tokens
list | ner_tags
list |
|---|---|
[
"Recently,",
"Differentiable",
"Architecture",
"Search",
"(DARTS",
")",
"has",
"become",
"one",
"of",
"the",
"most",
"popular",
"Neural",
"Architecture",
"Search",
"(NAS)",
"methods",
"successfully",
"applied",
"in",
"supervised",
"learning",
"(SL).",
"However,",
"its",
"applications",
"in",
"other",
"domains,",
"in",
"particular",
"for",
"reinforcement",
"learning",
"(RL),",
"has",
"seldom",
"been",
"studied.",
"This",
"is",
"due",
"in",
"part",
"to",
"RL",
"possessing",
"a",
"significantly",
"different",
"optimization",
"paradigm",
"than",
"SL,",
"especially",
"with",
"regards",
"to",
"the",
"notion",
"of",
"replay",
"data,",
"which",
"is",
"continually",
"generated",
"via",
"inference",
"in",
"RL.",
"In",
"this",
"paper,",
"we",
"introduce",
"RL-DARTS",
",",
"one",
"of",
"the",
"first",
"applications",
"of",
"end-to-end",
"DARTS",
"in",
"RL",
"to",
"search",
"for",
"convolutional",
"cells,",
"applied",
"to",
"the",
"challenging,",
"infinitely",
"procedurally",
"generated",
"Procgen",
"benchmark.",
"We",
"demonstrate",
"that",
"the",
"benefits",
"of",
"DARTS",
"become",
"amplified",
"when",
"applied",
"to",
"RL,",
"namely",
"search",
"efficiency",
"in",
"terms",
"of",
"time",
"and",
"compute,",
"as",
"well",
"as",
"simplicity",
"in",
"integration",
"with",
"complex",
"preexisting",
"RL",
"code",
"via",
"simply",
"replacing",
"the",
"image",
"encoder",
"with",
"a",
"DARTS",
"supernet,",
"compatible",
"with",
"both",
"off-policy",
"and",
"on-policy",
"RL",
"algorithms.",
"At",
"the",
"same",
"time",
"however,",
"we",
"provide",
"one",
"of",
"the",
"first",
"extensive",
"studies",
"of",
"DARTS",
"outside",
"of",
"the",
"standard",
"fixed",
"dataset",
"setting",
"in",
"SL",
"via",
"RL-DARTS",
".",
"We",
"show",
"that",
"throughout",
"training,",
"the",
"supernet",
"gradually",
"learns",
"better",
"cells,",
"leading",
"to",
"alternative",
"architectures",
"which",
"can",
"be",
"highly",
"competitive",
"against",
"manually",
"designed",
"policies,",
"but",
"also",
"verify",
"previous",
"design",
"choices",
"for",
"RL",
"policies."
] |
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[
"In",
"this",
"paper",
"we",
"describe",
"a",
"novel",
"data",
"structure",
"for",
"phrase-based",
"statistical",
"machine",
"translation",
"which",
"allows",
"for",
"the",
"retrieval",
"of",
"arbitrarily",
"long",
"phrases",
"while",
"simultaneously",
"using",
"less",
"memory",
"than",
"is",
"required",
"by",
"current",
"decoder",
"implementations",
".",
"We",
"detail",
"the",
"computational",
"complexity",
"and",
"average",
"retrieval",
"times",
"for",
"looking",
"up",
"phrase",
"translations",
"in",
"our",
"suffix",
"array-based",
"data",
"structure",
".",
"We",
"show",
"how",
"sampling",
"can",
"be",
"used",
"to",
"reduce",
"the",
"retrieval",
"time",
"by",
"orders",
"of",
"magnitude",
"with",
"no",
"loss",
"in",
"translation",
"quality",
"."
] |
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[
"Strictly",
"enforcing",
"orthonormality",
"constraints",
"on",
"parameter",
"matrices",
"has",
"been",
"shown",
"advantageous",
"in",
"deep",
"learning.",
"This",
"amounts",
"to",
"Riemannian",
"optimization",
"on",
"the",
"Stiefel",
"manifold,",
"which,",
"however,",
"is",
"computationally",
"expensive.",
"To",
"address",
"this",
"challenge,",
"we",
"present",
"two",
"main",
"contributions:",
"-1",
"A",
"new",
"efficient",
"retraction",
"map",
"based",
"on",
"an",
"iterative",
"Cayley",
"transform",
"for",
"optimization",
"updates,",
"and",
"-2",
"An",
"implicit",
"vector",
"transport",
"mechanism",
"based",
"on",
"the",
"combination",
"of",
"a",
"projection",
"of",
"the",
"momentum",
"and",
"the",
"Cayley",
"transform",
"on",
"the",
"Stiefel",
"manifold.",
"We",
"specify",
"two",
"new",
"optimization",
"algorithms:",
"Cayley",
"SGD",
"with",
"momentum,",
"and",
"Cayley",
"ADAM",
"on",
"the",
"Stiefel",
"manifold.",
"Convergence",
"of",
"Cayley",
"SGD",
"is",
"theoretically",
"analyzed.",
"Our",
"experiments",
"for",
"CNN",
"training",
"demonstrate",
"that",
"both",
"algorithms:",
"(a)",
"Use",
"less",
"running",
"time",
"per",
"iteration",
"relative",
"to",
"existing",
"approaches",
"that",
"enforce",
"orthonormality",
"of",
"CNN",
"parameters;",
"and",
"(b)",
"Achieve",
"faster",
"convergence",
"rates",
"than",
"the",
"baseline",
"SGD",
"and",
"ADAM",
"algorithms",
"without",
"compromising",
"the",
"performance",
"of",
"the",
"CNN.",
"Cayley",
"SGD",
"and",
"Cayley",
"ADAM",
"are",
"also",
"shown",
"to",
"reduce",
"the",
"training",
"time",
"for",
"optimizing",
"the",
"unitary",
"transition",
"matrices",
"in",
"RNNs."
] |
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[
"A",
"highly",
"desirable",
"property",
"of",
"a",
"reinforcement",
"learning",
"(RL)",
"agent",
"--",
"and",
"a",
"major",
"difficulty",
"for",
"deep",
"RL",
"approaches",
"--",
"is",
"the",
"ability",
"to",
"generalize",
"policies",
"learned",
"on",
"a",
"few",
"tasks",
"over",
"a",
"high-dimensional",
"observation",
"space",
"to",
"similar",
"tasks",
"not",
"seen",
"during",
"training.",
"Many",
"promising",
"approaches",
"to",
"this",
"challenge",
"consider",
"RL",
"as",
"a",
"process",
"of",
"training",
"two",
"functions",
"simultaneously:",
"a",
"complex",
"nonlinear",
"encoder",
"that",
"maps",
"high-dimensional",
"observations",
"to",
"a",
"latent",
"representation",
"space,",
"and",
"a",
"simple",
"linear",
"policy",
"over",
"this",
"space.",
"We",
"posit",
"that",
"a",
"superior",
"encoder",
"for",
"zero-shot",
"generalization",
"in",
"RL",
"can",
"be",
"trained",
"by",
"using",
"solely",
"an",
"auxiliary",
"SSL",
"objective",
"if",
"the",
"training",
"process",
"encourages",
"the",
"encoder",
"to",
"map",
"behaviorally",
"similar",
"observations",
"to",
"similar",
"representations,",
"as",
"reward-based",
"signal",
"can",
"cause",
"overfitting",
"in",
"the",
"encoder",
"(Raileanu",
"et",
"al.,",
"2021).",
"We",
"propose",
"Cross-Trajectory",
"Representation",
"Learning",
"(CTRL",
"),",
"a",
"method",
"that",
"runs",
"within",
"an",
"RL",
"agent",
"and",
"conditions",
"its",
"encoder",
"to",
"recognize",
"behavioral",
"similarity",
"in",
"observations",
"by",
"applying",
"a",
"novel",
"SSL",
"objective",
"to",
"pairs",
"of",
"trajectories",
"from",
"the",
"agent's",
"policies.",
"CTRL",
"can",
"be",
"viewed",
"as",
"having",
"the",
"same",
"effect",
"as",
"inducing",
"a",
"pseudo-bisimulation",
"metric",
"but,",
"crucially,",
"avoids",
"the",
"use",
"of",
"rewards",
"and",
"associated",
"overfitting",
"risks.",
"Our",
"experiments",
"ablate",
"various",
"components",
"of",
"CTRL",
"and",
"demonstrate",
"that",
"in",
"combination",
"with",
"PPO",
"it",
"achieves",
"better",
"generalization",
"performance",
"on",
"the",
"challenging",
"Procgen",
"benchmark",
"suite",
"(Cobbe",
"et",
"al.,",
"2020)."
] |
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[
"Named",
"entity",
"recognition",
"(NER",
")",
"is",
"used",
"to",
"identify",
"relevant",
"entities",
"in",
"text.A",
"bidirectional",
"LSTM",
"(long",
"short",
"term",
"memory)",
"encoder",
"with",
"a",
"neural",
"conditionalrandom",
"fields",
"(CRF)",
"decoder",
"(biLSTM",
"-CRF)",
"is",
"the",
"state",
"of",
"the",
"art",
"methodology.In",
"this",
"work,",
"we",
"have",
"done",
"an",
"analysis",
"of",
"several",
"methods",
"that",
"intend",
"tooptimize",
"the",
"performance",
"of",
"networks",
"based",
"on",
"this",
"architecture,",
"which",
"in",
"somecases",
"encourage",
"overfitting",
"avoidance.",
"These",
"methods",
"target",
"exploration",
"ofparameter",
"space,",
"regularization",
"of",
"LSTM",
"s",
"and",
"penalization",
"of",
"confident",
"outputdistributions.",
"Results",
"show",
"that",
"the",
"optimization",
"methods",
"improve",
"theperformance",
"of",
"the",
"biLSTM",
"#NAME?",
"NER",
"baseline",
"system,",
"setting",
"a",
"new",
"state",
"of",
"theart",
"performance",
"for",
"the",
"CoNLL-2003",
"Spanish",
"set",
"with",
"an",
"F1",
"of",
"87.18."
] |
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[
"Recent",
"studies",
"have",
"demonstrated",
"a",
"perceivable",
"improvement",
"on",
"the",
"performance",
"of",
"neural",
"machine",
"translation",
"by",
"applying",
"cross-lingual",
"language",
"model",
"pretraining",
"(Lample",
"and",
"Conneau,",
"2019),",
"especially",
"the",
"Translation",
"Language",
"Modeling",
"(TLM).",
"To",
"alleviate",
"the",
"need",
"for",
"expensive",
"parallel",
"corpora",
"by",
"TLM,",
"in",
"this",
"work,",
"we",
"incorporate",
"the",
"translation",
"information",
"from",
"dictionaries",
"into",
"the",
"pretraining",
"process",
"and",
"propose",
"a",
"novel",
"Bilingual",
"Dictionary-based",
"Language",
"Model",
"(BDLM).",
"We",
"evaluate",
"our",
"BDLM",
"in",
"Chinese,",
"English,",
"and",
"Romanian.",
"For",
"Chinese-English,",
"we",
"obtained",
"a",
"55",
"BLEU",
"on",
"WMT-News19",
"(Tiedemann,",
"2012)",
"and",
"a",
"24.3",
"BLEU",
"on",
"WMT20",
"news-commentary,",
"outperforming",
"the",
"Vanilla",
"Transformer",
"(Vaswani",
"et",
"al.,",
"2017)",
"by",
"more",
"than",
"8.4",
"BLEU",
"and",
"2.3",
"BLEU,",
"respectively.",
"According",
"to",
"our",
"results,",
"the",
"BDLM",
"also",
"has",
"advantages",
"on",
"convergence",
"speed",
"and",
"predicting",
"rare",
"words.",
"The",
"increase",
"in",
"BLEU",
"for",
"WMT16",
"Romanian-English",
"also",
"shows",
"its",
"effectiveness",
"in",
"low-resources",
"language",
"translation."
] |
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[
"Previous",
"studies",
"in",
"Open",
"Information",
"Extraction",
"(Open",
"IE)",
"are",
"mainly",
"based",
"onextraction",
"patterns.",
"They",
"manually",
"define",
"patterns",
"or",
"automatically",
"learn",
"themfrom",
"a",
"large",
"corpus.",
"However,",
"these",
"approaches",
"are",
"limited",
"when",
"grasping",
"thecontext",
"of",
"a",
"sentence,",
"and",
"they",
"fail",
"to",
"capture",
"implicit",
"relations.",
"In",
"thispaper,",
"we",
"address",
"this",
"problem",
"with",
"the",
"following",
"methods.",
"First,",
"we",
"exploitlong",
"short-term",
"memory",
"(LSTM",
")",
"networks",
"to",
"extract",
"higher-level",
"features",
"alongthe",
"shortest",
"dependency",
"paths,",
"connecting",
"headwords",
"of",
"relations",
"and",
"arguments.The",
"path-level",
"features",
"from",
"LSTM",
"networks",
"provide",
"useful",
"clues",
"regardingcontextual",
"information",
"and",
"the",
"validity",
"of",
"arguments.",
"Second,",
"we",
"constructedsamples",
"to",
"train",
"LSTM",
"networks",
"without",
"the",
"need",
"for",
"manual",
"labeling.",
"Inparticular,",
"feedback",
"negative",
"sampling",
"picks",
"highly",
"negative",
"samples",
"amongnon-positive",
"samples",
"through",
"a",
"model",
"trained",
"with",
"positive",
"samples.",
"Theexperimental",
"results",
"show",
"that",
"our",
"approach",
"produces",
"more",
"precise",
"and",
"abundantextractions",
"than",
"state-of-the-art",
"open",
"IE",
"systems.",
"To",
"the",
"best",
"of",
"ourknowledge,",
"this",
"is",
"the",
"first",
"work",
"to",
"apply",
"deep",
"learning",
"to",
"Open",
"IE."
