection,",
"resizing",
"UHR",
"input",
"images",
"to",
"smaller",
"sizes",
"often",
"leads",
"to",
"the",
"loss",
"of",
"pertinent",
"information,",
"while",
"processing",
"them",
"directly",
"is",
"highly",
"inefficient",
"and",
"computationally",
"expensive.",
"In",
"this",
"paper,",
"we",
"propose",
"using",
"semantic",
"segmentation",
"to",
"achieve",
"a",
"fast",
"and",
"accurate",
"detection",
"of",
"barcodes",
"of",
"various",
"scales",
"in",
"UHR",
"images.",
"Our",
"pipeline",
"involves",
"a",
"modified",
"Region",
"Proposal",
"Network",
"(RPN)",
"on",
"images",
"of",
"size",
"greater",
"than",
"10k$\\times$10k",
"and",
"a",
"newly",
"proposed",
"Y-Net",
"segmentation",
"network,",
"followed",
"by",
"a",
"post-processing",
"workflow",
"for",
"fitting",
"a",
"bounding",
"box",
"around",
"each",
"segmented",
"barcode",
"mask.",
"The",
"end-to-end",
"system",
"has",
"a",
"latency",
"of",
"16",
"milliseconds,",
"which",
"is",
"$2.5\\times$",
"faster",
"than",
"YOLOv4",
"and",
"$5.9\\times$",
"faster",
"than",
"Mask",
"R-CNN",
".",
"In",
"terms",
"of",
"accuracy,",
"our",
"method",
"outperforms",
"YOLOv4",
"and",
"Mask",
"R-CNN",
"by",
"a",
"$mAP$",
"of",
"5.50%",
"and",
"47.10%",
"respectively,",
"on",
"a",
"synthetic",
"dataset.",
"We",
"have",
"made",
"available",
"the",
"generated",
"synthetic",
"barcode",
"dataset",
"and",
"its",
"code",
"at",
"http://www.github.com/viplabB/SBD/."
] |
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[
"Differentiable",
"architecture",
"search",
"(DARTS",
")",
"marks",
"a",
"milestone",
"in",
"Neural",
"Architecture",
"Search",
"(NAS),",
"boasting",
"simplicity",
"and",
"small",
"search",
"costs.",
"However,",
"DARTS",
"still",
"suffers",
"from",
"frequent",
"performance",
"collapse,",
"which",
"happens",
"when",
"some",
"operations,",
"such",
"as",
"skip",
"connections,",
"zeroes",
"and",
"poolings,",
"dominate",
"the",
"architecture.",
"In",
"this",
"paper,",
"we",
"are",
"the",
"first",
"to",
"point",
"out",
"that",
"the",
"phenomenon",
"is",
"attributed",
"to",
"bi-level",
"optimization.",
"We",
"propose",
"Single-DARTS",
"which",
"merely",
"uses",
"single-level",
"optimization,",
"updating",
"network",
"weights",
"and",
"architecture",
"parameters",
"simultaneously",
"with",
"the",
"same",
"data",
"batch.",
"Even",
"single-level",
"optimization",
"has",
"been",
"previously",
"attempted,",
"no",
"literature",
"provides",
"a",
"systematic",
"explanation",
"on",
"this",
"essential",
"point.",
"Replacing",
"the",
"bi-level",
"optimization,",
"Single-DARTS",
"obviously",
"alleviates",
"performance",
"collapse",
"as",
"well",
"as",
"enhances",
"the",
"stability",
"of",
"architecture",
"search.",
"Experiment",
"results",
"show",
"that",
"Single-DARTS",
"achieves",
"state-of-the-art",
"performance",
"on",
"mainstream",
"search",
"spaces.",
"For",
"instance,",
"on",
"NAS-Benchmark-201,",
"the",
"searched",
"architectures",
"are",
"nearly",
"optimal",
"ones.",
"We",
"also",
"validate",
"that",
"the",
"single-level",
"optimization",
"framework",
"is",
"much",
"more",
"stable",
"than",
"the",
"bi-level",
"one.",
"We",
"hope",
"that",
"this",
"simple",
"yet",
"effective",
"method",
"will",
"give",
"some",
"insights",
"on",
"differential",
"architecture",
"search.",
"The",
"code",
"is",
"available",
"at",
"https://github.com/PencilAndBike/Single-DARTS",
".git."
] |
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[
"Natural",
"Language",
"Interfaces",
"to",
"Databases",
"-LRB-",
"NLIs",
"-RRB-",
"can",
"benefit",
"from",
"the",
"advances",
"in",
"statistical",
"parsing",
"over",
"the",
"last",
"fifteen",
"years",
"or",
"so",
".",
"However",
",",
"statistical",
"parsers",
"require",
"training",
"on",
"a",
"massive",
",",
"labeled",
"corpus",
",",
"and",
"manually",
"creating",
"such",
"a",
"corpus",
"for",
"each",
"database",
"is",
"prohibitively",
"expensive",
".",
"To",
"address",
"this",
"quandary",
",",
"this",
"paper",
"reports",
"on",
"the",
"PRECISE",
"NLI",
",",
"which",
"uses",
"a",
"statistical",
"parser",
"as",
"a",
"``",
"plug",
"in",
"''",
".",
"The",
"paper",
"shows",
"how",
"a",
"strong",
"semantic",
"model",
"coupled",
"with",
"``light",
"re-training",
"''",
"enables",
"PRECISE",
"to",
"overcome",
"parser",
"errors",
",",
"and",
"correctly",
"map",
"from",
"parsed",
"questions",
"to",
"the",
"corresponding",
"SQL",
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"domains,",
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"end,",
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"this",
"end,",
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"propose",
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"--",
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"framework",
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"assess",
"the",
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"clustering",
"and",
"show",
"that",
"SCCL",
"significantly",
"advances",
"the",
"state-of-the-art",
"results",
"on",
"most",
"benchmark",
"datasets",
"with",
"3%-11%",
"improvement",
"on",
"Accuracy",
"and",
"4%-15%",
"improvement",
"on",
"Normalized",
"Mutual",
"Information.",
"Furthermore,",
"our",
"quantitative",
"analysis",
"demonstrates",
"the",
"effectiveness",
"of",
"SCCL",
"in",
"leveraging",
"the",
"strengths",
"of",
"both",
"bottom-up",
"instance",
"discrimination",
"and",
"top-down",
"clustering",
"to",
"achieve",
"better",
"intra-cluster",
"and",
"inter-cluster",
"distances",
"when",
"evaluated",
"with",
"the",
"ground",
"truth",
"cluster",
"labels."
] |
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[
"Multispectral",
"person",
"detection",
"aims",
"at",
"automatically",
"localizing",
"humans",
"in",
"images",
"that",
"consist",
"of",
"multiple",
"spectral",
"bands.",
"Usually,",
"the",
"visual-optical",
"(VIS)",
"and",
"the",
"thermal",
"infrared",
"(IR)",
"spectra",
"are",
"combined",
"to",
"achieve",
"higher",
"robustness",
"for",
"person",
"detection",
"especially",
"in",
"insufficiently",
"illuminated",
"scenes.",
"This",
"paper",
"focuses",
"on",
"analyzing",
"existing",
"detection",
"approaches",
"for",
"their",
"generalization",
"ability.",
"Generalization",
"is",
"a",
"key",
"feature",
"for",
"machine",
"learning",
"based",
"detection",
"algorithms",
"that",
"are",
"supposed",
"to",
"perform",
"well",
"across",
"different",
"datasets.",
"Inspired",
"by",
"recent",
"literature",
"regarding",
"person",
"detection",
"in",
"the",
"VIS",
"spectrum,",
"we",
"perform",
"a",
"cross-validation",
"study",
"to",
"empirically",
"determine",
"the",
"most",
"promising",
"dataset",
"to",
"train",
"a",
"well-generalizing",
"detector.",
"Therefore,",
"we",
"pick",
"one",
"reference",
"Deep",
"Convolutional",
"Neural",
"Network",
"(DCNN)",
"architecture",
"and",
"three",
"different",
"multispectral",
"datasets.",
"The",
"Region",
"Proposal",
"Network",
"(RPN",
")",
"originally",
"introduced",
"for",
"object",
"detection",
"within",
"the",
"popular",
"Faster",
"R-CNN",
"is",
"chosen",
"as",
"a",
"reference",
"DCNN.",
"The",
"reason",
"is",
"that",
"a",
"stand-alone",
"RPN",
"is",
"able",
"to",
"serve",
"as",
"a",
"competitive",
"detector",
"for",
"two-class",
"problems",
"such",
"as",
"person",
"detection.",
"Furthermore,",
"current",
"state-of-the-art",
"approaches",
"initially",
"apply",
"an",
"RPN",
"followed",
"by",
"individual",
"classifiers.",
"The",
"three",
"considered",
"datasets",
"are",
"the",
"KAIST",
"Multispectral",
"Pedestrian",
"Benchmark",
"including",
"recently",
"published",
"improved",
"annotations",
"for",
"training",
"and",
"testing,",
"the",
"Tokyo",
"Multi-spectral",
"Semantic",
"Segmentation",
"dataset,",
"and",
"the",
"OSU",
"Color-Thermal",
"dataset",
"including",
"recently",
"released",
"annotations.",
"The",
"experimental",
"results",
"show",
"that",
"the",
"KAIST",
"Multispectral",
"Pedestrian",
"Benchmark",
"with",
"its",
"improved",
"annotations",
"provides",
"the",
"best",
"basis",
"to",
"train",
"a",
"DCNN",
"with",
"good",
"generalization",
"ability",
"compared",
"to",
"the",
"other",
"two",
"multispectral",
"datasets.",
"On",
"average,",
"this",
"detection",
"model",
"achieves",
"a",
"log-average",
"Miss",
"Rate",
"(MR)",
"of",
"29.74",
"%",
"evaluated",
"on",
"the",
"reasonable",
"test",
"subsets",
"of",
"the",
"three",
"datasets."
] |
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[
"With",
"recent",
"advances",
"in",
"network",
"architectures",
"for",
"Neural",
"Machine",
"Translation",
"(NMT)",
"recurrent",
"models",
"have",
"effectively",
"been",
"replaced",
"by",
"either",
"convolutional",
"or",
"self-attentional",
"approaches,",
"such",
"as",
"in",
"the",
"Transformer",
".",
"While",
"the",
"main",
"innovation",
"of",
"the",
"Transformer",
"architecture",
"is",
"its",
"use",
"of",
"self-attentional",
"layers,",
"there",
"are",
"several",
"other",
"aspects,",
"such",
"as",
"attention",
"with",
"multiple",
"heads",
"and",
"the",
"use",
"of",
"many",
"attention",
"layers,",
"that",
"distinguish",
"the",
"model",
"from",
"previous",
"baselines.",
"In",
"this",
"work",
"we",
"take",
"a",
"fine-grained",
"look",
"at",
"the",
"different",
"architectures",
"for",
"NMT.",
"We",
"introduce",
"an",
"Architecture",
"Definition",
"Language",
"(ADL)",
"allowing",
"for",
"a",
"flexible",
"combination",
"of",
"common",
"building",
"blocks.",
"Making",
"use",
"of",
"this",
"language",
"we",
"show",
"in",
"experiments",
"that",
"one",
"can",
"bring",
"recurrent",
"and",
"convolutional",
"models",
"very",
"close",
"to",
"the",
"Transformer",
"performance",
"by",
"borrowing",
"concepts",
"from",
"the",
"Transformer",
"architecture,",
"but",
"not",
"using",
"self-attention.",
"Additionally,",
"we",
"find",
"that",
"self-attention",
"is",
"much",
"more",
"important",
"on",
"the",
"encoder",
"side",
"than",
"on",
"the",
"decoder",
"side,",
"where",
"it",
"can",
"be",
"replaced",
"by",
"a",
"RNN",
"or",
"CNN",
"without",
"a",
"loss",
"in",
"performance",
"in",
"most",
"settings.",
"Surprisingly,",
"even",
"a",
"model",
"without",
"any",
"target",
"side",
"self-attention",
"performs",
"well."