] |
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[
"Video",
"understanding",
"of",
"robot-assisted",
"surgery",
"(RAS)",
"videos",
"is",
"an",
"active",
"research",
"area.",
"Modeling",
"the",
"gestures",
"and",
"skill",
"level",
"of",
"surgeons",
"presents",
"an",
"interesting",
"problem.",
"The",
"insights",
"drawn",
"may",
"be",
"applied",
"in",
"effective",
"skill",
"acquisition,",
"objective",
"skill",
"assessment,",
"real-time",
"feedback,",
"and",
"human-robot",
"collaborative",
"surgeries.",
"We",
"propose",
"a",
"solution",
"to",
"the",
"tool",
"detection",
"and",
"localization",
"open",
"problem",
"in",
"RAS",
"video",
"understanding,",
"using",
"a",
"strictly",
"computer",
"vision",
"approach",
"and",
"the",
"recent",
"advances",
"of",
"deep",
"learning.",
"We",
"propose",
"an",
"architecture",
"using",
"multimodal",
"convolutional",
"neural",
"networks",
"for",
"fast",
"detection",
"and",
"localization",
"of",
"tools",
"in",
"RAS",
"videos.",
"To",
"our",
"knowledge,",
"this",
"approach",
"will",
"be",
"the",
"first",
"to",
"incorporate",
"deep",
"neural",
"networks",
"for",
"tool",
"detection",
"and",
"localization",
"in",
"RAS",
"videos.",
"Our",
"architecture",
"applies",
"a",
"Region",
"Proposal",
"Network",
"(RPN",
"),",
"and",
"a",
"multi-modal",
"two",
"stream",
"convolutional",
"network",
"for",
"object",
"detection,",
"to",
"jointly",
"predict",
"objectness",
"and",
"localization",
"on",
"a",
"fusion",
"of",
"image",
"and",
"temporal",
"motion",
"cues.",
"Our",
"results",
"with",
"an",
"Average",
"Precision",
"(AP)",
"of",
"91%",
"and",
"a",
"mean",
"computation",
"time",
"of",
"0.1",
"seconds",
"per",
"test",
"frame",
"detection",
"indicate",
"that",
"our",
"study",
"is",
"superior",
"to",
"conventionally",
"used",
"methods",
"for",
"medical",
"imaging",
"while",
"also",
"emphasizing",
"the",
"benefits",
"of",
"using",
"RPN",
"for",
"precision",
"and",
"efficiency.",
"We",
"also",
"introduce",
"a",
"new",
"dataset,",
"ATLAS",
"Dione,",
"for",
"RAS",
"video",
"understanding.",
"Our",
"dataset",
"provides",
"video",
"data",
"of",
"ten",
"surgeons",
"from",
"Roswell",
"Park",
"Cancer",
"Institute",
"(RPCI)",
"(Buffalo,",
"NY)",
"performing",
"six",
"different",
"surgical",
"tasks",
"on",
"the",
"daVinci",
"Surgical",
"System",
"(dVSS",
"R",
")",
"with",
"annotations",
"of",
"robotic",
"tools",
"per",
"frame."
] |
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[
"A",
"common",
"issue",
"of",
"deep",
"neural",
"networks-based",
"methods",
"for",
"the",
"problem",
"ofSingle",
"Image",
"Super-Resolution",
"(SISR),",
"is",
"the",
"recovery",
"of",
"finer",
"texture",
"detailswhen",
"super-resolving",
"at",
"large",
"upscaling",
"factors.",
"This",
"issue",
"is",
"particularlyrelated",
"to",
"the",
"choice",
"of",
"the",
"objective",
"loss",
"function.",
"In",
"particular,",
"recentworks",
"proposed",
"the",
"use",
"of",
"a",
"VGG",
"loss",
"which",
"consists",
"in",
"minimizing",
"the",
"errorbetween",
"the",
"generated",
"high",
"resolution",
"images",
"and",
"ground-truth",
"in",
"the",
"featurespace",
"of",
"a",
"Convolutional",
"Neural",
"Network",
"(VGG",
"19),",
"pre-trained",
"on",
"the",
"very\"large\"",
"ImageNet",
"dataset.",
"When",
"considering",
"the",
"problem",
"of",
"super-resolvingimages",
"with",
"a",
"distribution",
"far",
"from",
"the",
"ImageNet",
"images",
"distribution(\\textit{e.g.,}",
"satellite",
"images),",
"their",
"proposed",
"\\textit{fixed}",
"VGG",
"loss",
"is",
"nolonger",
"relevant.",
"In",
"this",
"paper,",
"we",
"present",
"a",
"general",
"framework",
"named\\textit{Generative",
"Collaborative",
"Networks}",
"(GCN",
"),",
"where",
"the",
"idea",
"consists",
"inoptimizing",
"the",
"\\textit{generator}",
"(the",
"mapping",
"of",
"interest)",
"in",
"the",
"featurespace",
"of",
"a",
"\\textit{features",
"extractor}",
"network.",
"The",
"two",
"networks",
"(generator",
"andextractor)",
"are",
"\\textit{collaborative}",
"in",
"the",
"sense",
"that",
"the",
"latter",
"helps",
"theformer,",
"by",
"constructing",
"discriminative",
"and",
"relevant",
"features",
"(not",
"necessarily\\textit{fixed}",
"and",
"possibly",
"learned",
"\\textit{mutually}",
"with",
"the",
"generator).",
"Weevaluate",
"the",
"GCN",
"framework",
"in",
"the",
"context",
"of",
"SISR,",
"and",
"we",
"show",
"that",
"it",
"resultsin",
"a",
"method",
"that",
"is",
"adapted",
"to",
"super-resolution",
"domains",
"that",
"are",
"far",
"from",
"theImageNet",
"domain."
] |
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[
"We",
"detect",
"out-of-training-distribution",
"sentences",
"in",
"Neural",
"Machine",
"Translation",
"using",
"the",
"Bayesian",
"Deep",
"Learning",
"equivalent",
"of",
"Transformer",
"models.",
"For",
"this",
"we",
"develop",
"a",
"new",
"measure",
"of",
"uncertainty",
"designed",
"specifically",
"for",
"long",
"sequences",
"of",
"discrete",
"random",
"variables",
"--",
"i.e.",
"words",
"in",
"the",
"output",
"sentence.",
"Our",
"new",
"measure",
"of",
"uncertainty",
"solves",
"a",
"major",
"intractability",
"in",
"the",
"naive",
"application",
"of",
"existing",
"approaches",
"on",
"long",
"sentences.",
"We",
"use",
"our",
"new",
"measure",
"on",
"a",
"Transformer",
"model",
"trained",
"with",
"dropout",
"approximate",
"inference.",
"On",
"the",
"task",
"of",
"German-English",
"translation",
"using",
"WMT13",
"and",
"Europarl,",
"we",
"show",
"that",
"with",
"dropout",
"uncertainty",
"our",
"measure",
"is",
"able",
"to",
"identify",
"when",
"Dutch",
"source",
"sentences,",
"sentences",
"which",
"use",
"the",
"same",
"word",
"types",
"as",
"German,",
"are",
"given",
"to",
"the",
"model",
"instead",
"of",
"German."
] |
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[
"For",
"unsupervised",
"data-dependent",
"hashing,",
"the",
"two",
"most",
"important",
"requirements",
"are",
"to",
"preserve",
"similarity",
"in",
"the",
"low-dimensional",
"feature",
"space",
"and",
"to",
"minimize",
"the",
"binary",
"quantization",
"loss.",
"A",
"well-established",
"hashing",
"approach",
"is",
"Iterative",
"Quantization",
"(ITQ),",
"which",
"addresses",
"these",
"two",
"requirements",
"in",
"separate",
"steps.",
"In",
"this",
"paper,",
"we",
"revisit",
"the",
"ITQ",
"approach",
"and",
"propose",
"novel",
"formulations",
"and",
"algorithms",
"to",
"the",
"problem.",
"Specifically,",
"we",
"propose",
"a",
"novel",
"approach,",
"named",
"Simultaneous",
"Compression",
"and",
"Quantization",
"(SCQ),",
"to",
"jointly",
"learn",
"to",
"compress",
"(reduce",
"dimensionality)",
"and",
"binarize",
"input",
"data",
"in",
"a",
"single",
"formulation",
"under",
"strict",
"orthogonal",
"constraint.",
"With",
"this",
"approach,",
"we",
"introduce",
"a",
"loss",
"function",
"and",
"its",
"relaxed",
"version,",
"termed",
"Orthonormal",
"Encoder",
"(OnE)",
"and",
"Orthogonal",
"Encoder",
"(OgE)",
"respectively,",
"which",
"involve",
"challenging",
"binary",
"and",
"orthogonal",
"constraints.",
"We",
"propose",
"to",
"attack",
"the",
"optimization",
"using",
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"Second,",
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"),",
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"pass,",
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"the",
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"language",
"model",
"for",
"initialization.",
"Thebenefits",
"are",
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"comprehensively",
"preserving",
"sequential",
"and",
"visualinformation;",
"and",
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"adaptively",
"learning",
"dense",
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"features",
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"representations",
"for",
"videos",
"and",
"sentences,",
"respectively.",
"We",
"verify",
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"framework",
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[
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"of",
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"diseases.",
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"research",
"on",
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"vessel",
"segmentation",
"focuses",
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"model",
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"augmentation",
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"addressing",
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"show",
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"performance",
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"U-Net",
"model",
"can",
"be",
"increased",
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"Results",
"are",
"reported",
"using",
"the",
"most",
"widely",
"used",
"retina",
"dataset,",
"DRIVE."
] |
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[
"The",
"role",
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"media",
"in",
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"far-reaching",
"implications",
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"all",
"spheres",
"of",
"society.",
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"media",
"provide",
"platforms",
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"views,",
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"the",
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"posts",
"on",
"platforms",
"like",
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"and",
"Facebook.",
"Misinformation",
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"rumours",
"have",
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"opinions",
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"is",
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"remove",
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"these",
"platforms.",
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"only",
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"spread",
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"is",
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"automatic",
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"media",
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"medium,",
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"Twitter.",
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"approaches",
"rely",
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"Manually",
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"non-rumours",
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"supervised",
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"improved",
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] |
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[
"This",
"paper",
"introduces",
"a",
"large-scale",
"human-labeled",
"dataset",
"for",
"the",
"Vietnamese",
"POS",
"tagging",
"task",
"on",
"conversational",
"texts.",
"To",
"this",
"end,",
"wepropose",
"a",
"new",
"tagging",
"scheme",
"(with",
"36",
"POS",
"tags)",
"consisting",
"of",
"exclusive",
"tags",
"for",
"special",
"phenomena",
"of",
"conversational",
"words,",
"developthe",
"annotation",
"guideline",
"and",
"manually",
"annotate",
"16.310K",
"sentences",
"using",
"this",
"guideline.",
"Based",
"on",
"this",
"corpus,",
"a",
"series",
"of",
"state-of-the-art",
"tagging",
"methods",
"has",
"been",
"conducted",
"to",
"estimate",
"their",
"performances.",
"Experimental",
"results",
"showed",
"that",
"the",
"Conditional",
"Random",
"Fields",
"model",
"using",
"both",
"automatically",
"learnt",
"features",
"from",
"deep",
"neural",
"networks",
"and",
"handcrafted",
"features",
"yielded",
"the",
"best",
"performance.",
"Thismodel",
"achieved",
"93.36{\\%}",
"in",
"the",
"accuracy",
"score",
"which",
"is",
"1.6{\\%}",
"and",
"2.7{\\%}",
"higher",
"than",
"the",
"model",
"using",
"either",
"handcrafted",
"features",
"orautomatically-learnt",
"features,",
"respectively.",
"This",
"result",
"is",
"also",
"a",
"little",
"bit",
"higher",
"than",
"the",
"model",
"of",
"fine-tuning",
"BERT",
"by",
"0.94{\\%}",
"in",
"theaccuracy",
"score.",
"The",
"performance",
"measured",
"on",
"each",
"POS",
"tag",
"is",
"also",
"very",
"high",
"with",
"{\\textgreater}90{\\%}",
"in",
"the",
"F1",
"score",
"for",
"20",
"POS",
"tags",
"and",
"{\\textgreater}80{\\%}in",
"the",
"F1",
"score",
"for",
"11",
"POS",
"tags.",
"This",
"work",
"provides",
"the",
"public",
"dataset",
"and",
"preliminary",
"results",
"for",
"follow-up",
"research",
"on",
"this",
"interesting",
"direction."
] |
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[
"We",
"address",
"the",
"problem",
"of",
"Duplicate",
"Question",
"Detection",
"(DQD)",
"in",
"low-resource",
"domain-specific",
"Community",
"Question",
"Answering",
"forums.",
"Our",
"multi-view",
"framework",
"MV-DASE",
"combines",
"an",
"ensemble",
"of",
"sentence",
"encoders",
"via",
"Generalized",
"Canonical",
"Correlation",
"Analysis,",
"using",
"unlabeled",
"data",
"only.",
"In",
"our",
"experiments,",
"the",
"ensemble",
"includes",
"generic",
"and",
"domain-specific",
"averaged",
"word",
"embeddings,",
"domain-finetuned",
"BERT",
"and",
"the",
"Universal",
"Sentence",
"Encoder.",
"We",
"evaluate",
"MV-DASE",
"on",
"the",
"CQADupStack",
"corpus",
"and",
"on",
"additional",
"low-resource",
"Stack",
"Exchange",
"forums.",
"Combining",
"the",
"strengths",
"of",
"different",
"encoders,",
"we",
"significantly",
"outperform",
"BM25,",
"all",
"single-view",
"systems",
"as",
"well",
"as",
"a",
"recent",
"supervised",
"domain-adversarial",
"DQD",
"method."
] |
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[
"It",
"has",
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"shown",
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"named",
"entity",
"recognition",
"(NER",
")",
"could",
"benefit",
"from",
"incorporating",
"the",
"long-distance",
"structured",
"information",
"captured",
"by",
"dependency",
"trees.",
"We",
"believe",
"this",
"is",
"because",
"both",
"types",
"of",
"features",
"-",
"the",
"contextual",
"information",
"captured",
"by",
"the",
"linear",
"sequences",
"and",
"the",
"structured",
"information",
"captured",
"by",
"the",
"dependency",
"trees",
"may",
"complement",
"each",
"other.",
"However,",
"existing",
"approaches",
"largely",
"focused",
"on",
"stacking",
"the",
"LSTM",
"and",
"graph",
"neural",
"networks",
"such",
"as",
"graph",
"convolutional",
"networks",
"(GCNs)",
"for",
"building",
"improved",
"NER",
"models,",
"where",
"the",
"exact",
"interaction",
"mechanism",
"between",
"the",
"two",
"types",
"of",
"features",
"is",
"not",
"very",
"clear,",
"and",
"the",
"performance",
"gain",
"does",
"not",
"appear",
"to",
"be",
"significant.",
"In",
"this",
"work,",
"we",
"propose",
"a",
"simple",
"and",
"robust",
"solution",
"to",
"incorporate",
"both",
"types",
"of",
"features",
"with",
"our",
"Synergized-LSTM",
"(Syn-LSTM",
"),",
"which",
"clearly",
"captures",
"how",
"the",
"two",
"types",
"of",
"features",
"interact.",
"We",
"conduct",
"extensive",
"experiments",
"on",
"several",
"standard",
"datasets",
"across",
"four",
"languages.",
"The",
"results",
"demonstrate",
"that",
"the",
"proposed",
"model",
"achieves",
"better",
"performance",
"than",
"previous",
"approaches",
"while",
"requiring",
"fewer",
"parameters.",
"Our",
"further",
"analysis",
"demonstrates",
"that",
"our",
"model",
"can",
"capture",
"longer",
"dependencies",
"compared",
"with",
"strong",
"baselines."
] |
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[
"There",
"is",
"a",
"need",
"to",
"protect",
"the",
"personal",
"identity",
"information",
"in",
"public",
"EEG",
"datasets.",
"However,",
"it",
"is",
"challenging",
"to",
"remove",
"such",
"information",
"that",
"has",
"infinite",
"classes",
"(open",
"set).",
"We",
"propose",
"an",
"approach",
"to",
"disguise",
"the",
"identity",
"information",
"in",
"EEG",
"signals",
"with",
"dummy",
"identities,",
"while",
"preserving",
"the",
"key",
"features.",
"The",
"dummy",
"identities",
"are",
"obtained",
"by",
"applying",
"grand",
"average",
"on",
"EEG",
"spectrums",
"across",
"the",
"subjects",
"within",
"a",
"group",
"that",
"have",
"common",
"attributes.",
"The",
"personal",
"identity",
"information",
"in",
"original",
"EEG",
"s",
"are",
"transformed",
"into",
"disguised",
"ones",
"with",
"a",
"CycleGANbased",
"EEG",
"disguising",
"model.",
"With",
"the",
"constraints",
"added",
"to",
"the",
"model,",
"the",
"features",
"of",
"interest",
"in",
"EEG",
"signals",
"can",
"be",
"preserved.",
"We",
"evaluate",
"the",
"model",
"by",
"performing",
"classification",
"tasks",
"on",
"both",
"the",
"original",
"and",
"the",
"disguised",
"EEG",
"and",
"compare",
"the",
"results.",
"For",
"evaluation,",
"we",
"also",
"experiment",
"with",
"ResNet",
"classifiers,",
"which",
"perform",
"well",
"especially",
"on",
"the",
"identity",
"recognition",
"task",
"with",
"an",
"accuracy",
"of",
"98.4%.",
"The",
"results",
"show",
"that",
"our",
"EEG",
"disguising",
"model",
"can",
"hide",
"about",
"90%",
"of",
"personal",
"identity",
"information",
"and",
"can",
"preserve",
"most",
"of",
"the",
"other",
"key",
"features."
] |
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[
"Machine",
"Reading",
"Comprehension",
"(MRC)",
"aims",
"to",
"extract",
"answers",
"to",
"questions",
"given",
"a",
"passage.",
"It",
"has",
"been",
"widely",
"studied",
"recently,",
"especially",
"in",
"open",
"domains.",
"However,",
"few",
"efforts",
"have",
"been",
"made",
"on",
"closed-domain",
"MRC,",
"mainly",
"due",
"to",
"the",
"lack",
"of",
"large-scale",
"training",
"data.",
"In",
"this",
"paper,",
"we",
"introduce",
"a",
"multi-target",
"MRC",
"task",
"for",
"the",
"medical",
"domain,",
"whose",
"goal",
"is",
"to",
"predict",
"answers",
"to",
"medical",
"questions",
"and",
"the",
"corresponding",
"support",
"sentences",
"from",
"medical",
"information",
"sources",
"simultaneously,",
"in",
"order",
"to",
"ensure",
"the",
"high",
"reliability",
"of",
"medical",
"knowledge",
"serving.",
"A",
"high-quality",
"dataset",
"is",
"manually",
"constructed",
"for",
"the",
"purpose,",
"named",
"Multi-task",
"Chinese",
"Medical",
"MRC",
"dataset",
"(CMedMRC),",
"with",
"detailed",
"analysis",
"conducted.",
"We",
"further",
"propose",
"the",
"Chinese",
"medical",
"BERT",
"model",
"for",
"the",
"task",
"(CMedBERT",
"),",
"which",
"fuses",
"medical",
"knowledge",
"into",
"pre-trained",
"language",
"models",
"by",
"the",
"dynamic",
"fusion",
"mechanism",
"of",
"heterogeneous",
"features",
"and",
"the",
"multi-task",
"learning",
"strategy.",
"Experiments",
"show",
"that",
"CMedBERT",
"consistently",
"outperforms",
"strong",
"baselines",
"by",
"fusing",
"context-aware",
"and",
"knowledge-aware",
"token",
"representations."
] |
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[
"Transfer",
"learning",
"---",
"transferring",
"learned",
"knowledge",
"---",
"has",
"brought",
"a",
"paradigm",
"shift",
"in",
"the",
"way",
"models",
"are",
"trained.",
"The",
"lucrative",
"benefits",
"of",
"improved",
"accuracy",
"and",
"reduced",
"training",
"time",
"have",
"shown",
"promise",
"in",
"training",
"models",
"with",
"constrained",
"computational",
"resources",
"and",
"fewer",
"training",
"samples.",
"Specifically,",
"publicly",
"available",
"text-based",
"models",
"such",
"as",
"GloVe",
"and",
"BERT",
"that",
"are",
"trained",
"on",
"large",
"corpus",
"of",
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"have",
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"In",
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"we",
"ask,",
"can\tO\ntransfer\tO\nlearning\tO\nin\tO\ntext\tO\nprediction\tO\nmodels\tO\nbe\tO\nexploited\tO\nto\tO\nperform\tO\nmisclassification\tO\nattacks?",
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"our",
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"present",
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"To",
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"our",
"knowledge,",
"ours",
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"the",
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"work",
"to",
"show",
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"learning",
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"sentence-based",
"teacher",
"models",
"increase",
"the",
"susceptibility",
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"student",
"models",
"to",
"misclassification",
"attacks.",
"First,",
"we",
"propose",
"a",
"novel",
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"based",
"attack",
"algorithm",
"for",
"generating",
"adversarial",
"examples",
"against",
"student",
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"word-level",
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"On",
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"we",
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"Movie",
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"41%",
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"Next,",
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"BERT",
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"and",
"39%",
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"Thus,",
"our",
"results",
"motivate",
"the",
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"for",
"designing",
"training",
"techniques",
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"are",
"robust",
"to",
"unintended",
"feature",
"learning,",
"specifically",
"for",
"transfer",
"learned",
"models."
] |
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[
"In",
"this",
"paper",
"we",
"propose",
"a",
"method",
"for",
"improving",
"pedestrian",
"detection",
"in",
"the",
"thermal",
"domain",
"using",
"two",
"stages:",
"first,",
"a",
"generative",
"data",
"augmentation",
"approach",
"is",
"used,",
"then",
"a",
"domain",
"adaptation",
"method",
"using",
"generated",
"data",
"adapts",
"an",
"RGB",
"pedestrian",
"detector.",
"Our",
"model,",
"based",
"on",
"the",
"Least-Squares",
"Generative",
"Adversarial",
"Network,",
"is",
"trained",
"to",
"synthesize",
"realistic",
"thermal",
"versions",
"of",
"input",
"RGB",
"images",
"which",
"are",
"then",
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"to",
"augment",
"the",
"limited",
"amount",
"of",
"labeled",
"thermal",
"pedestrian",
"images",
"available",
"for",
"training.",
"We",
"apply",
"our",
"generative",
"data",
"augmentation",
"strategy",
"in",
"order",
"to",
"adapt",
"a",
"pretrained",
"YOLOv3",
"pedestrian",
"detector",
"to",
"detection",
"in",
"the",
"thermal-only",
"domain.",
"Experimental",
"results",
"demonstrate",
"the",
"effectiveness",
"of",
"our",
"approach:",
"using",
"less",
"than",
"50\\%",
"of",
"available",
"real",
"thermal",
"training",
"data,",
"and",
"relying",
"on",
"synthesized",
"data",
"generated",
"by",
"our",
"model",
"in",
"the",
"domain",
"adaptation",
"phase,",
"our",
"detector",
"achieves",
"state-of-the-art",
"results",
"on",
"the",
"KAIST",
"Multispectral",
"Pedestrian",
"Detection",
"Benchmark;",
"even",
"if",
"more",
"real",
"thermal",
"data",
"is",
"available",
"adding",
"GAN",
"generated",
"images",
"to",
"the",
"training",
"data",
"results",
"in",
"improved",
"performance,",
"thus",
"showing",
"that",
"these",
"images",
"act",
"as",
"an",
"effective",
"form",
"of",
"data",
"augmentation.",
"To",
"the",
"best",
"of",
"our",
"knowledge,",
"our",
"detector",
"achieves",
"the",
"best",
"single-modality",
"detection",
"results",
"on",
"KAIST",
"with",
"respect",
"to",
"the",
"state-of-the-art."
] |
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[
"We",
"describe",
"a",
"practical",
"parser",
"for",
"unrestricted",
"dependencies",
".",
"The",
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"creates",
"links",
"between",
"words",
"and",
"names",
"the",
"links",
"according",
"to",
"their",
"syntactic",
"functions",
".",
"We",
"first",
"describe",
"the",
"older",
"Constraint",
"Grammar",
"parser",
"where",
"many",
"of",
"the",
"ideas",
"come",
"from",
".",
"Then",
"we",
"proceed",
"to",
"describe",
"the",
"central",
"ideas",
"of",
"our",
"new",
"parser",
".",
"Finally",
",",
"the",
"parser",
"is",
"evaluated",
"."
] |
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[
"Recent",
"advances",
"with",
"language",
"models",
"(e.g.",
"BERT",
",",
"XLNet,",
"...),",
"have",
"allowed",
"surpassing",
"human",
"performance",
"on",
"complex",
"NLP",
"tasks",
"such",
"as",
"Reading",
"Comprehension.",
"However,",
"labeled",
"datasets",
"for",
"training",
"are",
"available",
"mostly",
"in",
"English",
"which",
"makes",
"it",
"difficult",
"to",
"acknowledge",
"progress",
"in",
"other",
"languages.",
"Fortunately,",
"models",
"are",
"now",
"pre-trained",
"on",
"unlabeled",
"data",
"from",
"hundreds",
"of",
"languages",
"and",
"exhibit",
"interesting",
"transfer",
"abilities",
"from",
"one",
"language",
"to",
"another.",
"In",
"this",
"paper,",
"we",
"show",
"that",
"multilingual",
"BERT",
"is",
"naturally",
"capable",
"of",
"zero-shot",
"transfer",
"for",
"an",
"extractive",
"Question",
"Answering",
"task",
"(eQA)",
"from",
"English",
"to",
"other",
"languages.",
"More",
"specifically,",
"it",
"outperforms",
"the",
"best",
"previously",
"known",
"baseline",
"for",
"transfer",
"to",
"Japanese",
"and",
"French.",
"Moreover,",
"using",
"a",
"recently",
"published",
"large",
"eQA",
"French",
"dataset,",
"we",
"are",
"able",
"to",
"further",
"show",
"that",
"-1",
"zero-shot",
"transfer",
"provides",
"results",
"really",
"close",
"to",
"a",
"direct",
"training",
"on",
"the",
"target",
"language",
"and",
"-2",
"combination",
"of",
"transfer",
"and",
"training",
"on",
"target",
"is",
"the",
"best",
"option",
"overall.",
"We",
"finally",
"present",
"a",
"practical",
"application:",
"a",
"multilingual",
"conversational",
"agent",
"called",
"Kate",
"which",
"answers",
"to",
"HR-related",
"questions",
"in",
"several",
"languages",
"directly",
"from",
"the",
"content",
"of",
"intranet",
"pages."