] |
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[
"The",
"compression",
"of",
"deep",
"learning",
"models",
"is",
"of",
"fundamental",
"importance",
"in",
"deploying",
"such",
"models",
"to",
"edge",
"devices.",
"Incorporating",
"hardware",
"model",
"and",
"application",
"constraints",
"during",
"compression",
"maximizes",
"the",
"benefits",
"but",
"makes",
"it",
"specifically",
"designed",
"for",
"one",
"case.",
"Therefore,",
"the",
"compression",
"needs",
"to",
"be",
"automated.",
"Searching",
"for",
"the",
"optimal",
"compression",
"method",
"parameters",
"is",
"considered",
"an",
"optimization",
"problem.",
"This",
"article",
"introduces",
"a",
"Multi-Objective",
"Hardware-Aware",
"Quantization",
"(MOHAQ)",
"method,",
"which",
"considers",
"both",
"hardware",
"efficiency",
"and",
"inference",
"error",
"as",
"objectives",
"for",
"mixed-precision",
"quantization.",
"The",
"proposed",
"method",
"makes",
"the",
"evaluation",
"of",
"candidate",
"solutions",
"in",
"a",
"large",
"search",
"space",
"feasible",
"by",
"relying",
"on",
"two",
"steps.",
"First,",
"post-training",
"quantization",
"is",
"applied",
"for",
"fast",
"solution",
"evaluation.",
"Second,",
"we",
"propose",
"a",
"search",
"technique",
"named",
"beacon-based\tO\nsearch",
"to",
"retrain",
"selected",
"solutions",
"only",
"in",
"the",
"search",
"space",
"and",
"use",
"them",
"as",
"beacons",
"to",
"know",
"the",
"effect",
"of",
"retraining",
"on",
"other",
"solutions.",
"To",
"evaluate",
"the",
"optimization",
"potential,",
"we",
"chose",
"a",
"speech",
"recognition",
"model",
"using",
"the",
"TIMIT",
"dataset.",
"The",
"model",
"is",
"based",
"on",
"Simple",
"Recurrent",
"Unit",
"(SRU",
")",
"due",
"to",
"its",
"considerable",
"speedup",
"over",
"other",
"recurrent",
"units.",
"We",
"applied",
"our",
"method",
"to",
"run",
"on",
"two",
"platforms:",
"SiLago",
"and",
"Bitfusion.",
"Experimental",
"evaluations",
"showed",
"that",
"SRU",
"can",
"be",
"compressed",
"up",
"to",
"8x",
"by",
"post-training",
"quantization",
"without",
"any",
"significant",
"increase",
"in",
"the",
"error",
"and",
"up",
"to",
"12x",
"with",
"only",
"a",
"1.5",
"percentage",
"point",
"increase",
"in",
"error.",
"On",
"SiLago,",
"the",
"inference-only",
"search",
"found",
"solutions",
"that",
"achieve",
"80\\%",
"and",
"64\\%",
"of",
"the",
"maximum",
"possible",
"speedup",
"and",
"energy",
"saving,",
"respectively,",
"with",
"a",
"0.5",
"percentage",
"point",
"increase",
"in",
"the",
"error.",
"On",
"Bitfusion,",
"with",
"a",
"constraint",
"of",
"a",
"small",
"SRAM",
"size,",
"beacon-based",
"search",
"reduced",
"the",
"error",
"gain",
"of",
"inference-only",
"search",
"by",
"4",
"percentage",
"points",
"and",
"increased",
"the",
"possible",
"reached",
"speedup",
"to",
"be",
"47x",
"compared",
"to",
"the",
"Bitfusion",
"baseline."
] |
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[
"Graph",
"Convolution",
"Network",
"(GCN)",
"has",
"become",
"new",
"state-of-the-art",
"for",
"collaborative",
"filtering.",
"Nevertheless,",
"the",
"reasons",
"of",
"its",
"effectiveness",
"for",
"recommendation",
"are",
"not",
"well",
"understood.",
"Existing",
"work",
"that",
"adapts",
"GCN",
"to",
"recommendation",
"lacks",
"thorough",
"ablation",
"analyses",
"on",
"GCN,",
"which",
"is",
"originally",
"designed",
"for",
"graph",
"classification",
"tasks",
"and",
"equipped",
"with",
"many",
"neural",
"network",
"operations.",
"However,",
"we",
"empirically",
"find",
"that",
"the",
"two",
"most",
"common",
"designs",
"in",
"GCNs",
"--",
"feature",
"transformation",
"and",
"nonlinear",
"activation",
"--",
"contribute",
"little",
"to",
"the",
"performance",
"of",
"collaborative",
"filtering.",
"Even",
"worse,",
"including",
"them",
"adds",
"to",
"the",
"difficulty",
"of",
"training",
"and",
"degrades",
"recommendation",
"performance.",
"In",
"this",
"work,",
"we",
"aim",
"to",
"simplify",
"the",
"design",
"of",
"GCN",
"to",
"make",
"it",
"more",
"concise",
"and",
"appropriate",
"for",
"recommendation.",
"We",
"propose",
"a",
"new",
"model",
"named",
"LightGCN",
",",
"including",
"only",
"the",
"most",
"essential",
"component",
"in",
"GCN",
"--",
"neighborhood",
"aggregation",
"--",
"for",
"collaborative",
"filtering.",
"Specifically,",
"LightGCN",
"learns",
"user",
"and",
"item",
"embeddings",
"by",
"linearly",
"propagating",
"them",
"on",
"the",
"user-item",
"interaction",
"graph,",
"and",
"uses",
"the",
"weighted",
"sum",
"of",
"the",
"embeddings",
"learned",
"at",
"all",
"layers",
"as",
"the",
"final",
"embedding.",
"Such",
"simple,",
"linear,",
"and",
"neat",
"model",
"is",
"much",
"easier",
"to",
"implement",
"and",
"train,",
"exhibiting",
"substantial",
"improvements",
"(about",
"16.0\\%",
"relative",
"improvement",
"on",
"average)",
"over",
"Neural",
"Graph",
"Collaborative",
"Filtering",
"(NGCF)",
"--",
"a",
"state-of-the-art",
"GCN-based",
"recommender",
"model",
"--",
"under",
"exactly",
"the",
"same",
"experimental",
"setting.",
"Further",
"analyses",
"are",
"provided",
"towards",
"the",
"rationality",
"of",
"the",
"simple",
"LightGCN",
"from",
"both",
"analytical",
"and",
"empirical",
"perspectives."
] |
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[
"Depthwise",
"convolution",
"is",
"becoming",
"increasingly",
"popular",
"in",
"modern",
"efficient",
"ConvNets,",
"but",
"its",
"kernel",
"size",
"is",
"often",
"overlooked.",
"In",
"this",
"paper,",
"we",
"systematically",
"study",
"the",
"impact",
"of",
"different",
"kernel",
"sizes,",
"and",
"observe",
"that",
"combining",
"the",
"benefits",
"of",
"multiple",
"kernel",
"sizes",
"can",
"lead",
"to",
"better",
"accuracy",
"and",
"efficiency.",
"Based",
"on",
"this",
"observation,",
"we",
"propose",
"a",
"new",
"mixed",
"depthwise",
"convolution",
"(MixConv",
"),",
"which",
"naturally",
"mixes",
"up",
"multiple",
"kernel",
"sizes",
"in",
"a",
"single",
"convolution.",
"As",
"a",
"simple",
"drop-in",
"replacement",
"of",
"vanilla",
"depthwise",
"convolution,",
"our",
"MixConv",
"improves",
"the",
"accuracy",
"and",
"efficiency",
"for",
"existing",
"MobileNets",
"on",
"both",
"ImageNet",
"classification",
"and",
"COCO",
"object",
"detection.",
"To",
"demonstrate",
"the",
"effectiveness",
"of",
"MixConv",
",",
"we",
"integrate",
"it",
"into",
"AutoML",
"search",
"space",
"and",
"develop",
"a",
"new",
"family",
"of",
"models,",
"named",
"as",
"MixNets,",
"which",
"outperform",
"previous",
"mobile",
"models",
"including",
"MobileNetV2",
"[20]",
"(ImageNet",
"top-1",
"accuracy",
"+4.2%),",
"ShuffleNetV2",
"[16]",
"(+3.5%),",
"MnasNet",
"[26]",
"(+1.3%),",
"ProxylessNAS",
"[2]",
"(+2.2%),",
"and",
"FBNet",
"[27]",
"(+2.0%).",
"In",
"particular,",
"our",
"MixNet-L",
"achieves",
"a",
"new",
"state-of-the-art",
"78.90%",
"ImageNet",
"top-1",
"accuracy",
"under",
"typical",
"mobile",
"settings",
"(<600M",
"FLOPS).",
"Code",
"is",
"at",
"https://github.com/",
"tensorflow/tpu/tree/master/models/official/mnasnet/mixnet"
] |
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[
"The",
"structure",
"of",
"a",
"discourse",
"is",
"reflected",
"in",
"many",
"aspects",
"of",
"its",
"linguistic",
"realization",
",",
"including",
"its",
"lexical",
",",
"prosodic",
",",
"syntactic",
",",
"and",
"semantic",
"nature",
".",
"Multiparty",
"dialog",
"contains",
"a",
"particular",
"kind",
"of",
"discourse",
"structure",
",",
"the",
"dialog",
"act",
"-LRB-",
"DA",
"-RRB-",
".",
"Like",
"other",
"types",
"of",
"structure",
",",
"the",
"dialog",
"act",
"sequence",
"of",
"a",
"conversation",
"is",
"also",
"reflected",
"in",
"its",
"lexical",
",",
"prosodic",
",",
"and",
"syntactic",
"realization",
".",
"This",
"paper",
"presents",
"a",
"preliminary",
"investigation",
"into",
"the",
"realization",
"of",
"a",
"particular",
"class",
"of",
"dialog",
"acts",
"which",
"play",
"an",
"essential",
"structuring",
"role",
"in",
"dialog",
",",
"the",
"backchannels",
"or",
"acknowledgements",
"tokens",
".",
"We",
"discuss",
"the",
"lexical",
",",
"prosodic",
",",
"and",
"syntactic",
"realization",
"of",
"these",
"and",
"subsumed",
"or",
"related",
"dialog",
"acts",
"like",
"continuers",
",",
"assessments",
",",
"yesanswers",
",",
"agreements",
",",
"and",
"incipient-speakership",
".",
"We",
"show",
"that",
"lexical",
"knowledge",
"plays",
"a",
"role",
"in",
"distinguishing",
"these",
"dialog",
"acts",
",",
"despite",
"the",
"widespread",
"ambiguity",
"of",
"words",
"such",
"as",
"yeah",
",",
"and",
"that",
"prosodic",
"knowledge",
"plays",
"a",
"role",
"in",
"DA",
"identification",
"for",
"certain",
"DA",
"types",
",",
"while",
"lexical",
"cues",
"may",
"be",
"sufficient",
"for",
"the",
"remainder",
".",
"Finally",
",",
"our",
"investigation",
"of",
"the",
"syntax",
"of",
"assessments",
"suggests",
"that",
"at",
"least",
"some",
"dialog",
"acts",
"have",
"a",
"very",
"constrained",
"syntactic",
"realization",
",",
"a",
"per-dialog",
"act",
"`",
"microsyntax",
"'",
"."