] |
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[
"Quantization",
"is",
"considered",
"as",
"one",
"of",
"the",
"most",
"effective",
"methods",
"to",
"optimize",
"the",
"inference",
"cost",
"of",
"neural",
"network",
"models",
"for",
"their",
"deployment",
"to",
"mobile",
"and",
"embedded",
"systems,",
"which",
"have",
"tight",
"resource",
"constraints.",
"In",
"such",
"approaches,",
"it",
"is",
"critical",
"to",
"provide",
"low-cost",
"quantization",
"under",
"a",
"tight",
"accuracy",
"loss",
"constraint",
"(e.g.,",
"1%).",
"In",
"this",
"paper,",
"we",
"propose",
"a",
"novel",
"method",
"for",
"quantizing",
"weights",
"and",
"activations",
"based",
"on",
"the",
"concept",
"of",
"weighted",
"entropy.",
"Unlike",
"recent",
"work",
"on",
"binary-weight",
"neural",
"networks,",
"our",
"approach",
"is",
"multi-bit",
"quantization,",
"in",
"which",
"weights",
"and",
"activations",
"can",
"be",
"quantized",
"by",
"any",
"number",
"of",
"bits",
"depending",
"on",
"the",
"target",
"accuracy.",
"This",
"facilitates",
"much",
"more",
"flexible",
"exploitation",
"of",
"accuracy-performance",
"trade-off",
"provided",
"by",
"different",
"levels",
"of",
"quantization.",
"Moreover,",
"our",
"scheme",
"provides",
"an",
"automated",
"quantization",
"flow",
"based",
"on",
"conventional",
"training",
"algorithms,",
"which",
"greatly",
"reduces",
"the",
"design-time",
"effort",
"to",
"quantize",
"the",
"network.",
"According",
"to",
"our",
"extensive",
"evaluations",
"based",
"on",
"practical",
"neural",
"network",
"models",
"for",
"image",
"classification",
"(AlexNet,",
"GoogLeNet",
"and",
"ResNet-50/101),",
"object",
"detection",
"(R-FCN",
"with",
"50-layer",
"ResNet),",
"and",
"language",
"modeling",
"(an",
"LSTM",
"network),",
"our",
"method",
"achieves",
"significant",
"reductions",
"in",
"both",
"the",
"model",
"size",
"and",
"the",
"amount",
"of",
"computation",
"with",
"minimal",
"accuracy",
"loss.",
"Also,",
"compared",
"to",
"existing",
"quantization",
"schemes,",
"ours",
"provides",
"higher",
"accuracy",
"with",
"a",
"similar",
"resource",
"constraint",
"and",
"requires",
"much",
"lower",
"design",
"effort."
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"paper",
"describes",
"the",
"Neural",
"Machine",
"Translation",
"systems",
"used",
"by",
"IIIT",
"Hyderabad",
"(CVIT-MT)",
"for",
"the",
"translation",
"tasks",
"part",
"of",
"WAT-2019.",
"We",
"participated",
"in",
"tasks",
"pertaining",
"to",
"Indian",
"languages",
"and",
"submitted",
"results",
"for",
"English-Hindi,",
"Hindi-English,",
"English-Tamil",
"and",
"Tamil-English",
"language",
"pairs.",
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"architecture",
"experimenting",
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"multilingual",
"models",
"and",
"methods",
"for",
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"into",
"morphemes,",
"early",
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"the",
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"Neural",
"MD",
"may",
"be",
"addressed",
"as",
"a",
"simple",
"pipeline,",
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"segmentation",
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"sequence",
"tagging,",
"or",
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"end-to-end",
"model,",
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"propagation,",
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"units",
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"morphemes.",
"This",
"paper",
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"architecture",
"that",
"combines",
"the",
"symbolic",
"knowledge",
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"morphemes",
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"the",
"learning",
"capacity",
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"neural",
"end-to-end",
"modeling.",
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"a",
"new,",
"general",
"and",
"easy-to-implement",
"Pointer",
"Network",
"model",
"where",
"the",
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"lattice",
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"tagging,",
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"and",
"Turkish",
"texts,",
"based",
"on",
"their",
"respective",
"Universal",
"Dependencies",
"(UD)",
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"Our",
"experiments",
"show",
"that",
"with",
"complete",
"lattices,",
"our",
"model",
"outperforms",
"all",
"shared-task",
"results",
"on",
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"and",
"tagging",
"these",
"languages.",
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"the",
"SPMRL",
"treebank,",
"our",
"model",
"outperforms",
"all",
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"results",
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"MD",
"in",
"realistic",
"scenarios."
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"This",
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"-",
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"-",
"caused",
"by",
"Diabetic",
"Retinopathy",
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"the",
"eyes",
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"diabetic",
"patients.",
"We",
"make",
"use",
"of",
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"Neural",
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"mask",
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"the",
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"fundus",
"images.",
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"our",
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"database",
"out",
"of",
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"EX",
"and",
"e-ophtha",
"MA",
"and",
"tweak",
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"R-CNN",
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"detect",
"small",
"lesions.",
"Moreover,",
"we",
"employ",
"data",
"augmentation",
"and",
"the",
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"ResNet101",
"to",
"compensate",
"for",
"our",
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"showing",
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"clinicians",
"and",
"ophthalmologist",
"in",
"the",
"process",
"of",
"detecting",
"and",
"treating",
"the",
"infamous",
"DR."
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[
"Graph",
"convolutional",
"networks",
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"s),",
"which",
"generalize",
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"to",
"more",
"generic",
"non-Euclidean",
"structures,",
"have",
"achieved",
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"performance",
"for",
"skeleton-based",
"action",
"recognition.",
"However,",
"there",
"still",
"exist",
"several",
"issues",
"in",
"the",
"previous",
"GCN",
"#NAME?",
"models.",
"First,",
"the",
"topology",
"of",
"the",
"graph",
"is",
"set",
"heuristically",
"and",
"fixed",
"over",
"all",
"the",
"model",
"layers",
"and",
"input",
"data.",
"This",
"may",
"not",
"be",
"suitable",
"for",
"the",
"hierarchy",
"of",
"the",
"GCN",
"model",
"and",
"the",
"diversity",
"of",
"the",
"data",
"in",
"action",
"recognition",
"tasks.",
"Second,",
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"second-order",
"information",
"of",
"the",
"skeleton",
"data,",
"i.e.,",
"the",
"length",
"and",
"orientation",
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"the",
"bones,",
"is",
"rarely",
"investigated,",
"which",
"is",
"naturally",
"more",
"informative",
"and",
"discriminative",
"for",
"the",
"human",
"action",
"recognition.",
"In",
"this",
"work,",
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"propose",
"a",
"novel",
"multi-stream",
"attention-enhanced",
"adaptive",
"graph",
"convolutional",
"neural",
"network",
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")",
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"skeleton-based",
"action",
"recognition.",
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"graph",
"topology",
"in",
"our",
"model",
"can",
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"uniformly",
"or",
"individually",
"learned",
"based",
"on",
"the",
"input",
"data",
"in",
"an",
"end-to-end",
"manner.",
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"data-driven",
"approach",
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"the",
"flexibility",
"of",
"the",
"model",
"for",
"graph",
"construction",
"and",
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"data",
"samples.",
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"convolutional",
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"attention",
"module,",
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"pay",
"more",
"attention",
"to",
"important",
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"frames",
"and",
"features.",
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"information",
"of",
"both",
"the",
"joints",
"and",
"bones,",
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"motion",
"information,",
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"modeled",
"in",
"a",
"multi-stream",
"framework,",
"which",
"shows",
"notable",
"improvement",
"for",
"the",
"recognition",
"accuracy.",
"Extensive",
"experiments",
"on",
"the",
"two",
"large-scale",
"datasets,",
"NTU-RGBD",
"and",
"Kinetics-Skeleton,",
"demonstrate",
"that",
"the",
"performance",
"of",
"our",
"model",
"exceeds",
"the",
"state-of-the-art",
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"a",
"significant",
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[
"This",
"paper",
"presents",
"an",
"approach",
"for",
"developing",
"a",
"task-oriented",
"dialog",
"system",
"for",
"less-resourced",
"languages",
"in",
"scenarios",
"where",
"training",
"data",
"is",
"not",
"available.",
"Both",
"intent",
"classification",
"and",
"slot",
"filling",
"are",
"tackled.",
"We",
"project",
"the",
"existing",
"annotations",
"in",
"rich-resource",
"languages",
"by",
"means",
"of",
"Neural",
"Machine",
"Translation",
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"and",
"posterior",
"word",
"alignments.",
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"then",
"compare",
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"on",
"the",
"projected",
"monolingual",
"data",
"with",
"direct",
"model",
"transfer",
"alternatives.",
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"and",
"slot",
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"architecture",
"or",
"by",
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"BERT",
"transformer",
"models.",
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"learnt",
"exclusively",
"from",
"Basque",
"projected",
"data",
"provide",
"better",
"accuracies",
"for",
"slot",
"filling.",
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"Basque",
"projected",
"train",
"data",
"with",
"rich-resource",
"languages",
"data",
"outperforms",
"consistently",
"models",
"trained",
"solely",
"on",
"projected",
"data",
"for",
"intent",
"classification.",
"At",
"any",
"rate,",
"we",
"achieve",
"competitive",
"performance",
"in",
"both",
"tasks,",
"with",
"accuracies",
"of",
"81{\\%}",
"for",
"intent",
"classification",
"and",
"77{\\%}",
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"filling."
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"Transformer",
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"been",
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"of",
"its",
"large",
"capacity",
"and",
"parallel",
"training",
"of",
"sequence",
"generation.",
"However,",
"the",
"deployment",
"of",
"Transformer",
"is",
"challenging",
"because",
"different",
"scenarios",
"require",
"models",
"of",
"different",
"complexities",
"and",
"scales.",
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"training",
"multiple",
"Transformer",
"s",
"is",
"redundant",
"in",
"terms",
"of",
"both",
"computation",
"and",
"memory.",
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"this",
"paper,",
"we",
"propose",
"a",
"novel",
"Scalable",
"Transformer",
"s,",
"which",
"naturally",
"contains",
"sub-Transformer",
"s",
"of",
"different",
"scales",
"and",
"have",
"shared",
"parameters.",
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"sub-Transformer",
"can",
"be",
"easily",
"obtained",
"by",
"cropping",
"the",
"parameters",
"of",
"the",
"largest",
"Transformer",
".",
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"three-stage",
"training",
"scheme",
"is",
"proposed",
"to",
"tackle",
"the",
"difficulty",
"of",
"training",
"the",
"Scalable",
"Transformer",
"s,",
"which",
"introduces",
"additional",
"supervisions",
"from",
"word-level",
"and",
"sequence-level",
"self-distillation.",
"Extensive",
"experiments",
"were",
"conducted",
"on",
"WMT",
"EN-De",
"and",
"En-Fr",
"to",
"validate",
"our",
"proposed",
"Scalable",
"Transformer",
"s."
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[
"Low-resource",
"languages",
"such",
"as",
"Filipino",
"suffer",
"from",
"data",
"scarcity",
"which",
"makes",
"it",
"challenging",
"to",
"develop",
"NLP",
"applications",
"for",
"Filipino",
"language.",
"The",
"use",
"of",
"Transfer",
"Learning",
"(TL)",
"techniques",
"alleviates",
"this",
"problem",
"in",
"low-resource",
"setting.",
"In",
"recent",
"years,",
"transformer-based",
"models",
"are",
"proven",
"to",
"be",
"effective",
"in",
"low-resource",
"tasks",
"but",
"faces",
"challenges",
"in",
"accessibility",
"due",
"to",
"its",
"high",
"compute",
"and",
"memory",
"requirements.",
"For",
"this",
"reason,",
"there's",
"a",
"need",
"for",
"a",
"cheaper",
"but",
"effective",
"alternative.",
"This",
"paper",
"has",
"three",
"contributions.",
"First,",
"release",
"a",
"pre-trained",
"AWD-LSTM",
"language",
"model",
"for",
"Filipino",
"language.",
"Second,",
"benchmark",
"AWD-LSTM",
"in",
"the",
"Hate",
"Speech",
"classification",
"task",
"and",
"show",
"that",
"it",
"performs",
"on",
"par",
"with",
"transformer-based",
"models.",
"Third,",
"analyze",
"the",
"the",
"performance",
"of",
"AWD-LSTM",
"in",
"low-resource",
"setting",
"using",
"degradation",
"test",
"and",
"compare",
"it",
"with",
"transformer-based",
"models.",
"-----",
"Ang",
"mga",
"low-resource",
"languages",
"tulad",
"ng",
"Filipino",
"ay",
"gipit",
"sa",
"accessible",
"na",
"datos",
"kaya't",
"mahirap",
"gumawa",
"ng",
"mga",
"applications",
"sa",
"wikang",
"ito.",
"Ang",
"mga",
"Transfer",
"Learning",
"(TL)",
"techniques",
"ay",
"malaking",
"tulong",
"para",
"sa",
"low-resource",
"setting",
"o",
"mga",
"pagkakataong",
"gipit",
"sa",
"datos.",
"Sa",
"mga",
"nagdaang",
"taon,",
"nanaig",
"ang",
"mga",
"transformer-based",
"TL",
"techniques",
"pagdating",
"sa",
"low-resource",
"tasks",
"ngunit",
"ito",
"ay",
"mataas",
"na",
"compute",
"and",
"memory",
"requirements",
"kaya",
"nangangailangan",
"ng",
"mas",
"mura",
"pero",
"epektibong",
"alternatibo.",
"Ang",
"papel",
"na",
"ito",
"ay",
"may",
"tatlong",
"kontribusyon.",
"Una,",
"maglabas",
"ng",
"pre-trained",
"AWD-LSTM",
"language",
"model",
"sa",
"wikang",
"Filipino",
"upang",
"maging",
"tuntungan",
"sa",
"pagbuo",
"ng",
"mga",
"NLP",
"applications",
"sa",
"wikang",
"Filipino.",
"Pangalawa,",
"mag",
"benchmark",
"ng",
"AWD-LSTM",
"sa",
"Hate",
"Speech",
"classification",
"task",
"at",
"ipakita",
"na",
"kayang",
"nitong",
"makipagsabayan",
"sa",
"mga",
"transformer-based",
"models.",
"Pangatlo,",
"suriin",
"ang",
"performance",
"ng",
"AWD-LSTM",
"sa",
"low-resource",
"setting",
"gamit",
"ang",
"degradation",
"test",
"at",
"ikumpara",
"ito",
"sa",
"mga",
"transformer-based",
"models."