] |
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[
"This",
"work",
"presents",
"an",
"exploration",
"and",
"imitation-learning-based",
"agent",
"capable",
"of",
"state-of-the-art",
"performance",
"in",
"playing",
"text-based",
"computer",
"games.",
"Text-based",
"computer",
"games",
"describe",
"their",
"world",
"to",
"the",
"player",
"through",
"natural",
"language",
"and",
"expect",
"the",
"player",
"to",
"interact",
"with",
"the",
"game",
"using",
"text.",
"These",
"games",
"are",
"of",
"interest",
"as",
"they",
"can",
"be",
"seen",
"as",
"a",
"testbed",
"for",
"language",
"understanding,",
"problem-solving,",
"and",
"language",
"generation",
"by",
"artificial",
"agents.",
"Moreover,",
"they",
"provide",
"a",
"learning",
"environment",
"in",
"which",
"these",
"skills",
"can",
"be",
"acquired",
"through",
"interactions",
"with",
"an",
"environment",
"rather",
"than",
"using",
"fixed",
"corpora.",
"One",
"aspect",
"that",
"makes",
"these",
"games",
"particularly",
"challenging",
"for",
"learning",
"agents",
"is",
"the",
"combinatorially",
"large",
"action",
"space.",
"Existing",
"methods",
"for",
"solving",
"text-based",
"games",
"are",
"limited",
"to",
"games",
"that",
"are",
"either",
"very",
"simple",
"or",
"have",
"an",
"action",
"space",
"restricted",
"to",
"a",
"predetermined",
"set",
"of",
"admissible",
"actions.",
"In",
"this",
"work,",
"we",
"propose",
"to",
"use",
"the",
"exploration",
"approach",
"of",
"Go-Explore",
"for",
"solving",
"text-based",
"games",
".",
"More",
"specifically,",
"in",
"an",
"initial",
"exploration",
"phase,",
"we",
"first",
"extract",
"trajectories",
"with",
"high",
"rewards,",
"after",
"which",
"we",
"train",
"a",
"policy",
"to",
"solve",
"the",
"game",
"by",
"imitating",
"these",
"trajectories.",
"Our",
"experiments",
"show",
"that",
"this",
"approach",
"outperforms",
"existing",
"solutions",
"in",
"solving",
"text-based",
"games",
",",
"and",
"it",
"is",
"more",
"sample",
"efficient",
"in",
"terms",
"of",
"the",
"number",
"of",
"interactions",
"with",
"the",
"environment.",
"Moreover,",
"we",
"show",
"that",
"the",
"learned",
"policy",
"can",
"generalize",
"better",
"than",
"existing",
"solutions",
"to",
"unseen",
"games",
"without",
"using",
"any",
"restriction",
"on",
"the",
"action",
"space."
] |
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[
"Recently,",
"some",
"Neural",
"Architecture",
"Search",
"(NAS)",
"techniques",
"are",
"proposed",
"for",
"the",
"automatic",
"design",
"of",
"Graph",
"Convolutional",
"Network",
"(GCN",
")",
"architectures.",
"They",
"bring",
"great",
"convenience",
"to",
"the",
"use",
"of",
"GCN",
",",
"but",
"could",
"hardly",
"apply",
"to",
"the",
"Federated",
"Learning",
"(FL)",
"scenarios",
"with",
"distributed",
"and",
"private",
"datasets,",
"which",
"limit",
"their",
"applications.",
"Moreover,",
"they",
"need",
"to",
"train",
"many",
"candidate",
"GCN",
"models",
"from",
"scratch,",
"which",
"is",
"inefficient",
"for",
"FL.",
"To",
"address",
"these",
"challenges,",
"we",
"propose",
"FL-AGCN",
"S,",
"an",
"efficient",
"GCN",
"NAS",
"algorithm",
"suitable",
"for",
"FL",
"scenarios.",
"FL-AGCN",
"S",
"designs",
"a",
"federated",
"evolutionary",
"optimization",
"strategy",
"to",
"enable",
"distributed",
"agents",
"to",
"cooperatively",
"design",
"powerful",
"GCN",
"models",
"while",
"keeping",
"personal",
"information",
"on",
"local",
"devices.",
"Besides,",
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"GCN",
"SuperNet",
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"a",
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"results",
"show",
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"FL-AGCN",
"S",
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"GCN",
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"FL",
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"surpassing",
"the",
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"NAS",
"methods",
"and",
"GCN",
"models."
] |
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[
"Named",
"entity",
"recognition",
"(NER",
")",
"has",
"been",
"studied",
"extensively",
"and",
"the",
"earlier",
"algorithms",
"were",
"based",
"on",
"sequence",
"labeling",
"like",
"Hidden",
"Markov",
"Models",
"(HMM)",
"and",
"conditional",
"random",
"fields",
"(CRF).",
"These",
"were",
"followed",
"by",
"neural",
"network",
"based",
"deep",
"learning",
"models.",
"Recently,",
"BERT",
"has",
"shown",
"new",
"state",
"of",
"the",
"art",
"accuracy",
"in",
"sequence",
"labeling",
"tasks",
"like",
"NER",
".",
"In",
"this",
"short",
"article,",
"we",
"study",
"various",
"approaches",
"to",
"task",
"specific",
"NER",
".",
"Task",
"specific",
"NER",
"has",
"two",
"components",
"-",
"identifying",
"the",
"intent",
"of",
"a",
"piece",
"of",
"text",
"(like",
"search",
"queries),",
"and",
"then",
"labeling",
"the",
"query",
"with",
"task",
"specific",
"named",
"entities.",
"For",
"example,",
"we",
"consider",
"the",
"task",
"of",
"labeling",
"Target",
"store",
"locations",
"in",
"a",
"search",
"query",
"(which",
"could",
"be",
"entered",
"in",
"a",
"search",
"box",
"or",
"spoken",
"in",
"a",
"device",
"like",
"Alexa",
"or",
"Google",
"Home).",
"Store",
"locations",
"are",
"highly",
"ambiguous",
"and",
"sometimes",
"it",
"is",
"difficult",
"to",
"differentiate",
"between",
"say",
"a",
"location",
"and",
"a",
"non-location.",
"For",
"example,",
"pickup\tO\nmy\tO\norder\tO\nat\tO\norange\tO\nstore",
"has",
"orange",
"as",
"the",
"store",
"location,",
"while",
"buy\tO\norange\tO\nat\tO\ntarget",
"has",
"orange",
"as",
"a",
"fruit.",
"We",
"explore",
"this",
"difficulty",
"by",
"doing",
"multi-task",
"learning",
"which",
"we",
"call",
"global",
"to",
"local",
"transfer",
"of",
"information.",
"We",
"jointly",
"learn",
"the",
"query",
"intent",
"(i.e.",
"store",
"lookup)",
"and",
"the",
"named",
"entities",
"by",
"using",
"multiple",
"loss",
"functions",
"in",
"our",
"BERT",
"based",
"model",
"and",
"find",
"interesting",
"results."
] |
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[
"Prediction",
"of",
"the",
"real-time",
"multiplayer",
"online",
"battle",
"arena",
"(MOBA)",
"games'",
"match",
"outcome",
"is",
"one",
"of",
"the",
"most",
"important",
"and",
"exciting",
"tasks",
"in",
"Esports",
"analytical",
"research.",
"This",
"research",
"paper",
"predominantly",
"focuses",
"on",
"building",
"predictive",
"machine",
"and",
"deep",
"learning",
"models",
"to",
"identify",
"the",
"outcome",
"of",
"the",
"Dota",
"2",
"MOBA",
"game",
"using",
"the",
"new",
"method",
"of",
"multi-forward",
"steps",
"predictions.",
"Three",
"models",
"were",
"investigated",
"and",
"compared:",
"Linear",
"Regression",
"(LR),",
"Neural",
"Networks",
"(NN),",
"and",
"a",
"type",
"of",
"recurrent",
"neural",
"network",
"Long",
"Short-Term",
"Memory",
"(LSTM",
").",
"In",
"order",
"to",
"achieve",
"the",
"goals,",
"we",
"developed",
"a",
"data",
"collecting",
"python",
"server",
"using",
"Game",
"State",
"Integration",
"(GSI)",
"to",
"track",
"the",
"real-time",
"data",
"of",
"the",
"players.",
"Once",
"the",
"exploratory",
"feature",
"analysis",
"and",
"tuning",
"hyper-parameters",
"were",
"done,",
"our",
"models'",
"experiments",
"took",
"place",
"on",
"different",
"players",
"with",
"dissimilar",
"backgrounds",
"of",
"playing",
"experiences.",
"The",
"achieved",
"accuracy",
"scores",
"depend",
"on",
"the",
"multi-forward",
"prediction",
"parameters,",
"which",
"for",
"the",
"worse",
"case",
"in",
"linear",
"regression",
"69\\%",
"but",
"on",
"average",
"82\\%,",
"while",
"in",
"the",
"deep",
"learning",
"models",
"hit",
"the",
"utmost",
"accuracy",
"of",
"prediction",
"on",
"average",
"88\\%",
"for",
"NN,",
"and",
"93\\%",
"for",
"LSTM",
"models."