] |
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[
"Electroencephalography",
"(EEG",
")",
"is",
"an",
"important",
"clinical",
"tool",
"for",
"reviewing",
"sleep-wake",
"cycling",
"in",
"neonates",
"in",
"intensive",
"care.",
"Trace",
"alternant",
"(TA)-a",
"characteristic",
"pattern",
"of",
"EEG",
"activity",
"during",
"quiet",
"sleep",
"in",
"term",
"neonates-is",
"defined",
"by",
"alternating",
"periods",
"of",
"short-duration,",
"high-voltage",
"activity",
"(bursts)",
"separated",
"by",
"lower-voltage",
"activity",
"(inter-bursts).",
"This",
"study",
"presents",
"a",
"novel",
"approach",
"for",
"detecting",
"TA",
"activity",
"by",
"first",
"detecting",
"the",
"inter-bursts",
"and",
"then",
"processing",
"the",
"temporal",
"map",
"of",
"the",
"bursts",
"and",
"inter-bursts.",
"EEG",
"recordings",
"from",
"72",
"healthy",
"term",
"neonates",
"were",
"used",
"to",
"develop",
"and",
"evaluate",
"performance",
"of",
"1)",
"an",
"inter-burst",
"detection",
"method",
"which",
"is",
"then",
"used",
"for",
"2)",
"detection",
"of",
"TA",
"activity.",
"First,",
"multiple",
"amplitude",
"and",
"spectral",
"features",
"were",
"combined",
"using",
"a",
"support",
"vector",
"machine",
"(SVM",
")",
"to",
"classify",
"bursts",
"from",
"inter-bursts",
"within",
"TA",
"activity,",
"resulting",
"in",
"a",
"median",
"area",
"under",
"the",
"operating",
"characteristic",
"curve",
"(AUC)",
"of",
"0.95",
"(95%",
"confidence",
"interval,",
"CI:",
"0.93",
"to",
"0.98).",
"Second,",
"post-processing",
"of",
"the",
"continuous",
"SVM",
"output,",
"the",
"confidence",
"score,",
"was",
"used",
"to",
"produce",
"a",
"TA",
"envelope.",
"This",
"envelope",
"was",
"used",
"to",
"detect",
"TA",
"activity",
"within",
"the",
"continuous",
"EEG",
"with",
"a",
"median",
"AUC",
"of",
"0.84",
"(95%",
"CI:",
"0.8",
"to",
"0.88).",
"These",
"results",
"validate",
"how",
"an",
"inter-burst",
"detection",
"approach",
"combined",
"with",
"post",
"processing",
"can",
"be",
"used",
"to",
"classify",
"TA",
"activity.",
"Detecting",
"the",
"presence",
"or",
"absence",
"of",
"TA",
"will",
"help",
"quantify",
"disruption",
"of",
"the",
"clinically",
"important",
"sleep-wake",
"cycle."
] |
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[
"Current",
"graph-based",
"approaches",
"to",
"automatic",
"text",
"summarization",
",",
"such",
"as",
"LexRank",
"and",
"TextRank",
",",
"assume",
"a",
"static",
"graph",
"which",
"does",
"not",
"model",
"how",
"the",
"input",
"texts",
"emerge",
".",
"A",
"suitable",
"evolutionary",
"text",
"graph",
"model",
"may",
"impart",
"a",
"better",
"understanding",
"of",
"the",
"texts",
"and",
"improve",
"the",
"summarization",
"process",
".",
"We",
"propose",
"a",
"timestamped",
"graph",
"-LRB-",
"TSG",
"-RRB-",
"model",
"that",
"is",
"motivated",
"by",
"human",
"writing",
"and",
"reading",
"processes",
",",
"and",
"show",
"how",
"text",
"units",
"in",
"this",
"model",
"emerge",
"over",
"time",
".",
"In",
"our",
"model",
",",
"the",
"graphs",
"used",
"by",
"LexRank",
"and",
"TextRank",
"are",
"specific",
"instances",
"of",
"our",
"timestamped",
"graph",
"with",
"particular",
"parameter",
"settings",
".",
"We",
"apply",
"timestamped",
"graphs",
"on",
"the",
"standard",
"DUC",
"multi-document",
"text",
"summarization",
"task",
"and",
"achieve",
"comparable",
"results",
"to",
"the",
"state",
"of",
"the",
"art",
"."
] |
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[
"Transliteration",
"is",
"the",
"task",
"of",
"converting",
"a",
"word",
"from",
"one",
"alphabetic",
"script",
"to",
"another",
".",
"We",
"present",
"a",
"novel",
",",
"substring-based",
"approach",
"to",
"transliteration",
",",
"inspired",
"by",
"phrasebased",
"models",
"of",
"machine",
"translation",
".",
"We",
"investigate",
"two",
"implementations",
"of",
"substringbased",
"transliteration",
":",
"a",
"dynamic",
"programming",
"algorithm",
",",
"and",
"a",
"finite-state",
"transducer",
".",
"We",
"show",
"that",
"our",
"substring-based",
"transducer",
"not",
"only",
"outperforms",
"a",
"state-of-the-art",
"letterbased",
"approach",
"by",
"a",
"significant",
"margin",
",",
"but",
"is",
"also",
"orders",
"of",
"magnitude",
"faster",
"."
] |
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[
"Graph",
"Neural",
"Networks",
"(GNNs)",
"are",
"the",
"first",
"choice",
"methods",
"for",
"graph",
"machine",
"learning",
"problems",
"thanks",
"to",
"their",
"ability",
"to",
"learn",
"state-of-the-art",
"level",
"representations",
"from",
"graph-structured",
"data.",
"However,",
"centralizing",
"a",
"massive",
"amount",
"of",
"real-world",
"graph",
"data",
"for",
"GNN",
"training",
"is",
"prohibitive",
"due",
"to",
"user-side",
"privacy",
"concerns,",
"regulation",
"restrictions,",
"and",
"commercial",
"competition.",
"Federated",
"Learning",
"is",
"the",
"de-facto",
"standard",
"for",
"collaborative",
"training",
"of",
"machine",
"learning",
"models",
"over",
"many",
"distributed",
"edge",
"devices",
"without",
"the",
"need",
"for",
"centralization.",
"Nevertheless,",
"training",
"graph",
"neural",
"networks",
"in",
"a",
"federated",
"setting",
"is",
"vaguely",
"defined",
"and",
"brings",
"statistical",
"and",
"systems",
"challenges.",
"This",
"work",
"proposes",
"SpreadGNN,",
"a",
"novel",
"multi-task",
"federated",
"training",
"framework",
"capable",
"of",
"operating",
"in",
"the",
"presence",
"of",
"partial",
"labels",
"and",
"absence",
"of",
"a",
"central",
"server",
"for",
"the",
"first",
"time",
"in",
"the",
"literature.",
"SpreadGNN",
"extends",
"federated",
"multi-task",
"learning",
"to",
"realistic",
"serverless",
"settings",
"for",
"GNNs,",
"and",
"utilizes",
"a",
"novel",
"optimization",
"algorithm",
"with",
"a",
"convergence",
"guarantee,",
"Decentralized",
"Periodic",
"Averaging",
"SGD",
"(DPA-SGD",
"),",
"to",
"solve",
"decentralized",
"multi-task",
"learning",
"problems.",
"We",
"empirically",
"demonstrate",
"the",
"efficacy",
"of",
"our",
"framework",
"on",
"a",
"variety",
"of",
"non-I.I.D.",
"distributed",
"graph-level",
"molecular",
"property",
"prediction",
"datasets",
"with",
"partial",
"labels.",
"Our",
"results",
"show",
"that",
"SpreadGNN",
"outperforms",
"GNN",
"models",
"trained",
"over",
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"programming",
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"Furthermore,",
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"constrainedmeasures",
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"In",
"this",
"paper,",
"we",
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"measures",
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"Time",
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")",
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"data",
"sets,",
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"time",
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"We",
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"its",
"unconstrained",
"counterpart,",
"in",
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"1-nearest",
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"measures,",
"highlighting",
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"parameters",
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"achieve",
"a",
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"speed",
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"accuracy."
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"Sound",
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"wide",
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"video",
"indexing,",
"etc.",
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"mainly",
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"frame-level",
"predictions,",
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"sequence",
"multi-label",
"classification",
"problem,",
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"boundary",
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"and",
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"tagging",
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"labeled",
"data",
"to",
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"the",
"model.",
"Besides,",
"it",
"needs",
"post-processing",
"and",
"cannot",
"be",
"trained",
"in",
"an",
"end-to-end",
"way.",
"This",
"paper",
"firstly",
"presents",
"the",
"1D",
"Detection",
"Transformer",
"(1D-DETR),",
"inspired",
"by",
"Detection",
"Transformer",
".",
"Furthermore,",
"given",
"the",
"characteristics",
"of",
"SED,",
"the",
"audio",
"query",
"and",
"a",
"one-to-many",
"matching",
"strategy",
"for",
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"the",
"model",
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"added",
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"1D-DETR",
"to",
"form",
"the",
"model",
"of",
"Sound",
"Event",
"Detection",
"Transformer",
"(SEDT),",
"which",
"generates",
"event-level",
"predictions,",
"end-to-end",
"detection.",
"Experiments",
"are",
"conducted",
"on",
"the",
"URBAN-SED",
"dataset",
"and",
"the",
"DCASE2019",
"Task4",
"dataset,",
"and",
"both",
"experiments",
"have",
"achieved",
"competitive",
"results",
"compared",
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"SOTA",
"models.",
"The",
"application",
"of",
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"on",
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"shows",
"that",
"it",
"can",
"be",
"used",
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"a",
"framework",
"for",
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"signal",
"detection",
"and",
"may",
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"extended",
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"This",
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"multi-domain",
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"guidelines",
"for",
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"nested",
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"cross-domain",
"learning",
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"Named",
"Entity",
"Recognition",
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"task.",
"We",
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"German",
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"annotation",
"from",
"scratch.",
"We",
"examine",
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"multilingual",
"BERT",
",",
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"study",
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"NER",
".",
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"1)",
"the",
"most",
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"is",
"multi-task",
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"the",
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"task",
"of",
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"a",
"set",
"of",
"labels",
"corresponding",
"to",
"objects,",
"attributes",
"or",
"other",
"entities",
"present",
"in",
"an",
"image.",
"In",
"this",
"work",
"we",
"propose",
"the",
"Classification",
"Transformer",
"(C-Tran),",
"a",
"general",
"framework",
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"image",
"classification",
"that",
"leverages",
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"s",
"to",
"exploit",
"the",
"complex",
"dependencies",
"among",
"visual",
"features",
"and",
"labels.",
"Our",
"approach",
"consists",
"of",
"a",
"Transformer",
"encoder",
"trained",
"to",
"predict",
"a",
"set",
"of",
"target",
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"input",
"set",
"of",
"masked",
"labels,",
"and",
"visual",
"features",
"from",
"a",
"convolutional",
"neural",
"network.",
"A",
"key",
"ingredient",
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"our",
"method",
"is",
"a",
"label",
"mask",
"training",
"objective",
"that",
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"ternary",
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"the",
"labels",
"as",
"positive,",
"negative,",
"or",
"unknown",
"during",
"training.",
"Our",
"model",
"shows",
"state-of-the-art",
"performance",
"on",
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"datasets",
"such",
"as",
"COCO",
"and",
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"Genome.",
"Moreover,",
"because",
"our",
"model",
"explicitly",
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"the",
"uncertainty",
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"labels",
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"training,",
"it",
"is",
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"general",
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"allowing",
"us",
"to",
"produce",
"improved",
"results",
"for",
"images",
"with",
"partial",
"or",
"extra",
"label",
"annotations",
"during",
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"demonstrate",
"this",
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"capability",
"in",
"the",
"COCO,",
"Visual",
"Genome,",
"News500,",
"and",
"CUB",
"image",
"datasets."
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"The",
"goal",
"of",
"self-supervised",
"learning",
"from",
"images",
"is",
"to",
"construct",
"image",
"representations",
"that",
"are",
"semantically",
"meaningful",
"via",
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"tasks",
"that",
"do",
"not",
"require",
"semantic",
"annotations",
"for",
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"large",
"training",
"set",
"of",
"images.",
"Many",
"pretext",
"tasks",
"lead",
"to",
"representations",
"that",
"are",
"covariant",
"with",
"image",
"transformations.",
"We",
"argue",
"that,",
"instead,",
"semantic",
"representations",
"ought",
"to",
"be",
"invariant",
"under",
"such",
"transformations.",
"Specifically,",
"we",
"develop",
"Pretext-Invariant",
"Representation",
"Learning",
"(PIRL",
",",
"pronounced",
"as",
"pearl)",
"that",
"learns",
"invariant",
"representations",
"based",
"on",
"pretext",
"tasks.",
"We",
"use",
"PIRL",
"with",
"a",
"commonly",
"used",
"pretext",
"task",
"that",
"involves",
"solving",
"jigsaw",
"puzzles.",
"We",
"find",
"that",
"PIRL",
"substantially",
"improves",
"the",
"semantic",
"quality",
"of",
"the",
"learned",
"image",
"representations.",
"Our",
"approach",
"sets",
"a",
"new",
"state-of-the-art",
"in",
"self-supervised",
"learning",
"from",
"images",
"on",
"several",
"popular",
"benchmarks",
"for",
"self-supervised",
"learning.",
"Despite",
"being",
"unsupervised,",
"PIRL",
"outperforms",
"supervised",
"pre-training",
"in",
"learning",
"image",
"representations",
"for",
"object",
"detection.",
"Altogether,",
"our",
"results",
"demonstrate",
"the",
"potential",
"of",
"self-supervised",
"learning",
"of",
"image",
"representations",
"with",
"good",
"invariance",
"properties."