] |
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[
"Significant",
"advances",
"have",
"been",
"made",
"in",
"recent",
"years",
"on",
"Natural",
"Language",
"Processing",
"with",
"machines",
"surpassing",
"human",
"performance",
"in",
"many",
"tasks,",
"including",
"but",
"not",
"limited",
"to",
"Question",
"Answering",
".",
"The",
"majority",
"of",
"deep",
"learning",
"methods",
"for",
"Question",
"Answering",
"targets",
"domains",
"with",
"large",
"datasets",
"and",
"highly",
"matured",
"literature.",
"The",
"area",
"of",
"Nuclear",
"and",
"Atomic",
"energy",
"has",
"largely",
"remained",
"unexplored",
"in",
"exploiting",
"non-annotated",
"data",
"for",
"driving",
"industry",
"viable",
"applications.",
"Due",
"to",
"lack",
"of",
"dataset,",
"a",
"new",
"dataset",
"was",
"created",
"from",
"the",
"7000",
"research",
"papers",
"on",
"nuclear",
"domain.",
"This",
"paper",
"contributes",
"to",
"research",
"in",
"understanding",
"nuclear",
"domain",
"knowledge",
"which",
"is",
"then",
"evaluated",
"on",
"Nuclear",
"Question",
"Answering",
"Dataset",
"(NQuAD)",
"created",
"by",
"nuclear",
"domain",
"experts",
"as",
"part",
"of",
"this",
"research.",
"NQuAD",
"contains",
"612",
"questions",
"developed",
"on",
"181",
"paragraphs",
"randomly",
"selected",
"from",
"the",
"IGCAR",
"research",
"paper",
"corpus.",
"In",
"this",
"paper,",
"the",
"Nuclear",
"Bidirectional",
"Encoder",
"Representational",
"Transformers",
"(NukeBERT",
")",
"is",
"proposed,",
"which",
"incorporates",
"a",
"novel",
"technique",
"for",
"building",
"BERT",
"vocabulary",
"to",
"make",
"it",
"suitable",
"for",
"tasks",
"with",
"less",
"training",
"data.",
"The",
"experiments",
"evaluated",
"on",
"NQuAD",
"revealed",
"that",
"NukeBERT",
"was",
"able",
"to",
"outperform",
"BERT",
"significantly,",
"thus",
"validating",
"the",
"adopted",
"methodology.",
"Training",
"NukeBERT",
"is",
"computationally",
"expensive",
"and",
"hence",
"we",
"will",
"be",
"open-sourcing",
"the",
"NukeBERT",
"pretrained",
"weights",
"and",
"NQuAD",
"for",
"fostering",
"further",
"research",
"work",
"in",
"the",
"nuclear",
"domain."
] |
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[
"Optical",
"Character",
"Recognition",
"and",
"extraction",
"is",
"a",
"key",
"tool",
"in",
"the",
"automatic",
"evaluation",
"of",
"documents",
"in",
"a",
"financial",
"context.",
"However,",
"the",
"image",
"data",
"provided",
"to",
"automated",
"systems",
"can",
"have",
"unreliable",
"quality,",
"and",
"can",
"be",
"inherently",
"low-resolution",
"or",
"downsampled",
"and",
"compressed",
"by",
"a",
"transmitting",
"program.",
"In",
"this",
"paper,",
"we",
"illustrate",
"the",
"efficacy",
"of",
"a",
"Gaussian",
"Process",
"upsampling",
"model",
"for",
"the",
"purposes",
"of",
"improving",
"OCR",
"and",
"extraction",
"through",
"upsampling",
"low",
"resolution",
"documents."
] |
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[
"Semantic",
"Segmentation",
"is",
"an",
"important",
"module",
"for",
"autonomous",
"robots",
"such",
"as",
"self-driving",
"cars.",
"The",
"advantage",
"of",
"video",
"segmentation",
"approaches",
"compared",
"to",
"single",
"image",
"segmentation",
"is",
"that",
"temporal",
"image",
"information",
"is",
"considered,",
"and",
"their",
"performance",
"increases",
"due",
"to",
"this.",
"Hence,",
"single",
"image",
"segmentation",
"approaches",
"are",
"extended",
"by",
"recurrent",
"units",
"such",
"as",
"convolutional",
"LSTM",
"(convLSTM",
")",
"cells,",
"which",
"are",
"placed",
"at",
"suitable",
"positions",
"in",
"the",
"basic",
"network",
"architecture.",
"However,",
"a",
"major",
"critique",
"of",
"video",
"segmentation",
"approaches",
"based",
"on",
"recurrent",
"neural",
"networks",
"is",
"their",
"large",
"parameter",
"count",
"and",
"their",
"computational",
"complexity,",
"and",
"so,",
"their",
"inference",
"time",
"of",
"one",
"video",
"frame",
"takes",
"up",
"to",
"66",
"percent",
"longer",
"than",
"their",
"basic",
"version.",
"Inspired",
"by",
"the",
"success",
"of",
"the",
"spatial",
"and",
"depthwise",
"separable",
"convolutional",
"neural",
"networks,",
"we",
"generalize",
"these",
"techniques",
"for",
"convLSTM",
"s",
"in",
"this",
"work,",
"so",
"that",
"the",
"number",
"of",
"parameters",
"and",
"the",
"required",
"FLOPs",
"are",
"reduced",
"significantly.",
"Experiments",
"on",
"different",
"datasets",
"show",
"that",
"the",
"segmentation",
"approaches",
"using",
"the",
"proposed,",
"modified",
"convLSTM",
"cells",
"achieve",
"similar",
"or",
"slightly",
"worse",
"accuracy,",
"but",
"are",
"up",
"to",
"15",
"percent",
"faster",
"on",
"a",
"GPU",
"than",
"the",
"ones",
"using",
"the",
"standard",
"convLSTM",
"cells.",
"Furthermore,",
"a",
"new",
"evaluation",
"metric",
"is",
"introduced,",
"which",
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"pixels",
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"video",
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[
"Aspect",
"Sentiment",
"Triplet",
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"opinion",
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"aspect,",
"its",
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"sentiment,",
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"corresponding",
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"term/span",
"explaining",
"the",
"rationale",
"behind",
"the",
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"Existing",
"research",
"efforts",
"are",
"majorly",
"tagging-based.",
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"the",
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"taking",
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"sequence",
"tagging",
"approach,",
"some",
"fail",
"to",
"capture",
"the",
"strong",
"interdependence",
"between",
"the",
"three",
"opinion",
"factors,",
"whereas",
"others",
"fall",
"short",
"of",
"identifying",
"triplets",
"with",
"overlapping",
"aspect/opinion",
"spans.",
"A",
"recent",
"grid",
"tagging",
"approach",
"on",
"the",
"other",
"hand",
"fails",
"to",
"capture",
"the",
"span-level",
"semantics",
"while",
"predicting",
"the",
"sentiment",
"between",
"an",
"aspect-opinion",
"pair.",
"Different",
"from",
"these,",
"we",
"present",
"a",
"tagging-free",
"solution",
"for",
"the",
"task,",
"while",
"addressing",
"the",
"limitations",
"of",
"the",
"existing",
"works.",
"We",
"adapt",
"an",
"encoder-decoder",
"architecture",
"with",
"a",
"Pointer",
"Network-based",
"decoding",
"framework",
"that",
"generates",
"an",
"entire",
"opinion",
"triplet",
"at",
"each",
"time",
"step",
"thereby",
"making",
"our",
"solution",
"end-to-end.",
"Interactions",
"between",
"the",
"aspects",
"and",
"opinions",
"are",
"effectively",
"captured",
"by",
"the",
"decoder",
"by",
"considering",
"their",
"entire",
"detected",
"spans",
"while",
"predicting",
"their",
"connecting",
"sentiment.",
"Extensive",
"experiments",
"on",
"several",
"benchmark",
"datasets",
"establish",
"the",
"better",
"efficacy",
"of",
"our",
"proposed",
"approach,",
"especially",
"in",
"the",
"recall,",
"and",
"in",
"predicting",
"multiple",
"and",
"aspect/opinion-overlapped",
"triplets",
"from",
"the",
"same",
"review",
"sentence.",
"We",
"report",
"our",
"results",
"both",
"with",
"and",
"without",
"BERT",
"and",
"also",
"demonstrate",
"the",
"utility",
"of",
"domain-specific",
"BERT",
"post-training",
"for",
"the",
"task."
] |
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[
"Recent",
"advances",
"in",
"Natural",
"Language",
"Processing",
"(NLP),",
"and",
"specifically",
"automated",
"Question",
"Answering",
"(QA)",
"systems,",
"have",
"demonstrated",
"both",
"impressive",
"linguistic",
"fluency",
"and",
"a",
"pernicious",
"tendency",
"to",
"reflect",
"social",
"biases.",
"In",
"this",
"study,",
"we",
"introduce",
"Q-Pain,",
"a",
"dataset",
"for",
"assessing",
"bias",
"in",
"medical",
"QA",
"in",
"the",
"context",
"of",
"pain",
"management,",
"one",
"of",
"the",
"most",
"challenging",
"forms",
"of",
"clinical",
"decision-making.",
"Along",
"with",
"the",
"dataset,",
"we",
"propose",
"a",
"new,",
"rigorous",
"framework,",
"including",
"a",
"sample",
"experimental",
"design,",
"to",
"measure",
"the",
"potential",
"biases",
"present",
"when",
"making",
"treatment",
"decisions.",
"We",
"demonstrate",
"its",
"use",
"by",
"assessing",
"two",
"reference",
"Question-Answering",
"systems,",
"GPT-2",
"and",
"GPT-3,",
"and",
"find",
"statistically",
"significant",
"differences",
"in",
"treatment",
"between",
"intersectional",
"race-gender",
"subgroups,",
"thus",
"reaffirming",
"the",
"risks",
"posed",
"by",
"AI",
"in",
"medical",
"settings,",
"and",
"the",
"need",
"for",
"datasets",
"like",
"ours",
"to",
"ensure",
"safety",
"before",
"medical",
"AI",
"applications",
"are",
"deployed."
] |
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[
"The",
"development",
"of",
"quantum",
"computational",
"techniques",
"has",
"advanced",
"greatly",
"in",
"recent",
"years,",
"parallel",
"to",
"the",
"advancements",
"in",
"techniques",
"for",
"deep",
"reinforcement",
"learning.",
"This",
"work",
"explores",
"the",
"potential",
"for",
"quantum",
"computing",
"to",
"facilitate",
"reinforcement",
"learning",
"problems.",
"Quantum",
"computing",
"approaches",
"offer",
"important",
"potential",
"improvements",
"in",
"time",
"and",
"space",
"complexity",
"over",
"traditional",
"algorithms",
"because",
"of",
"its",
"ability",
"to",
"exploit",
"the",
"quantum",
"phenomena",
"of",
"superposition",
"and",
"entanglement.",
"Specifically,",
"we",
"investigate",
"the",
"use",
"of",
"quantum",
"variational",
"circuits,",
"a",
"form",
"of",
"quantum",
"machine",
"learning.",
"We",
"present",
"our",
"techniques",
"for",
"encoding",
"classical",
"data",
"for",
"a",
"quantum",
"variational",
"circuit,",
"we",
"further",
"explore",
"pure",
"and",
"hybrid",
"quantum",
"algorithms",
"for",
"DQN",
"and",
"Double",
"DQN",
".",
"Our",
"results",
"indicate",
"both",
"hybrid",
"and",
"pure",
"quantum",
"variational",
"circuit",
"have",
"the",
"ability",
"to",
"solve",
"reinforcement",
"learning",
"tasks",
"with",
"a",
"smaller",
"parameter",
"space.",
"These",
"comparison",
"are",
"conducted",
"with",
"two",
"OpenAI",
"Gym",
"environments:",
"CartPole",
"and",
"Blackjack,",
"The",
"success",
"of",
"this",
"work",
"is",
"indicative",
"of",
"a",
"strong",
"future",
"relationship",
"between",
"quantum",
"machine",
"learning",
"and",
"deep",
"reinforcement",
"learning."