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"consisting",
"of",
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"visual-optical",
"(VIS)",
"and",
"thermal",
"infrared",
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"are",
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"applications",
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"driving",
"or",
"visual",
"surveillance.",
"Such",
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"be",
"used",
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"especially",
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"small-scaled,",
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"current",
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"R-CNN",
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"network",
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"anchor",
"boxes",
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"localization",
"and",
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"classification",
"network",
"for",
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"object",
"category.",
"In",
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"paper",
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"method",
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"effective",
"and",
"efficient",
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"in",
"an",
"adapted",
"single-stage",
"anchor-free",
"base",
"architecture.",
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"pedestrian",
"representations",
"based",
"on",
"object",
"center",
"and",
"scale",
"rather",
"than",
"direct",
"bounding",
"box",
"predictions.",
"In",
"this",
"way,",
"we",
"can",
"both",
"simplify",
"the",
"network",
"architecture",
"and",
"achieve",
"higher",
"detection",
"performance,",
"especially",
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"pedestrians",
"under",
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"or",
"at",
"low",
"object",
"resolution.",
"In",
"addition,",
"we",
"provide",
"a",
"study",
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"data",
"augmentation",
"techniques",
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"improve",
"the",
"commonly",
"used",
"augmentations.",
"The",
"results",
"show",
"our",
"method's",
"effectiveness",
"in",
"detecting",
"small-scaled",
"pedestrians.",
"We",
"achieve",
"5.68%",
"log-average",
"miss",
"rate",
"in",
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"to",
"the",
"best",
"current",
"state-of-the-art",
"of",
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"on",
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"challenging",
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"Multispectral",
"Pedestrian",
"Detection",
"Benchmark.",
"Code:",
"https://github.com/HensoldtOptronicsCV/MultispectralPedestrianDetection"
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"Misinformation",
"of",
"COVID-19",
"is",
"prevalent",
"on",
"social",
"media",
"as",
"the",
"pandemic",
"unfolds,",
"and",
"the",
"associated",
"risks",
"are",
"extremely",
"high.",
"Thus,",
"it",
"is",
"critical",
"to",
"detect",
"and",
"combat",
"such",
"misinformation.",
"Recently,",
"deep",
"learning",
"models",
"using",
"natural",
"language",
"processing",
"techniques,",
"such",
"as",
"BERT",
"(Bidirectional",
"Encoder",
"Representations",
"from",
"Transformers),",
"have",
"achieved",
"great",
"successes",
"in",
"detecting",
"misinformation.",
"In",
"this",
"paper,",
"we",
"proposed",
"an",
"explainable",
"natural",
"language",
"processing",
"model",
"based",
"on",
"DistilBERT",
"and",
"SHAP",
"(Shapley",
"Additive",
"exPlanations)",
"to",
"combat",
"misinformation",
"about",
"COVID-19",
"due",
"to",
"their",
"efficiency",
"and",
"effectiveness.",
"First,",
"we",
"collected",
"a",
"dataset",
"of",
"984",
"claims",
"about",
"COVID-19",
"with",
"fact",
"checking.",
"By",
"augmenting",
"the",
"data",
"using",
"back-translation,",
"we",
"doubled",
"the",
"sample",
"size",
"of",
"the",
"dataset",
"and",
"the",
"DistilBERT",
"model",
"was",
"able",
"to",
"obtain",
"good",
"performance",
"(accuracy:",
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"areas",
"under",
"the",
"curve:",
"0.993)",
"in",
"detecting",
"misinformation",
"about",
"COVID-19.",
"Our",
"model",
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"also",
"tested",
"on",
"a",
"larger",
"dataset",
"for",
"AAAI2021",
"-",
"COVID-19",
"Fake",
"News",
"Detection",
"Shared",
"Task",
"and",
"obtained",
"good",
"performance",
"(accuracy:",
"0.938;",
"areas",
"under",
"the",
"curve:",
"0.985).",
"The",
"performance",
"on",
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"datasets",
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"better",
"than",
"traditional",
"machine",
"learning",
"models.",
"Second,",
"in",
"order",
"to",
"boost",
"public",
"trust",
"in",
"model",
"prediction,",
"we",
"employed",
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"was",
"further",
"evaluated",
"using",
"a",
"between-subjects",
"experiment",
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"(T),",
"text+SHAP",
"explanation",
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"explanation+source",
"and",
"evidence",
"(TSESE).",
"The",
"participants",
"were",
"significantly",
"more",
"likely",
"to",
"trust",
"and",
"share",
"information",
"related",
"to",
"COVID-19",
"in",
"the",
"TSE",
"and",
"TSESE",
"conditions",
"than",
"in",
"the",
"T",
"condition.",
"Our",
"results",
"provided",
"good",
"implications",
"in",
"detecting",
"misinformation",
"about",
"COVID-19",
"and",
"improving",
"public",
"trust."
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"This",
"paper",
"proposes",
"how",
"to",
"automatically",
"identify",
"Korean",
"comparative",
"sentences",
"from",
"text",
"documents",
".",
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"paper",
"first",
"investigates",
"many",
"comparative",
"sentences",
"referring",
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"previous",
"studies",
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"then",
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".",
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"result",
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"an",
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"."
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[
"The",
"ability",
"to",
"detect",
"small",
"objects",
"and",
"the",
"speed",
"of",
"the",
"object",
"detector",
"arevery",
"important",
"for",
"the",
"application",
"of",
"autonomous",
"driving,",
"and",
"in",
"this",
"paper,",
"wepropose",
"an",
"effective",
"yet",
"efficient",
"one-stage",
"detector,",
"which",
"gained",
"the",
"secondplace",
"in",
"the",
"Road",
"Object",
"Detection",
"competition",
"of",
"CVPR2018",
"workshop",
"-",
"Workshopof",
"Autonomous",
"Driving(WAD).",
"The",
"proposed",
"detector",
"inherits",
"the",
"architecture",
"ofSSD",
"and",
"introduces",
"a",
"novel",
"Comprehensive",
"Feature",
"Enhancement(CFE)",
"module",
"intoit.",
"Experimental",
"results",
"on",
"this",
"competition",
"dataset",
"as",
"well",
"as",
"the",
"MSCOCOdataset",
"demonstrate",
"that",
"the",
"proposed",
"detector",
"(named",
"CFENet)",
"performs",
"muchbetter",
"than",
"the",
"original",
"SSD",
"and",
"the",
"state-of-the-art",
"method",
"RefineDetespecially",
"for",
"small",
"objects,",
"while",
"keeping",
"high",
"efficiency",
"close",
"to",
"theoriginal",
"SSD",
".",
"Specifically,",
"the",
"single",
"scale",
"version",
"of",
"the",
"proposed",
"detectorcan",
"run",
"at",
"the",
"speed",
"of",
"21",
"fps,",
"while",
"the",
"multi-scale",
"version",
"with",
"larger",
"inputsize",
"achieves",
"the",
"mAP",
"29.69,",
"ranking",
"second",
"on",
"the",
"leaderboard"
] |
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[
"Autonomous",
"Driving",
"and",
"Simultaneous",
"Localization",
"and",
"Mapping(SLAM)",
"are",
"becoming",
"increasingly",
"important",
"in",
"real",
"world,",
"where",
"point",
"cloud-based",
"large",
"scale",
"place",
"recognition",
"is",
"the",
"spike",
"of",
"them.",
"Previous",
"place",
"recognition",
"methods",
"have",
"achieved",
"acceptable",
"performances",
"by",
"regarding",
"the",
"task",
"as",
"a",
"point",
"cloud",
"retrieval",
"problem.",
"However,",
"all",
"of",
"them",
"are",
"suffered",
"from",
"a",
"common",
"defect:",
"they",
"can't",
"handle",
"the",
"situation",
"when",
"the",
"point",
"clouds",
"are",
"rotated,",
"which",
"is",
"common,",
"e.g,",
"when",
"viewpoints",
"or",
"motorcycle",
"types",
"are",
"changed.",
"To",
"tackle",
"this",
"issue,",
"we",
"propose",
"an",
"Attentive",
"Rotation",
"Invariant",
"Convolution",
"(ARIConv)",
"in",
"this",
"paper.",
"The",
"ARIConv",
"adopts",
"three",
"kind",
"of",
"Rotation",
"Invariant",
"Features",
"(RIFs):",
"Spherical",
"Signals",
"(SS),",
"Individual-Local",
"Rotation",
"Invariant",
"Features",
"(ILRIF)",
"and",
"Group-Local",
"Rotation",
"Invariant",
"features",
"(GLRIF)",
"in",
"its",
"structure",
"to",
"learn",
"rotation",
"invariant",
"convolutional",
"kernels,",
"which",
"are",
"robust",
"for",
"learning",
"rotation",
"invariant",
"point",
"cloud",
"features.",
"What's",
"more,",
"to",
"highlight",
"pivotal",
"RIFs,",
"we",
"inject",
"an",
"attentive",
"module",
"in",
"ARIConv",
"to",
"give",
"different",
"RIFs",
"different",
"importance",
"when",
"learning",
"kernels.",
"Finally,",
"utilizing",
"ARIConv,",
"we",
"build",
"a",
"DenseNet-like",
"network",
"architecture",
"to",
"learn",
"rotation-insensitive",
"global",
"descriptors",
"used",
"for",
"retrieving.",
"We",
"experimentally",
"demonstrate",
"that",
"our",
"model",
"can",
"achieve",
"state-of-the-art",
"performance",
"on",
"large",
"scale",
"place",
"recognition",
"task",
"when",
"the",
"point",
"cloud",
"scans",
"are",
"rotated",
"and",
"can",
"achieve",
"comparable",
"results",
"with",
"most",
"of",
"existing",
"methods",
"on",
"the",
"original",
"non-rotated",
"datasets."
] |
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[
"BERT",
"has",
"achieved",
"superior",
"performances",
"on",
"Natural",
"Language",
"Understanding",
"(NLU)",
"tasks.",
"However,",
"BERT",
"possesses",
"a",
"large",
"number",
"of",
"parameters",
"and",
"demands",
"certain",
"resources",
"to",
"deploy.",
"For",
"acceleration,",
"Dynamic",
"Early",
"Exiting",
"for",
"BERT",
"(DeeBERT",
")",
"has",
"been",
"proposed",
"recently,",
"which",
"incorporates",
"multiple",
"exits",
"and",
"adopts",
"a",
"dynamic",
"early-exit",
"mechanism",
"to",
"ensure",
"efficient",
"inference.",
"While",
"obtaining",
"an",
"efficiency-performance",
"tradeoff,",
"the",
"performances",
"of",
"early",
"exits",
"in",
"multi-exit",
"BERT",
"are",
"significantly",
"worse",
"than",
"late",
"exits.",
"In",
"this",
"paper,",
"we",
"leverage",
"gradient",
"regularized",
"self-distillation",
"for",
"RObust",
"training",
"of",
"Multi-Exit",
"BERT",
"(RomeBERT),",
"which",
"can",
"effectively",
"solve",
"the",
"performance",
"imbalance",
"problem",
"between",
"early",
"and",
"late",
"exits.",
"Moreover,",
"the",
"proposed",
"RomeBERT",
"adopts",
"a",
"one-stage",
"joint",
"training",
"strategy",
"for",
"multi-exits",
"and",
"the",
"BERT",
"backbone",
"while",
"DeeBERT",
"needs",
"two",
"stages",
"that",
"require",
"more",
"training",
"time.",
"Extensive",
"experiments",
"on",
"GLUE",
"datasets",
"are",
"performed",
"to",
"demonstrate",
"the",
"superiority",
"of",
"our",
"approach.",
"Our",
"code",
"is",
"available",
"at",
"https://github.com/romebert/RomeBERT."
] |
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[
"The",
"tremendous",
"numbers",
"of",
"network",
"security",
"breaches",
"that",
"have",
"occurred",
"in",
"IoT",
"networks",
"have",
"demonstrated",
"the",
"unreliability",
"of",
"current",
"Network",
"Intrusion",
"Detection",
"Systems",
"(NIDSs).",
"Consequently,",
"network",
"interruptions",
"and",
"loss",
"of",
"sensitive",
"data",
"have",
"occurred",
"which",
"led",
"to",
"an",
"active",
"research",
"area",
"for",
"improving",
"NIDS",
"technologies.",
"During",
"an",
"analysis",
"of",
"related",
"works,",
"it",
"was",
"observed",
"that",
"most",
"researchers",
"aimed",
"to",
"obtain",
"better",
"classification",
"results",
"by",
"using",
"a",
"set",
"of",
"untried",
"combinations",
"of",
"Feature",
"Reduction",
"(FR)",
"and",
"Machine",
"Learning",
"(ML)",
"techniques",
"on",
"NIDS",
"datasets.",
"However,",
"these",
"datasets",
"are",
"different",
"in",
"feature",
"sets,",
"attack",
"types,",
"and",
"network",
"design.",
"Therefore,",
"this",
"paper",
"aims",
"to",
"discover",
"whether",
"these",
"techniques",
"can",
"be",
"generalised",
"across",
"various",
"datasets.",
"Six",
"ML",
"models",
"are",
"utilised:",
"a",
"Deep",
"Feed",
"Forward,",
"Convolutional",
"Neural",
"Network,",
"Recurrent",
"Neural",
"Network,",
"Decision",
"Tree,",
"Logistic",
"Regression,",
"and",
"Naive",
"Bayes.",
"The",
"detection",
"accuracy",
"of",
"three",
"Feature",
"Extraction",
"(FE)",
"algorithms;",
"Principal",
"Component",
"Analysis",
"(PCA",
"),",
"Auto-encoder",
"(AE",
"),",
"and",
"Linear",
"Discriminant",
"Analysis",
"(LDA",
")",
"is",
"evaluated",
"using",
"three",
"benchmark",
"datasets;",
"UNSW-NB15,",
"ToN-IoT",
"and",
"CSE-CIC-IDS2018.",
"Although",
"PCA",
"and",
"AE",
"algorithms",
"have",
"been",
"widely",
"used,",
"determining",
"their",
"optimal",
"number",
"of",
"extracted",
"dimensions",
"has",
"been",
"overlooked.",
"The",
"results",
"obtained",
"indicate",
"that",
"there",
"is",
"no",
"clear",
"FE",
"method",
"or",
"ML",
"model",
"that",
"can",
"achieve",
"the",
"best",
"scores",
"for",
"all",
"datasets.",
"The",
"optimal",
"number",
"of",
"extracted",
"dimensions",
"has",
"been",
"identified",
"for",
"each",
"dataset",
"and",
"LDA",
"decreases",
"the",
"performance",
"of",
"the",
"ML",
"models",
"on",
"two",
"datasets.",
"The",
"variance",
"is",
"used",
"to",
"analyse",
"the",
"extracted",
"dimensions",
"of",
"LDA",
"and",
"PCA",
".",
"Finally,",
"this",
"paper",
"concludes",
"that",
"the",
"choice",
"of",
"datasets",
"significantly",
"alters",
"the",
"performance",
"of",
"the",
"applied",
"techniques",
"and",
"we",
"argue",
"for",
"the",
"need",
"for",
"a",
"universal",
"(benchmark)",
"feature",
"set",
"to",
"facilitate",
"further",
"advancement",
"and",
"progress",
"in",
"this",
"field",
"of",
"research."
] |
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[
"The",
"need",
"for",
"algorithms",
"able",
"to",
"solve",
"Reinforcement",
"Learning",
"(RL)",
"problems",
"with",
"few",
"trials",
"has",
"motivated",
"the",
"advent",
"of",
"model-based",
"RL",
"methods.",
"The",
"reported",
"performance",
"of",
"model-based",
"algorithms",
"has",
"dramatically",
"increased",
"within",
"recent",
"years.",
"However,",
"it",
"is",
"not",
"clear",
"how",
"much",
"of",
"the",
"recent",
"progress",
"is",
"due",
"to",
"improved",
"algorithms",
"or",
"due",
"to",
"improved",
"models.",
"While",
"different",
"modeling",
"options",
"are",
"available",
"to",
"choose",
"from",
"when",
"applying",
"a",
"model-based",
"approach,",
"the",
"distinguishing",
"traits",
"and",
"particular",
"strengths",
"of",
"different",
"models",
"are",
"not",
"clear.",
"The",
"main",
"contribution",
"of",
"this",
"work",
"lies",
"precisely",
"in",
"assessing",
"the",
"model",
"influence",
"on",
"the",
"performance",
"of",
"RL",
"algorithms.",
"A",
"set",
"of",
"commonly",
"adopted",
"models",
"is",
"established",
"for",
"the",
"purpose",
"of",
"model",
"comparison.",
"These",
"include",
"Neural",
"Networks",
"(NNs),",
"ensembles",
"of",
"NNs,",
"two",
"different",
"approximations",
"of",
"Bayesian",
"NNs",
"(BNNs),",
"that",
"is,",
"the",
"Concrete",
"Dropout",
"NN",
"and",
"the",
"Anchored",
"Ensembling,",
"and",
"Gaussian",
"Processes",
"(GPs).",
"The",
"model",
"comparison",
"is",
"evaluated",
"on",
"a",
"suite",
"of",
"continuous",
"control",
"benchmarking",
"tasks.",
"Our",
"results",
"reveal",
"that",
"significant",
"differences",
"in",
"model",
"performance",
"do",
"exist.",
"The",
"Concrete",
"Dropout",
"NN",
"reports",
"persistently",
"superior",
"performance.",
"We",
"summarize",
"these",
"differences",
"for",
"the",
"benefit",
"of",
"the",
"modeler",
"and",
"suggest",
"that",
"the",
"model",
"choice",
"is",
"tailored",
"to",
"the",
"standards",
"required",
"by",
"each",
"specific",
"application."
] |
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[
"Graph",
"convolutional",
"networks",
"(GCNs)",
"have",
"recently",
"enabled",
"a",
"popular",
"class",
"of",
"algorithms",
"for",
"collaborative",
"filtering",
"(CF).",
"Nevertheless,",
"the",
"theoretical",
"underpinnings",
"of",
"their",
"empirical",
"successes",
"remain",
"elusive.",
"In",
"this",
"paper,",
"we",
"endeavor",
"to",
"obtain",
"a",
"better",
"understanding",
"of",
"GCN-based",
"CF",
"methods",
"via",
"the",
"lens",
"of",
"graph",
"signal",
"processing.",
"By",
"identifying",
"the",
"critical",
"role",
"of",
"smoothness,",
"a",
"key",
"concept",
"in",
"graph",
"signal",
"processing,",
"we",
"develop",
"a",
"unified",
"graph",
"convolution-based",
"framework",
"for",
"CF.",
"We",
"prove",
"that",
"many",
"existing",
"CF",
"methods",
"are",
"special",
"cases",
"of",
"this",
"framework,",
"including",
"the",
"neighborhood-based",
"methods,",
"low-rank",
"matrix",
"factorization,",
"linear",
"auto-encoders,",
"and",
"LightGCN",
",",
"corresponding",
"to",
"different",
"low-pass",
"filters.",
"Based",
"on",
"our",
"framework,",
"we",
"then",
"present",
"a",
"simple",
"and",
"computationally",
"efficient",
"CF",
"baseline,",
"which",
"we",
"shall",
"refer",
"to",
"as",
"Graph",
"Filter",
"based",
"Collaborative",
"Filtering",
"(GF-CF).",
"Given",
"an",
"implicit",
"feedback",
"matrix,",
"GF-CF",
"can",
"be",
"obtained",
"in",
"a",
"closed",
"form",
"instead",
"of",
"expensive",
"training",
"with",
"back-propagation.",
"Experiments",
"will",
"show",
"that",
"GF-CF",
"achieves",
"competitive",
"or",
"better",
"performance",
"against",
"deep",
"learning-based",
"methods",
"on",
"three",
"well-known",
"datasets,",
"notably",
"with",
"a",
"$70\\%$",
"performance",
"gain",
"over",
"LightGCN",
"on",
"the",
"Amazon-book",
"dataset."
] |
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[
"Multi-task",
"benchmarks",
"such",
"as",
"GLUE",
"and",
"SuperGLUE",
"have",
"driven",
"great",
"progress",
"of",
"pretraining",
"and",
"transfer",
"learning",
"in",
"Natural",
"Language",
"Processing",
"(NLP).",
"These",
"benchmarks",
"mostly",
"focus",
"on",
"a",
"range",
"of",
"Natural",
"Language",
"Understanding",
"(NLU)",
"tasks,",
"without",
"considering",
"the",
"Natural",
"Language",
"Generation",
"(NLG)",
"models.",
"In",
"this",
"paper,",
"we",
"present",
"the",
"General",
"Language",
"Generation",
"Evaluation",
"(GLGE),",
"a",
"new",
"multi-task",
"benchmark",
"for",
"evaluating",
"the",
"generalization",
"capabilities",
"of",
"NLG",
"models",
"across",
"eight",
"language",
"generation",
"tasks.",
"For",
"each",
"task,",
"we",
"continue",
"to",
"design",
"three",
"subtasks",
"in",
"terms",
"of",
"task",
"difficulty",
"(GLGE-Easy,",
"GLGE-Medium,",
"and",
"GLGE-Hard).",
"This",
"introduces",
"24",
"subtasks",
"to",
"comprehensively",
"compare",
"model",
"performance.",
"To",
"encourage",
"research",
"on",
"pretraining",
"and",
"transfer",
"learning",
"on",
"NLG",
"models,",
"we",
"make",
"GLGE",
"publicly",
"available",
"and",
"build",
"a",
"leaderboard",
"with",
"strong",
"baselines",
"including",
"MASS,",
"BART,",
"and",
"ProphetNet",
"(The",
"source",
"code",
"and",
"dataset",
"are",
"publicly",
"available",
"at",
"https://github.com/microsoft/glge)."
] |
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[
"This",
"paper",
"introduces",
"a",
"new",
"fundamental",
"characteristic,",
"\\ie,",
"the",
"dynamic",
"range,",
"from",
"real-world",
"metric",
"tools",
"to",
"deep",
"visual",
"recognition.",
"In",
"metrology,",
"the",
"dynamic",
"range",
"is",
"a",
"basic",
"quality",
"of",
"a",
"metric",
"tool,",
"indicating",
"its",
"flexibility",
"to",
"accommodate",
"various",
"scales.",
"Larger",
"dynamic",
"range",
"offers",
"higher",
"flexibility.",
"In",
"visual",
"recognition,",
"the",
"multiple",
"scale",
"problem",
"also",
"exist.",
"Different",
"visual",
"concepts",
"may",
"have",
"different",
"semantic",
"scales.",
"For",
"example,",
"``Animal''",
"and",
"``Plants''",
"have",
"a",
"large",
"semantic",
"scale",
"while",
"``Elk''",
"has",
"a",
"much",
"smaller",
"one.",
"Under",
"a",
"small",
"semantic",
"scale,",
"two",
"different",
"elks",
"may",
"look",
"quite",
"\\emph{different}",
"to",
"each",
"other",
".",
"However,",
"under",
"a",
"large",
"semantic",
"scale",
"(\\eg,",
"animals",
"and",
"plants),",
"these",
"two",
"elks",
"should",
"be",
"measured",
"as",
"being",
"\\emph{similar}.",
"%We",
"argue",
"that",
"such",
"flexibility",
"is",
"also",
"important",
"for",
"deep",
"metric",
"learning,",
"because",
"different",
"visual",
"concepts",
"indeed",
"correspond",
"to",
"different",
"semantic",
"scales.",
"Introducing",
"the",
"dynamic",
"range",
"to",
"deep",
"metric",
"learning,",
"we",
"get",
"a",
"novel",
"computer",
"vision",
"task,",
"\\ie,",
"the",
"Dynamic",
"Metric",
"Learning",
".",
"It",
"aims",
"to",
"learn",
"a",
"scalable",
"metric",
"space",
"to",
"accommodate",
"visual",
"concepts",
"across",
"multiple",
"semantic",
"scales.",
"Based",
"on",
"three",
"types",
"of",
"images,",
"\\emph{i.e.},",
"vehicle,",
"animal",
"and",
"online",
"products,",
"we",
"construct",
"three",
"datasets",
"for",
"Dynamic",
"Metric",
"Learning",
".",
"We",
"benchmark",
"these",
"datasets",
"with",
"popular",
"deep",
"metric",
"learning",
"methods",
"and",
"find",
"Dynamic",
"Metric",
"Learning",
"to",
"be",
"very",
"challenging.",
"The",
"major",
"difficulty",
"lies",
"in",
"a",
"conflict",
"between",
"different",
"scales:",
"the",
"discriminative",
"ability",
"under",
"a",
"small",
"scale",
"usually",
"compromises",
"the",
"discriminative",
"ability",
"under",
"a",
"large",
"one,",
"and",
"vice",
"versa.",
"As",
"a",
"minor",
"contribution,",
"we",
"propose",
"Cross-Scale",
"Learning",
"(CSL",
")",
"to",
"alleviate",
"such",
"conflict.",
"We",
"show",
"that",
"CSL",
"consistently",
"improves",
"the",
"baseline",
"on",
"all",
"the",
"three",
"datasets.",
"The",
"datasets",
"and",
"the",
"code",
"will",
"be",
"publicly",
"available",
"at",
"https://github.com/SupetZYK/DynamicMetricLearning."
] |
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[
"As",
"various",
"databases",
"of",
"facial",
"expressions",
"have",
"been",
"made",
"accessible",
"over",
"the",
"last",
"few",
"decades,",
"the",
"Facial",
"Expression",
"Recognition",
"(FER)",
"task",
"has",
"gotten",
"a",
"lot",
"of",
"interest.",
"The",
"multiple",
"sources",
"of",
"the",
"available",
"databases",
"raised",
"several",
"challenges",
"for",
"facial",
"recognition",
"task.",
"These",
"challenges",
"are",
"usually",
"addressed",
"by",
"Convolution",
"Neural",
"Network",
"(CNN)",
"architectures.",
"Different",
"from",
"CNN",
"models,",
"a",
"Transformer",
"model",
"based",
"on",
"attention",
"mechanism",
"has",
"been",
"presented",
"recently",
"to",
"address",
"vision",
"tasks.",
"One",
"of",
"the",
"major",
"issue",
"with",
"Transformer",
"s",
"is",
"the",
"need",
"of",
"a",
"large",
"data",
"for",
"training,",
"while",
"most",
"FER",
"databases",
"are",
"limited",
"compared",
"to",
"other",
"vision",
"applications.",
"Therefore,",
"we",
"propose",
"in",
"this",
"paper",
"to",
"learn",
"a",
"vision",
"Transformer",
"jointly",
"with",
"a",
"Squeeze",
"and",
"Excitation",
"(SE)",
"block",
"for",
"FER",
"task.",
"The",
"proposed",
"method",
"is",
"evaluated",
"on",
"different",
"publicly",
"available",
"FER",
"databases",
"including",
"CK+,",
"JAFFE,RAF-DB",
"and",
"SFEW.",
"Experiments",
"demonstrate",
"that",
"our",
"model",
"outperforms",
"state-of-the-art",
"methods",
"on",
"CK+",
"and",
"SFEW",
"and",
"achieves",
"competitive",
"results",
"on",
"JAFFE",
"and",
"RAF-DB."