] |
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"paper",
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"an",
"unsupervised",
"word",
"sense",
"learning",
"algorithm",
",",
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"senses",
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"''",
"number",
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"clusters",
"based",
"on",
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".",
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"words",
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"feature",
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",",
"feature",
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"cluster",
"number",
".",
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"results",
"show",
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"our",
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"subset",
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"estimate",
"model",
"order",
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"number",
"-RRB-",
"and",
"achieve",
"better",
"performance",
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"algorithm",
"which",
"requires",
"cluster",
"number",
"to",
"be",
"provided",
"."
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"Neural",
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"is",
"an",
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"yet",
"challenging",
"task",
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"network",
"design",
"due",
"to",
"its",
"high",
"computational",
"consumption.",
"To",
"address",
"this",
"issue,",
"we",
"propose",
"the",
"Reinforced",
"Evolutionary",
"Neural",
"Architecture",
"Search",
"(RENAS),",
"which",
"is",
"an",
"evolutionary",
"method",
"with",
"reinforced",
"mutation",
"for",
"NAS.",
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"method",
"integrates",
"reinforced",
"mutation",
"into",
"an",
"evolution",
"algorithm",
"for",
"neural",
"architecture",
"exploration,",
"in",
"which",
"a",
"mutation",
"controller",
"is",
"introduced",
"to",
"learn",
"the",
"effects",
"of",
"slight",
"modifications",
"and",
"make",
"mutation",
"actions.",
"The",
"reinforced",
"mutation",
"controller",
"guides",
"the",
"model",
"population",
"to",
"evolve",
"efficiently.",
"Furthermore,",
"as",
"child",
"models",
"can",
"inherit",
"parameters",
"from",
"their",
"parents",
"during",
"evolution,",
"our",
"method",
"requires",
"very",
"limited",
"computational",
"resources.",
"In",
"experiments,",
"we",
"conduct",
"the",
"proposed",
"search",
"method",
"on",
"CIFAR-10",
"and",
"obtain",
"a",
"powerful",
"network",
"architecture,",
"RENASNet.",
"This",
"architecture",
"achieves",
"a",
"competitive",
"result",
"on",
"CIFAR-10.",
"The",
"explored",
"network",
"architecture",
"is",
"transferable",
"to",
"ImageNet",
"and",
"achieves",
"a",
"new",
"state-of-the-art",
"accuracy,",
"i.e.,",
"75.70%",
"top-1",
"accuracy",
"with",
"5.36M",
"parameters",
"on",
"mobile",
"ImageNet.",
"We",
"further",
"test",
"its",
"performance",
"on",
"semantic",
"segmentation",
"with",
"DeepLabv3",
"on",
"the",
"PASCAL",
"VOC.",
"RENASNet",
"outperforms",
"MobileNet-v1,",
"MobileNet-v2",
"and",
"NASNet.",
"It",
"achieves",
"75.83%",
"mIOU",
"without",
"being",
"pretrained",
"on",
"COCO."
] |
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[
"Recent",
"work",
"has",
"shown",
"evidence",
"that",
"the",
"knowledge",
"acquired",
"by",
"multilingual",
"BERT",
"(mBERT",
")",
"has",
"two",
"components:",
"a",
"language-specific",
"and",
"a",
"language-neutral",
"one.",
"This",
"paper",
"analyses",
"the",
"relationship",
"between",
"them,",
"in",
"the",
"context",
"of",
"fine-tuning",
"on",
"two",
"tasks",
"--",
"POS",
"tagging",
"and",
"natural",
"language",
"inference",
"--",
"which",
"require",
"the",
"model",
"to",
"bring",
"to",
"bear",
"different",
"degrees",
"of",
"language-specific",
"knowledge.",
"Visualisations",
"reveal",
"that",
"mBERT",
"loses",
"the",
"ability",
"to",
"cluster",
"representations",
"by",
"language",
"after",
"fine-tuning,",
"a",
"result",
"that",
"is",
"supported",
"by",
"evidence",
"from",
"language",
"identification",
"experiments.",
"However,",
"further",
"experiments",
"on",
"'unlearning'",
"language-specific",
"representations",
"using",
"gradient",
"reversal",
"and",
"iterative",
"adversarial",
"learning",
"are",
"shown",
"not",
"to",
"add",
"further",
"improvement",
"to",
"the",
"language-independent",
"component",
"over",
"and",
"above",
"the",
"effect",
"of",
"fine-tuning.",
"The",
"results",
"presented",
"here",
"suggest",
"that",
"the",
"process",
"of",
"fine-tuning",
"causes",
"a",
"reorganisation",
"of",
"the",
"model's",
"limited",
"representational",
"capacity,",
"enhancing",
"language-independent",
"representations",
"at",
"the",
"expense",
"of",
"language-specific",
"ones."
] |
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[
"Definition",
"Extraction",
"is",
"the",
"task",
"to",
"automatically",
"extract",
"terms",
"and",
"their",
"definitions",
"from",
"text.",
"In",
"recent",
"years,",
"it",
"attracts",
"wide",
"interest",
"from",
"NLP",
"researchers.",
"This",
"paper",
"describes",
"the",
"unixlong",
"team{'}s",
"system",
"for",
"the",
"SemEval",
"2020",
"task6:",
"DeftEval:",
"Extracting",
"term-definition",
"pairs",
"in",
"free",
"text.",
"The",
"goal",
"of",
"this",
"task",
"is",
"to",
"extract",
"definition,",
"word",
"level",
"BIO",
"tags",
"and",
"relations.",
"This",
"task",
"is",
"challenging",
"due",
"to",
"the",
"free",
"style",
"of",
"the",
"text,",
"especially",
"the",
"definitions",
"of",
"the",
"terms",
"range",
"across",
"several",
"sentences",
"and",
"lack",
"explicit",
"verb",
"phrases.",
"We",
"propose",
"a",
"joint",
"model",
"to",
"train",
"the",
"tasks",
"of",
"definition",
"extraction",
"and",
"the",
"word",
"level",
"BIO",
"tagging",
"simultaneously.",
"We",
"design",
"a",
"creative",
"format",
"input",
"of",
"BERT",
"to",
"capture",
"the",
"location",
"information",
"between",
"entity",
"and",
"its",
"definition.",
"Then",
"we",
"adjust",
"the",
"result",
"of",
"BERT",
"with",
"some",
"rules.",
"Finally,",
"we",
"apply",
"TAG{\\_}ID,",
"ROOT{\\_}ID,",
"BIO",
"tag",
"to",
"predict",
"the",
"relation",
"and",
"achieve",
"macro-averaged",
"F1",
"score",
"1",
"which",
"rank",
"first",
"on",
"the",
"official",
"test",
"set",
"in",
"the",
"relation",
"extraction",
"subtask."
] |
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[
"In",
"this",
"paper,",
"we",
"present",
"FoodChem,",
"a",
"new",
"Relation",
"Extraction",
"(RE)",
"model",
"for",
"identifying",
"chemicals",
"present",
"in",
"the",
"composition",
"of",
"food",
"entities,",
"based",
"on",
"textual",
"information",
"provided",
"in",
"biomedical",
"peer-reviewed",
"scientific",
"literature.",
"The",
"RE",
"task",
"is",
"treated",
"as",
"a",
"binary",
"classification",
"problem,",
"aimed",
"at",
"identifying",
"whether",
"the",
"contains",
"relation",
"exists",
"between",
"a",
"food-chemical",
"entity",
"pair.",
"This",
"is",
"accomplished",
"by",
"fine-tuning",
"BERT,",
"BioBERT",
"and",
"RoBERTa",
"transformer",
"models.",
"For",
"evaluation",
"purposes,",
"a",
"novel",
"dataset",
"with",
"annotated",
"contains",
"relations",
"in",
"food-chemical",
"entity",
"pairs",
"is",
"generated,",
"in",
"a",
"golden",
"and",
"silver",
"version.",
"The",
"models",
"are",
"integrated",
"into",
"a",
"voting",
"scheme",
"in",
"order",
"to",
"produce",
"the",
"silver",
"version",
"of",
"the",
"dataset",
"which",
"we",
"use",
"for",
"augmenting",
"the",
"individual",
"models,",
"while",
"the",
"manually",
"annotated",
"golden",
"version",
"is",
"used",
"for",
"their",
"evaluation.",
"Out",
"of",
"the",
"three",
"evaluated",
"models,",
"the",
"BioBERT",
"model",
"achieves",
"the",
"best",
"results,",
"with",
"a",
"macro",
"averaged",
"F1",
"score",
"of",
"0.902",
"in",
"the",
"unbalanced",
"augmentation",
"setting."
] |
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[
"TorchBeast",
"is",
"a",
"platform",
"for",
"reinforcement",
"learning",
"(RL)",
"research",
"in",
"PyTorch.",
"It",
"implements",
"a",
"version",
"of",
"the",
"popular",
"IMPALA",
"algorithm",
"for",
"fast,",
"asynchronous,",
"parallel",
"training",
"of",
"RL",
"agents.",
"Additionally,",
"TorchBeast",
"has",
"simplicity",
"as",
"an",
"explicit",
"design",
"goal:",
"We",
"provide",
"both",
"a",
"pure-Python",
"implementation",
"(\"MonoBeast\")",
"as",
"well",
"as",
"a",
"multi-machine",
"high-performance",
"version",
"(\"PolyBeast\").",
"In",
"the",
"latter,",
"parts",
"of",
"the",
"implementation",
"are",
"written",
"in",
"C++,",
"but",
"all",
"parts",
"pertaining",
"to",
"machine",
"learning",
"are",
"kept",
"in",
"simple",
"Python",
"using",
"PyTorch,",
"with",
"the",
"environments",
"provided",
"using",
"the",
"OpenAI",
"Gym",
"interface.",
"This",
"enables",
"researchers",
"to",
"conduct",
"scalable",
"RL",
"research",
"using",
"TorchBeast",
"without",
"any",
"programming",
"knowledge",
"beyond",
"Python",
"and",
"PyTorch.",
"In",
"this",
"paper,",
"we",
"describe",
"the",
"TorchBeast",
"design",
"principles",
"and",
"implementation",
"and",
"demonstrate",
"that",
"it",
"performs",
"on-par",
"with",
"IMPALA",
"on",
"Atari.",
"TorchBeast",
"is",
"released",
"as",
"an",
"open-source",
"package",
"under",
"the",
"Apache",
"2",
"license",
"and",
"is",
"available",
"at",
"\\url{https://github.com/facebookresearch/torchbeast}."
] |
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[
"The",
"increment",
"of",
"toxic",
"comments",
"on",
"online",
"space",
"is",
"causing",
"tremendous",
"effects",
"on",
"other",
"vulnerable",
"users.",
"For",
"this",
"reason,",
"considerable",
"efforts",
"are",
"made",
"to",
"deal",
"with",
"this,",
"and",
"SemEval-2021",
"Task",
"05:00",
"Toxic",
"Spans",
"Detection",
"is",
"one",
"of",
"those.",
"This",
"task",
"asks",
"competitors",
"to",
"extract",
"spans",
"that",
"have",
"toxicity",
"from",
"the",
"given",
"texts,",
"and",
"we",
"have",
"done",
"several",
"analyses",
"to",
"understand",
"its",
"structure",
"before",
"doing",
"experiments.",
"We",
"solve",
"this",
"task",
"by",
"two",
"approaches,",
"Named",
"Entity",
"Recognition",
"with",
"spaCy",
"library",
"and",
"Question-Answering",
"with",
"RoBERTa",
"combining",
"with",
"ToxicBERT,",
"and",
"the",
"former",
"gains",
"the",
"highest",
"F1-score",
"of",
"66.99%."
] |
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[
"We",
"present",
"a",
"novel",
"Dynamic",
"Differentiable",
"Reasoning",
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"framework",
"forjointly",
"learning",
"branching",
"programs",
"and",
"the",
"functions",
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"them;",
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"nondifferentiability",
"inhibiting",
"recent",
"dynamicarchitectures.",
"We",
"apply",
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"framework",
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"settings",
"in",
"two",
"highly",
"compact",
"anddata",
"efficient",
"architectures:",
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"for",
"CLEVR",
"Visual",
"Question",
"Answering",
"andDDRstack",
"for",
"reverse",
"Polish",
"notation",
"expression",
"evaluation.",
"DDRprog",
"uses",
"arecurrent",
"controller",
"to",
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"and",
"execute",
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"neural",
"programsthat",
"directly",
"correspond",
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"the",
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"logic;",
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"explicitly",
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"to",
"handle",
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"By",
"effectively",
"leveraging",
"additionalstructural",
"supervision,",
"we",
"achieve",
"a",
"large",
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"previous",
"approachesin",
"subtask",
"consistency",
"and",
"a",
"small",
"improvement",
"in",
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"accuracy.",
"We",
"furtherdemonstrate",
"the",
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"RPN",
"setting:",
"theinclusion",
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"stack",
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"to",
"generalizeto",
"long",
"expressions",
"where",
"an",
"LSTM",
"fails",
"the",
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"object",
"detection",
"and",
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"estimation",
"in",
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"driving",
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"point",
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"show",
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"images,",
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"the",
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"regularization",
"principle,",
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"label",
"variants",
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"label",
"errors,",
"showing",
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"performance",
"improvements.",
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"conduct",
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"on",
"a",
"conversational",
"speech",
"data",
"set",
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"manually",
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"using",
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"labels",
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"labeled",
"data).",
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"the",
"result,",
"the",
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"Student",
"algorithm",
"with",
"soft",
"labels",
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"consistency",
"regularization",
"achieves",
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"word",
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"rate",
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"adding",
"475h",
"of",
"unlabeled",
"data,",
"corresponding",
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"recovery",
"rate",
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"92%.",
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"adding",
"950h",
"more",
"unlabeled",
"data,",
"our",
"best",
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"performance",
"is",
"within",
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"increase",
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"to",
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"training",
"set",
"(recovery",
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"framework",
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"Dirichlet",
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"-",
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"Today,",
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"news",
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"tools",
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"us",
"to",
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"and",
"prevent",
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"spread",
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"about",
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"urgently.",
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[
"Image",
"Compression",
"has",
"become",
"an",
"absolute",
"necessity",
"in",
"today's",
"day",
"and",
"age.",
"With",
"the",
"advent",
"of",
"the",
"Internet",
"era,",
"compressing",
"files",
"to",
"share",
"among",
"other",
"users",
"is",
"quintessential.",
"Several",
"efforts",
"have",
"been",
"made",
"to",
"reduce",
"file",
"sizes",
"while",
"still",
"maintain",
"image",
"quality",
"in",
"order",
"to",
"transmit",
"files",
"even",
"on",
"limited",
"bandwidth",
"connections.",
"This",
"paper",
"discusses",
"the",
"need",
"for",
"Discrete",
"Cosine",
"Transform",
"or",
"DCT",
"in",
"the",
"compression",
"of",
"images",
"in",
"Joint",
"Photographic",
"Experts",
"Group",
"or",
"JPEG",
"file",
"format.",
"Via",
"an",
"intensive",
"literature",
"study,",
"this",
"paper",
"first",
"introduces",
"DCT",
"and",
"JPEG",
"Compression.",
"The",
"section",
"preceding",
"it",
"discusses",
"how",
"JPEG",
"compression",
"is",
"implemented",
"by",
"DCT.",
"The",
"last",
"section",
"concludes",
"with",
"further",
"real",
"world",
"applications",
"of",
"DCT",
"in",
"image",
"processing."
] |
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[
"Supervised",
"models",
"trained",
"to",
"predict",
"properties",
"from",
"representations",
"have",
"been",
"achieving",
"high",
"accuracy",
"on",
"a",
"variety",
"of",
"tasks.",
"For",
"instance,",
"the",
"BERT",
"family",
"seems",
"to",
"work",
"exceptionally",
"well",
"on",
"the",
"downstream",
"task",
"from",
"NER",
"tagging",
"to",
"the",
"range",
"of",
"other",
"linguistic",
"tasks.",
"But",
"the",
"vocabulary",
"used",
"in",
"the",
"medical",
"field",
"contains",
"a",
"lot",
"of",
"different",
"tokens",
"used",
"only",
"in",
"the",
"medical",
"industry",
"such",
"as",
"the",
"name",
"of",
"different",
"diseases,",
"devices,",
"organisms,",
"medicines,",
"etc.",
"that",
"makes",
"it",
"difficult",
"for",
"traditional",
"BERT",
"model",
"to",
"create",
"contextualized",
"embedding.",
"In",
"this",
"paper,",
"we",
"are",
"going",
"to",
"illustrate",
"the",
"System",
"for",
"Named",
"Entity",
"Tagging",
"based",
"on",
"Bio-Bert.",
"Experimental",
"results",
"show",
"that",
"our",
"model",
"gives",
"substantial",
"improvements",
"over",
"the",
"baseline",
"and",
"stood",
"the",
"fourth",
"runner",
"up",
"in",
"terms",
"of",
"F1",
"score,",
"and",
"first",
"runner",
"up",
"in",
"terms",
"of",
"Recall",
"with",
"just",
"2.21",
"F1",
"score",
"behind",
"the",
"best",
"one."
] |
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[
"Named",
"Entity",
"Recognition",
"(NER",
")",
"is",
"one",
"of",
"the",
"most",
"common",
"tasks",
"of",
"the",
"naturallanguage",
"processing.",
"The",
"purpose",
"of",
"NER",
"is",
"to",
"find",
"and",
"classify",
"tokens",
"in",
"textdocuments",
"into",
"predefined",
"categories",
"called",
"tags,",
"such",
"as",
"person",
"names,quantity",
"expressions,",
"percentage",
"expressions,",
"names",
"of",
"locations,organizations,",
"as",
"well",
"as",
"expression",
"of",
"time,",
"currency",
"and",
"others.",
"Althoughthere",
"is",
"a",
"number",
"of",
"approaches",
"have",
"been",
"proposed",
"for",
"this",
"task",
"in",
"Russianlanguage,",
"it",
"still",
"has",
"a",
"substantial",
"potential",
"for",
"the",
"better",
"solutions.",
"Inthis",
"work,",
"we",
"studied",
"several",
"deep",
"neural",
"network",
"models",
"starting",
"from",
"vanillaBi-directional",
"Long",
"Short-Term",
"Memory",
"(Bi-LSTM)",
"then",
"supplementing",
"it",
"withConditional",
"Random",
"Fields",
"(CRF",
")",
"as",
"well",
"as",
"highway",
"networks",
"and",
"finally",
"addingexternal",
"word",
"embeddings.",
"All",
"models",
"were",
"evaluated",
"across",
"three",
"datasets:Gareev's",
"dataset,",
"Person-1000,",
"FactRuEval-2016.",
"We",
"found",
"that",
"extension",
"ofBi-LSTM",
"model",
"with",
"CRF",
"significantly",
"increased",
"the",
"quality",
"of",
"predictions.Encoding",
"input",
"tokens",
"with",
"external",
"word",
"embeddings",
"reduced",
"training",
"time",
"andallowed",
"to",
"achieve",
"state",
"of",
"the",
"art",
"for",
"the",
"Russian",
"NER",
"task."
] |
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[
"Recently,",
"significant",
"progresses",
"have",
"been",
"made",
"in",
"object",
"detection",
"on",
"common",
"benchmarks",
"(i.e.,",
"Pascal",
"VOC).",
"However,",
"object",
"detection",
"in",
"real",
"world",
"is",
"still",
"challenging",
"due",
"to",
"the",
"serious",
"data",
"imbalance.",
"Images",
"in",
"real",
"world",
"are",
"dominated",
"by",
"easy",
"samples",
"like",
"the",
"wide",
"range",
"of",
"background",
"and",
"some",
"easily",
"recognizable",
"objects,",
"for",
"example.",
"Although",
"two-stage",
"detectors",
"like",
"Faster",
"R-CNN",
"achieved",
"big",
"successes",
"in",
"object",
"detection",
"due",
"to",
"the",
"strategy",
"of",
"extracting",
"region",
"proposals",
"by",
"region",
"proposal",
"network,",
"they",
"show",
"their",
"poor",
"adaption",
"in",
"real-world",
"object",
"detection",
"as",
"a",
"result",
"of",
"without",
"considering",
"mining",
"hard",
"samples",
"during",
"extracting",
"region",
"proposals.",
"To",
"address",
"this",
"issue,",
"we",
"propose",
"a",
"Cascade",
"framework",
"of",
"Region",
"Proposal",
"Networks,",
"referred",
"to",
"as",
"C-RPNs.",
"The",
"essence",
"of",
"C-RPNs",
"is",
"adopting",
"multiple",
"stages",
"to",
"mine",
"hard",
"samples",
"while",
"extracting",
"region",
"proposals",
"and",
"learn",
"stronger",
"classifiers.",
"Meanwhile,",
"a",
"feature",
"chain",
"and",
"a",
"score",
"chain",
"are",
"proposed",
"to",
"help",
"learning",
"more",
"discriminative",
"representations",
"for",
"proposals.",
"Moreover,",
"a",
"loss",
"function",
"of",
"cascade",
"stages",
"is",
"designed",
"to",
"train",
"cascade",
"classifiers",
"through",
"backpropagation.",
"Our",
"proposed",
"method",
"has",
"been",
"evaluated",
"on",
"Pascal",
"VOC",
"and",
"several",
"challenging",
"datasets",
"like",
"BSBDV",
"2017,",
"CityPersons,",
"etc.",
"Our",
"method",
"achieves",
"competitive",
"results",
"compared",
"with",
"the",
"current",
"state-of-the-arts",
"and",
"all-sided",
"improvements",
"in",
"error",
"analysis,",
"validating",
"its",
"efficacy",
"for",
"detection",
"in",
"real",
"world."
] |
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[
"Quantization",
"based",
"model",
"compression",
"serves",
"as",
"high",
"performing",
"and",
"fast",
"approach",
"for",
"inference",
"that",
"yields",
"models",
"which",
"are",
"highly",
"compressed",
"when",
"compared",
"to",
"their",
"full-precision",
"floating",
"point",
"counterparts.",
"The",
"most",
"extreme",
"quantization",
"is",
"a",
"1-bit",
"representation",
"of",
"parameters",
"such",
"that",
"they",
"have",
"only",
"two",
"possible",
"values,",
"typically",
"-1(0)",
"or",
"+1,",
"enabling",
"efficient",
"implementation",
"of",
"the",
"ubiquitous",
"dot",
"product",
"using",
"only",
"additions.",
"The",
"main",
"contribution",
"of",
"this",
"work",
"is",
"the",
"introduction",
"of",
"a",
"method",
"to",
"smooth",
"the",
"combinatorial",
"problem",
"of",
"determining",
"a",
"binary",
"vector",
"of",
"weights",
"to",
"minimize",
"the",
"expected",
"loss",
"for",
"a",
"given",
"objective",
"by",
"means",
"of",
"empirical",
"risk",
"minimization",
"with",
"backpropagation.",
"This",
"is",
"achieved",
"by",
"approximating",
"a",
"multivariate",
"binary",
"state",
"over",
"the",
"weights",
"utilizing",
"a",
"deterministic",
"and",
"differentiable",
"transformation",
"of",
"real-valued,",
"continuous",
"parameters.",
"The",
"proposed",
"method",
"adds",
"little",
"overhead",
"in",
"training,",
"can",
"be",
"readily",
"applied",
"without",
"any",
"substantial",
"modifications",
"to",
"the",
"original",
"architecture,",
"does",
"not",
"introduce",
"additional",
"saturating",
"nonlinearities",
"or",
"auxiliary",
"losses,",
"and",
"does",
"not",
"prohibit",
"applying",
"other",
"methods",
"for",
"binarizing",
"the",
"activations.",
"Contrary",
"to",
"common",
"assertions",
"made",
"in",
"the",
"literature,",
"it",
"is",
"demonstrated",
"that",
"binary",
"weighted",
"networks",
"can",
"train",
"well",
"with",
"the",
"same",
"standard",
"optimization",
"techniques",
"and",
"similar",
"hyperparameter",
"settings",
"as",
"their",
"full-precision",
"counterparts,",
"specifically",
"momentum",
"SGD",
"with",
"large",
"learning",
"rates",
"and",
"$L_2$",
"regularization.",
"To",
"conclude",
"experiments",
"demonstrate",
"the",
"method",
"performs",
"remarkably",
"well",
"across",
"a",
"number",
"of",
"inductive",
"image",
"classification",
"tasks",
"with",
"various",
"architectures",
"compared",
"to",
"their",
"full-precision",
"counterparts.",
"The",
"source",
"code",
"is",
"publicly",
"available",
"at",
"https://bitbucket.org/YanivShu/binary_weighted_networks_public."
] |
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"We",
"propose",
"Disentanglement",
"based",
"Active",
"Learning",
"(DAL),",
"a",
"new",
"active",
"learning",
"technique",
"based",
"on",
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"which",
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"the",
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"Instead",
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"requesting",
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"human",
"oracle,",
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"budget",
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"Adversarial",
"Net",
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"approaches.",
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"Nets",
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"labels",
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"Results",
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"classification",
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"demonstrate",
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"segmentation",
"of",
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"lesions",
"is",
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"towardsthe",
"creation",
"of",
"computer",
"aided",
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"support",
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"approaches",
"depend",
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"and",
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"of",
"the",
"user.",
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"aredifficult",
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"within",
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"Recently,",
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"to",
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"have",
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"Therefore,",
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"is",
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"to",
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"morediscriminative",
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"for",
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"In",
"this",
"study,",
"weovercome",
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"using",
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"residual",
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")",
"to",
"segmentliver",
"lesions.",
"ResNet",
"contain",
"skip",
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"accuracy",
"invery",
"deep",
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"more",
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"through",
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"novel",
"cascaded",
"ResNet",
"architecture",
"withmulti-scale",
"fusion",
"to",
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"learn",
"and",
"infer",
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"theliver",
"and",
"the",
"liver",
"lesions.",
"Our",
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"method",
"achieved",
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"Liver",
"Tumor",
"Segmentation",
"Challenge",
"by",
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"The",
"Aduio-visual",
"Speech",
"Recognition",
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"employs",
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"the",
"video",
"andaudio",
"information",
"to",
"do",
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"Speech",
"Recognition",
"(ASR)",
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"one",
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"of",
"multimodal",
"leaning",
"making",
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"robust",
"and",
"accuracy.The",
"traditional",
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"usually",
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"inference",
"or",
"projection",
"butstrict",
"prior",
"limits",
"its",
"ability.",
"As",
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"learning,",
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"NeuralNetworks",
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"image",
"classification,",
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"language",
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"models",
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"Autoencoders",
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"Deep",
"Belief",
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"Boltzmann",
"Machine(MDBM)",
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"-1",
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"fusion",
"andtemporal",
"fusion,",
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"end-to-end,",
"the",
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"and",
"testing",
"getting",
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"Wepropose",
"a",
"DNN",
"model,",
"Auxiliary",
"Multimodal",
"LSTM",
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"),",
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"am-LSTM",
"could",
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"trained",
"and",
"tested",
"once,",
"moreover",
"easy",
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"The",
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"arealso",
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"is",
"much",
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"and",
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"Efficient",
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",",
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"language",
"model",
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"MT",
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".",
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"beam-search",
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"at",
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"translation",
"accuracy",
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"We",
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"the",
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"multi-domain",
"Dialogue",
"State",
"Tracking",
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"open",
"vocabulary.",
"Existing",
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"exploit",
"BERT",
"encoder",
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"copy-based",
"RNN",
"decoder,",
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"encoder",
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"values.",
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"structure,",
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"prediction",
"objective",
"only",
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"encoder",
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"value",
"generation",
"objective",
"mainly",
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"RNN",
"decoder.",
"In",
"this",
"paper,",
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"propose",
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"purely",
"Transformer-based",
"framework,",
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"a",
"single",
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"encoder",
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"the",
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"In",
"so",
"doing,",
"the",
"operation",
"prediction",
"objective",
"and",
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"value",
"generation",
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"can",
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"BERT",
"for",
"DST.",
"At",
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"re-use",
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"mechanism",
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"decoder",
"layers",
"to",
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"a",
"flat",
"encoder-decoder",
"architecture",
"for",
"effective",
"parameter",
"updating.",
"Experimental",
"results",
"show",
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"our",
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"substantially",
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"framework,",
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"to",
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"The",
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"we",
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"the",
"task",
"instruction,",
"the",
"labeled",
"examples,",
"and",
"the",
"target",
"input",
"to",
"predict;",
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"meta-train",
"the",
"model",
"to",
"learn",
"from",
"in-context",
"examples,",
"we",
"fine-tune",
"a",
"pre-trained",
"language",
"model",
"(LM)",
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"predict",
"the",
"target",
"label",
"from",
"the",
"input",
"sequences",
"on",
"a",
"collection",
"of",
"tasks.",
"We",
"benchmark",
"our",
"method",
"on",
"two",
"collections",
"of",
"text",
"classification",
"tasks:",
"LAMA",
"and",
"BinaryClfs.",
"Compared",
"to",
"first-order",
"MAML",
"which",
"adapts",
"the",
"model",
"with",
"gradient",
"descent,",
"our",
"method",
"better",
"leverages",
"the",
"inductive",
"bias",
"of",
"LMs",
"to",
"perform",
"pattern",
"matching,",
"and",
"outperforms",
"MAML",
"by",
"an",
"absolute",
"$6\\%$",
"AUC",
"ROC",
"score",
"on",
"BinaryClfs,",
"with",
"increasing",
"advantage",
"w.r.t.",
"model",
"size.",
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"to",
"non-fine-tuned",
"in-context",
"learning",
"(i.e.",
"prompting",
"a",
"raw",
"LM),",
"in-context",
"tuning",
"directly",
"learns",
"to",
"learn",
"from",
"in-context",
"examples.",
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"BinaryClfs,",
"in-context",
"tuning",
"improves",
"the",
"average",
"AUC-ROC",
"score",
"by",
"an",
"absolute",
"$10\\%$,",
"and",
"reduces",
"the",
"variance",
"with",
"respect",
"to",
"example",
"ordering",
"by",
"6x",
"and",
"example",
"choices",
"by",
"2x."
] |
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[
"Learning",
"with",
"noisy",
"labels",
"is",
"a",
"practically",
"challenging",
"problem",
"in",
"weakly",
"supervised",
"learning.",
"In",
"the",
"existing",
"literature,",
"open-set",
"noises",
"are",
"always",
"considered",
"to",
"be",
"poisonous",
"for",
"generalization,",
"similar",
"to",
"closed-set",
"noises.",
"In",
"this",
"paper,",
"we",
"empirically",
"show",
"that",
"open-set",
"noisy",
"labels",
"can",
"be",
"non-toxic",
"and",
"even",
"benefit",
"the",
"robustness",
"against",
"inherent",
"noisy",
"labels.",
"Inspired",
"by",
"the",
"observations,",
"we",
"propose",
"a",
"simple",
"yet",
"effective",
"regularization",
"by",
"introducing",
"Open-set",
"samples",
"with",
"Dynamic",
"Noisy",
"Labels",
"(ODNL)",
"into",
"training.",
"With",
"ODNL,",
"the",
"extra",
"capacity",
"of",
"the",
"neural",
"network",
"can",
"be",
"largely",
"consumed",
"in",
"a",
"way",
"that",
"does",
"not",
"interfere",
"with",
"learning",
"patterns",
"from",
"clean",
"data.",
"Through",
"the",
"lens",
"of",
"SGD",
"noise,",
"we",
"show",
"that",
"the",
"noises",
"induced",
"by",
"our",
"method",
"are",
"random-direction,",
"conflict-free",
"and",
"biased,",
"which",
"may",
"help",
"the",
"model",
"converge",
"to",
"a",
"flat",
"minimum",
"with",
"superior",
"stability",
"and",
"enforce",
"the",
"model",
"to",
"produce",
"conservative",
"predictions",
"on",
"Out-of-Distribution",
"instances.",
"Extensive",
"experimental",
"results",
"on",
"benchmark",
"datasets",
"with",
"various",
"types",
"of",
"noisy",
"labels",
"demonstrate",
"that",
"the",
"proposed",
"method",
"not",
"only",
"enhances",
"the",
"performance",
"of",
"many",
"existing",
"robust",
"algorithms",
"but",
"also",
"achieves",
"significant",
"improvement",
"on",
"Out-of-Distribution",
"detection",
"tasks",
"even",
"in",
"the",
"label",
"noise",
"setting."
] |
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[
"In",
"real-world",
"search,",
"recommendation,",
"and",
"advertising",
"systems,",
"the",
"multi-stage",
"ranking",
"architecture",
"is",
"commonly",
"adopted.",
"Such",
"architecture",
"usually",
"consists",
"of",
"matching,",
"pre-ranking,",
"ranking,",
"and",
"re-ranking",
"stages.",
"In",
"the",
"pre-ranking",
"stage,",
"vector-product",
"based",
"models",
"with",
"representation-focused",
"architecture",
"are",
"commonly",
"adopted",
"to",
"account",
"for",
"system",
"efficiency.",
"However,",
"it",
"brings",
"a",
"significant",
"loss",
"to",
"the",
"effectiveness",
"of",
"the",
"system.",
"In",
"this",
"paper,",
"a",
"novel",
"pre-ranking",
"approach",
"is",
"proposed",
"which",
"supports",
"complicated",
"models",
"with",
"interaction-focused",
"architecture.",
"It",
"achieves",
"a",
"better",
"tradeoff",
"between",
"effectiveness",
"and",
"efficiency",
"by",
"utilizing",
"the",
"proposed",
"learnable",
"Feature",
"Selection",
"method",
"based",
"on",
"feature",
"Complexity",
"and",
"variational",
"Dropout",
"(FSCD).",
"Evaluations",
"in",
"a",
"real-world",
"e-commerce",
"sponsored",
"search",
"system",
"for",
"a",
"search",
"engine",
"demonstrate",
"that",
"utilizing",
"the",
"proposed",
"pre-ranking,",
"the",
"effectiveness",
"of",
"the",
"system",
"is",
"significantly",
"improved.",
"Moreover,",
"compared",
"to",
"the",
"systems",
"with",
"conventional",
"pre-ranking",
"models,",
"an",
"identical",
"amount",
"of",
"computational",
"resource",
"is",
"consumed."
] |
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[
"With",
"the",
"prevalence",
"of",
"Diabetes,",
"the",
"Diabetes",
"Mellitus",
"Retinopathy",
"(DR)",
"is",
"becoming",
"a",
"major",
"health",
"problem",
"across",
"the",
"world.",
"The",
"long-term",
"medical",
"complications",
"arising",
"due",
"to",
"DR",
"have",
"a",
"significant",
"impact",
"on",
"the",
"patient",
"as",
"well",
"as",
"the",
"society,",
"as",
"the",
"disease",
"mostly",
"affects",
"individuals",
"in",
"their",
"most",
"productive",
"years.",
"Early",
"detection",
"and",
"treatment",
"can",
"help",
"reduce",
"the",
"extent",
"of",
"damage",
"to",
"the",
"patients.",
"The",
"rise",
"of",
"Convolutional",
"Neural",
"Networks",
"for",
"predictive",
"analysis",
"in",
"the",
"medical",
"field",
"paves",
"the",
"way",
"for",
"a",
"robust",
"solution",
"to",
"DR",
"detection.",
"This",
"paper",
"studies",
"the",
"performance",
"of",
"several",
"highly",
"efficient",
"and",
"scalable",
"CNN",
"architectures",
"for",
"Diabetic",
"Retinopathy",
"Classification",
"with",
"the",
"help",
"of",
"Transfer",
"Learning",
".",
"The",
"research",
"focuses",
"on",
"VGG",
"16,",
"Resnet50",
"V2",
"and",
"EfficientNet",
"B0",
"models.",
"The",
"classification",
"performance",
"is",
"analyzed",
"using",
"several",
"performance",
"metrics",
"including",
"TRUE",
"Positive",
"Rate,",
"FALSE",
"Positive",
"Rate,",
"Accuracy,",
"etc.",
"Also,",
"several",
"performance",
"graphs",
"are",
"plotted",
"for",
"visualizing",
"the",
"architecture",
"performance",
"including",
"Confusion",
"Matrix,",
"ROC",
"Curve,",
"etc.",
"The",
"results",
"indicate",
"that",
"Transfer",
"Learning",
"with",
"ImageNet",
"weights",
"using",
"VGG",
"16",
"model",
"demonstrates",
"the",
"best",
"classification",
"performance",
"with",
"the",
"best",
"Accuracy",
"of",
"95%.",
"It",
"is",
"closely",
"followed",
"by",
"ResNet50",
"V2",
"architecture",
"with",
"the",
"best",
"Accuracy",
"of",
"93%.",
"This",
"paper",
"shows",
"that",
"predictive",
"analysis",
"of",
"DR",
"from",
"retinal",
"images",
"is",
"achieved",
"with",
"Transfer",
"Learning",
"on",
"Convolutional",
"Neural",
"Networks."
] |
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[
"The",
"recent",
"state-of-the-art",
"natural",
"language",
"understanding",
"(NLU)",
"systems",
"often",
"behave",
"unpredictably,",
"failing",
"on",
"simpler",
"reasoning",
"examples.",
"Despite",
"this,",
"there",
"has",
"been",
"limited",
"focus",
"on",
"quantifying",
"progress",
"towards",
"systems",
"with",
"more",
"predictable",
"behavior.",
"We",
"think",
"that",
"reasoning",
"capability-wise",
"behavioral",
"summary",
"is",
"a",
"step",
"towards",
"bridging",
"this",
"gap.",
"We",
"create",
"a",
"CheckList",
"test-suite",
"(184K",
"examples)",
"for",
"the",
"Natural",
"Language",
"Inference",
"(NLI)",
"task,",
"a",
"representative",
"NLU",
"task.",
"We",
"benchmark",
"state-of-the-art",
"NLI",
"systems",
"on",
"this",
"test-suite,",
"which",
"reveals",
"fine-grained",
"insights",
"into",
"the",
"reasoning",
"abilities",
"of",
"BERT",
"and",
"RoBERT",
"a.",
"Our",
"analysis",
"further",
"reveals",
"inconsistencies",
"of",
"the",
"models",
"on",
"examples",
"derived",
"from",
"the",
"same",
"template",
"or",
"distinct",
"templates",
"but",
"pertaining",
"to",
"same",
"reasoning",
"capability,",
"indicating",
"that",
"generalizing",
"the",
"models'",
"behavior",
"through",
"observations",
"made",
"on",
"a",
"CheckList",
"is",
"non-trivial.",
"Through",
"an",
"user-study,",
"we",
"find",
"that",
"users",
"were",
"able",
"to",
"utilize",
"behavioral",
"information",
"to",
"generalize",
"much",
"better",
"for",
"examples",
"predicted",
"from",
"RoBERT",
"a,",
"compared",
"to",
"that",
"of",
"BERT",
"."
] |
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6,
6,
6,
6,
7,
6,
6,
6,
6,
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7,
6
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[
"In",
"this",
"paper",
"we",
"describe",
"our",
"system",
"for",
"SemEval-2018",
"Task",
"7",
"on",
"classification",
"of",
"semantic",
"relations",
"in",
"scientific",
"literature",
"for",
"clean",
"(subtask",
"1.1)",
"and",
"noisy",
"data",
"(subtask",
"1.2).",
"We",
"compare",
"two",
"models",
"for",
"classification,",
"a",
"C-LSTM",
"which",
"utilizes",
"only",
"word",
"embeddings",
"and",
"an",
"SVM",
"that",
"also",
"takes",
"handcrafted",
"features",
"into",
"account.",
"To",
"adapt",
"to",
"the",
"domain",
"of",
"science",
"we",
"train",
"word",
"embeddings",
"on",
"scientific",
"papers",
"collected",
"from",
"arXiv.org.",
"The",
"hand-crafted",
"features",
"consist",
"of",
"lexical",
"features",
"to",
"model",
"the",
"semantic",
"relations",
"as",
"well",
"as",
"the",
"entities",
"between",
"which",
"the",
"relation",
"holds.",
"Classification",
"of",
"Relations",
"using",
"Embeddings",
"(ClaiRE)",
"achieved",
"an",
"F1",
"score",
"of",
"74.89{\\%}",
"for",
"the",
"first",
"subtask",
"and",
"78.39{\\%}",
"for",
"the",
"second."
] |
[
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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,
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6,
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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,
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6,
6,
6,
6,
6,
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6,
6,
6,
6,
6
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[
"Overestimation",
"of",
"the",
"maximum",
"action-value",
"is",
"a",
"well-known",
"problem",
"that",
"hinders",
"Q-Learning",
"performance,",
"leading",
"to",
"suboptimal",
"policies",
"and",
"unstable",
"learning.",
"Among",
"several",
"Q-Learning",
"variants",
"proposed",
"to",
"address",
"this",
"issue,",
"Weighted",
"Q-Learning",
"(WQL)",
"effectively",
"reduces",
"the",
"bias",
"and",
"shows",
"remarkable",
"results",
"in",
"stochastic",
"environments.",
"WQL",
"uses",
"a",
"weighted",
"sum",
"of",
"the",
"estimated",
"action-values,",
"where",
"the",
"weights",
"correspond",
"to",
"the",
"probability",
"of",
"each",
"action-value",
"being",
"the",
"maximum;",
"however,",
"the",
"computation",
"of",
"these",
"probabilities",
"is",
"only",
"practical",
"in",
"the",
"tabular",
"settings.",
"In",
"this",
"work,",
"we",
"provide",
"the",
"methodological",
"advances",
"to",
"benefit",
"from",
"the",
"WQL",
"properties",
"in",
"Deep",
"Reinforcement",
"Learning",
"(DRL),",
"by",
"using",
"neural",
"networks",
"with",
"Dropout",
"Variational",
"Inference",
"as",
"an",
"effective",
"approximation",
"of",
"deep",
"Gaussian",
"processes.",
"In",
"particular,",
"we",
"adopt",
"the",
"Concrete",
"Dropout",
"variant",
"to",
"obtain",
"calibrated",
"estimates",
"of",
"epistemic",
"uncertainty",
"in",
"DRL.",
"We",
"show",
"that",
"model",
"uncertainty",
"in",
"DRL",
"can",
"be",
"useful",
"not",
"only",
"for",
"action",
"selection,",
"but",
"also",
"action",
"evaluation.",
"We",
"analyze",
"how",
"the",
"novel",
"Weighted",
"Deep",
"Q-Learning",
"algorithm",
"reduces",
"the",
"bias",
"w.r.t.",
"relevant",
"baselines",
"and",
"provide",
"empirical",
"evidence",
"of",
"its",
"advantages",
"on",
"several",
"representative",
"benchmarks."
] |
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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,
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,
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,
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6,
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6,
6,
6,
6,
6,
1,
3,
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6,
6,
6,
6,
6,
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6,
6,
6,
6,
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2,
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6,
6,
6,
6,
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6,
6,
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
] |
[
"This",
"paper",
"describes",
"our",
"approach",
"to",
"the",
"task",
"of",
"identifying",
"offensive",
"languages",
"in",
"a",
"multilingual",
"setting.",
"We",
"investigate",
"two",
"data",
"augmentation",
"strategies:",
"using",
"additional",
"semi-supervised",
"labels",
"with",
"different",
"thresholds",
"and",
"cross-lingual",
"transfer",
"with",
"data",
"selection.",
"Leveraging",
"the",
"semi-supervised",
"dataset",
"resulted",
"in",
"performance",
"improvements",
"compared",
"to",
"the",
"baseline",
"trained",
"solely",
"with",
"the",
"manually-annotated",
"dataset.",
"We",
"propose",
"a",
"new",
"metric,",
"Translation",
"Embedding",
"Distance,",
"to",
"measure",
"the",
"transferability",
"of",
"instances",
"for",
"cross-lingual",
"data",
"selection.",
"We",
"also",
"introduce",
"various",
"preprocessing",
"steps",
"tailored",
"for",
"social",
"media",
"text",
"along",
"with",
"methods",
"to",
"fine-tune",
"the",
"pre-trained",
"multilingual",
"BERT",
"(mBERT",
")",
"for",
"offensive",
"language",
"identification.",
"Our",
"multilingual",
"systems",
"achieved",
"competitive",
"results",
"in",
"Greek,",
"Danish,",
"and",
"Turkish",
"at",
"OffensEval",
"2020"
] |
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6,
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7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6
] |
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