] |
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[
"Visual",
"inspection",
"of",
"underwater",
"structures",
"by",
"vehicles,",
"e.g.",
"remotely",
"operated",
"vehicles",
"(ROVs),",
"plays",
"an",
"important",
"role",
"in",
"scientific,",
"military,",
"and",
"commercial",
"sectors.",
"However,",
"the",
"automatic",
"extraction",
"of",
"information",
"using",
"software",
"tools",
"is",
"hindered",
"by",
"the",
"characteristics",
"of",
"water",
"which",
"degrade",
"the",
"quality",
"of",
"captured",
"videos.",
"As",
"a",
"contribution",
"for",
"restoring",
"the",
"color",
"of",
"underwater",
"images,",
"Underwater",
"Denoising",
"Autoencoder",
"(UDAE)",
"model",
"is",
"developed",
"using",
"a",
"denoising",
"autoencoder",
"with",
"U-Net",
"architecture.",
"The",
"proposed",
"network",
"takes",
"into",
"consideration",
"the",
"accuracy",
"and",
"the",
"computation",
"cost",
"to",
"enable",
"real-time",
"implementation",
"on",
"underwater",
"visual",
"tasks",
"using",
"end-to-end",
"autoencoder",
"network.",
"Underwater",
"vehicles",
"perception",
"is",
"improved",
"by",
"reconstructing",
"captured",
"frames;",
"hence",
"obtaining",
"better",
"performance",
"in",
"underwater",
"tasks.",
"Related",
"learning",
"methods",
"use",
"generative",
"adversarial",
"networks",
"(GANs)",
"to",
"generate",
"color",
"corrected",
"underwater",
"images,",
"and",
"to",
"our",
"knowledge",
"this",
"paper",
"is",
"the",
"first",
"to",
"deal",
"with",
"a",
"single",
"autoencoder",
"capable",
"of",
"producing",
"same",
"or",
"better",
"results.",
"Moreover,",
"image",
"pairs",
"are",
"constructed",
"for",
"training",
"the",
"proposed",
"network,",
"where",
"it",
"is",
"hard",
"to",
"obtain",
"such",
"dataset",
"from",
"underwater",
"scenery.",
"At",
"the",
"end,",
"the",
"proposed",
"model",
"is",
"compared",
"to",
"a",
"state-of-the-art",
"method."
] |
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[
"In",
"this",
"paper,",
"we",
"propose",
"a",
"novel",
"model",
"called",
"Adversarial",
"Multi-Task",
"Network",
"(AMTN)",
"for",
"jointly",
"modeling",
"Recognizing",
"Question",
"Entailment",
"(RQE)",
"and",
"medical",
"Question",
"Answering",
"(QA)",
"tasks.",
"AMTN",
"utilizes",
"a",
"pre-trained",
"BioBERT",
"model",
"and",
"an",
"Interactive",
"Transformer",
"to",
"learn",
"the",
"shared",
"semantic",
"representations",
"across",
"different",
"task",
"through",
"parameter",
"sharing",
"mechanism.",
"Meanwhile,",
"an",
"adversarial",
"training",
"strategy",
"is",
"introduced",
"to",
"separate",
"the",
"private",
"features",
"of",
"each",
"task",
"from",
"the",
"shared",
"representations.",
"Experiments",
"on",
"BioNLP",
"2019",
"RQE",
"and",
"QA",
"Shared",
"Task",
"datasets",
"show",
"that",
"our",
"model",
"benefits",
"from",
"the",
"shared",
"representations",
"of",
"both",
"tasks",
"provided",
"by",
"multi-task",
"learning",
"and",
"adversarial",
"training,",
"and",
"obtains",
"significant",
"improvements",
"upon",
"the",
"single-task",
"models."
] |
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[
"In",
"recent",
"years,",
"studies",
"on",
"automatic",
"speech",
"recognition",
"(ASR)",
"have",
"shown",
"outstanding",
"results",
"that",
"reach",
"human",
"parity",
"on",
"short",
"speech",
"segments.",
"However,",
"there",
"are",
"still",
"difficulties",
"in",
"standardizing",
"the",
"output",
"of",
"ASR",
"such",
"as",
"capitalization",
"and",
"punctuation",
"restoration",
"for",
"long-speech",
"transcription.",
"The",
"problems",
"obstruct",
"readers",
"to",
"understand",
"the",
"ASR",
"output",
"semantically",
"and",
"also",
"cause",
"difficulties",
"for",
"natural",
"language",
"processing",
"models",
"such",
"as",
"NER,",
"POS",
"and",
"semantic",
"parsing.",
"In",
"this",
"paper,",
"we",
"propose",
"a",
"method",
"to",
"restore",
"the",
"punctuation",
"and",
"capitalization",
"for",
"long-speech",
"ASR",
"transcription.",
"The",
"method",
"is",
"based",
"on",
"Transformer",
"models",
"and",
"chunk",
"merging",
"that",
"allows",
"us",
"to",
"(1),",
"build",
"a",
"single",
"model",
"that",
"performs",
"punctuation",
"and",
"capitalization",
"in",
"one",
"go,",
"and",
"(2),",
"perform",
"decoding",
"in",
"parallel",
"while",
"improving",
"the",
"prediction",
"accuracy.",
"Experiments",
"on",
"British",
"National",
"Corpus",
"showed",
"that",
"the",
"proposed",
"approach",
"outperforms",
"existing",
"methods",
"in",
"both",
"accuracy",
"and",
"decoding",
"speed."
] |
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[
"Mitotic",
"figure",
"detection",
"is",
"a",
"challenging",
"task",
"in",
"digital",
"pathology",
"that",
"has",
"a",
"direct",
"impact",
"on",
"therapeutic",
"decisions.",
"While",
"automated",
"methods",
"often",
"achieve",
"acceptable",
"results",
"under",
"laboratory",
"conditions,",
"they",
"frequently",
"fail",
"in",
"the",
"clinical",
"deployment",
"phase.",
"This",
"problem",
"can",
"be",
"mainly",
"attributed",
"to",
"a",
"phenomenon",
"called",
"domain",
"shift.",
"An",
"important",
"source",
"of",
"a",
"domain",
"shift",
"is",
"introduced",
"by",
"different",
"microscopes",
"and",
"their",
"camera",
"systems,",
"which",
"noticeably",
"change",
"the",
"color",
"representation",
"of",
"digitized",
"images.",
"In",
"this",
"method",
"description",
"we",
"present",
"our",
"submitted",
"algorithm",
"for",
"the",
"Mitosis",
"Domain",
"Generalization",
"Challenge,",
"which",
"employs",
"a",
"RetinaNet",
"trained",
"with",
"strong",
"data",
"augmentation",
"and",
"achieves",
"an",
"F1",
"score",
"of",
"0.7138",
"on",
"the",
"preliminary",
"test",
"set."
] |
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[
"Classification",
"of",
"biological",
"images",
"is",
"an",
"important",
"task",
"with",
"crucial",
"application",
"in",
"many",
"fields,",
"such",
"as",
"cell",
"phenotypes",
"recognition,",
"detection",
"of",
"cell",
"organelles",
"and",
"histopathological",
"classification,",
"and",
"it",
"might",
"help",
"in",
"early",
"medical",
"diagnosis,",
"allowing",
"automatic",
"disease",
"classification",
"without",
"the",
"need",
"of",
"a",
"human",
"expert.",
"In",
"this",
"paper",
"we",
"classify",
"biomedical",
"images",
"using",
"ensembles",
"of",
"neural",
"networks.",
"We",
"create",
"this",
"ensemble",
"using",
"a",
"ResNet50",
"architecture",
"and",
"modifying",
"its",
"activation",
"layers",
"by",
"substituting",
"ReLU",
"s",
"with",
"other",
"functions.",
"We",
"select",
"our",
"activations",
"among",
"the",
"following",
"ones:",
"ReLU",
",",
"leaky",
"ReLU",
",",
"Parametric",
"ReLU",
",",
"ELU,",
"Adaptive",
"Piecewice",
"Linear",
"Unit,",
"S-Shaped",
"ReLU",
",",
"Swish",
",",
"Mish,",
"Mexican",
"Linear",
"Unit,",
"Gaussian",
"Linear",
"Unit,",
"Parametric",
"Deformable",
"Linear",
"Unit,",
"Soft",
"Root",
"Sign",
"(SRS)",
"and",
"others.",
"As",
"a",
"baseline,",
"we",
"used",
"an",
"ensemble",
"of",
"neural",
"networks",
"that",
"only",
"use",
"ReLU",
"activations.",
"We",
"tested",
"our",
"networks",
"on",
"several",
"small",
"and",
"medium",
"sized",
"biomedical",
"image",
"datasets.",
"Our",
"results",
"prove",
"that",
"our",
"best",
"ensemble",
"obtains",
"a",
"better",
"performance",
"than",
"the",
"ones",
"of",
"the",
"naive",
"approaches.",
"In",
"order",
"to",
"encourage",
"the",
"reproducibility",
"of",
"this",
"work,",
"the",
"MATLAB",
"code",
"of",
"all",
"the",
"experiments",
"will",
"be",
"shared",
"at",
"https://github.com/LorisNanni."
] |
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[
"In",
"this",
"paper,",
"we",
"introduced",
"a",
"novel",
"deep",
"learning",
"based",
"reconstruction",
"technique",
"using",
"the",
"correlations",
"of",
"all",
"3",
"dimensions",
"with",
"each",
"other",
"by",
"taking",
"into",
"account",
"the",
"correlation",
"between",
"2-dimensional",
"low-dose",
"CT",
"images.",
"Sparse",
"or",
"noisy",
"sinograms",
"are",
"back",
"projected",
"to",
"the",
"image",
"domain",
"with",
"FBP",
"operation,",
"then",
"denoising",
"process",
"is",
"applied",
"with",
"a",
"U-Net",
"like",
"3",
"dimensional",
"network",
"called",
"3D",
"U-Net",
"R.",
"Proposed",
"network",
"is",
"trained",
"with",
"synthetic",
"and",
"real",
"chest",
"CT",
"images,",
"and",
"2D",
"U-Net",
"is",
"also",
"trained",
"with",
"the",
"same",
"dataset",
"to",
"prove",
"the",
"importance",
"of",
"the",
"3rd",
"dimension.",
"Proposed",
"network",
"shows",
"better",
"quantitative",
"performance",
"on",
"SSIM",
"and",
"PSNR.",
"More",
"importantly,",
"3D",
"U-Net",
"R",
"captures",
"medically",
"critical",
"visual",
"details",
"that",
"cannot",
"be",
"visualized",
"by",
"2D",
"network."
] |
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[
"This",
"paper",
"describes",
"the",
"implementation",
"of",
"a",
"prototype",
"of",
"a",
"grammar",
"based",
"grammar",
"checker",
"for",
"Czech",
"and",
"the",
"basic",
"ideas",
"behind",
"this",
"implementation",
".",
"The",
"demo",
"is",
"implemented",
"as",
"an",
"independent",
"program",
"cooperating",
"with",
"Microsoft",
"Word",
".",
"The",
"grammar",
"checker",
"uses",
"specialized",
"grammar",
"formalism",
"which",
"generally",
"enables",
"to",
"check",
"errors",
"in",
"languages",
"with",
"a",
"very",
"high",
"degree",
"of",
"word",
"order",
"freedom",
"."
] |
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"our",
"research",
"on",
"effective",
"privacy",
"preservation",
"approaches",
"for",
"pretrained",
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"utility",
"implications",
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"NLU",
"applications.",
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"further",
"propose",
"privacy-adaptive",
"LM",
"pretraining",
"methods",
"and",
"show",
"that",
"our",
"approach",
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"dramatically",
"while",
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"same",
"level",
"of",
"privacy",
"protection.",
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"also",
"quantify",
"the",
"level",
"of",
"privacy",
"preservation",
"and",
"provide",
"guidance",
"on",
"privacy",
"configuration.",
"Our",
"experiments",
"and",
"findings",
"lay",
"the",
"groundwork",
"for",
"future",
"explorations",
"of",
"privacy-preserving",
"NLU",
"with",
"pretrained",
"LMs."
] |
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[
"Colorization",
"is",
"the",
"method",
"of",
"converting",
"an",
"image",
"in",
"grayscale",
"to",
"a",
"fully",
"color",
"image.",
"There",
"are",
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"methods",
"to",
"do",
"the",
"same.",
"Old",
"school",
"methods",
"used",
"machine",
"learning",
"algorithms",
"and",
"optimization",
"techniques",
"to",
"suggest",
"possible",
"colors",
"to",
"use.",
"With",
"advances",
"in",
"the",
"field",
"of",
"deep",
"learning,",
"colorization",
"results",
"have",
"improved",
"consistently",
"with",
"improvements",
"in",
"deep",
"learning",
"architectures.",
"The",
"latest",
"development",
"in",
"the",
"field",
"of",
"deep",
"learning",
"is",
"the",
"emergence",
"of",
"generative",
"adversarial",
"networks",
"(GAN",
"s)",
"which",
"is",
"used",
"to",
"generate",
"information",
"and",
"not",
"just",
"predict",
"or",
"classify.",
"As",
"part",
"of",
"this",
"report,",
"2",
"architectures",
"of",
"recent",
"papers",
"are",
"reproduced",
"along",
"with",
"a",
"novel",
"architecture",
"being",
"suggested",
"for",
"general",
"colorization.",
"Following",
"this,",
"we",
"propose",
"the",
"use",
"of",
"colorization",
"by",
"generating",
"makeup",
"suggestions",
"automatically",
"on",
"a",
"face.",
"To",
"do",
"this,",
"a",
"dataset",
"consisting",
"of",
"1000",
"images",
"has",
"been",
"created.",
"When",
"an",
"image",
"of",
"a",
"person",
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"makeup",
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"model,",
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"model",
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"converts",
"the",
"image",
"to",
"grayscale",
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"then",
"passes",
"it",
"through",
"the",
"suggested",
"GAN",
"model.",
"The",
"output",
"is",
"a",
"generated",
"makeup",
"suggestion.",
"To",
"develop",
"this",
"model,",
"we",
"need",
"to",
"tweak",
"the",
"general",
"colorization",
"model",
"to",
"deal",
"only",
"with",
"faces",
"of",
"people."
] |
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[
"This",
"paper",
"describes",
"the",
"ASU",
"system",
"submitted",
"in",
"the",
"COLING",
"W-NUT",
"2016",
"Twitter",
"Named",
"Entity",
"Recognition",
"(NER",
")",
"task.",
"We",
"present",
"an",
"experimental",
"study",
"on",
"applying",
"deep",
"learning",
"to",
"extracting",
"named",
"entities",
"(NEs)",
"from",
"tweets.",
"We",
"built",
"two",
"Long",
"Short-Term",
"Memory",
"(LSTM",
")",
"models",
"for",
"the",
"task.",
"The",
"first",
"model",
"was",
"built",
"to",
"extract",
"named",
"entities",
"without",
"types",
"while",
"the",
"second",
"model",
"was",
"built",
"to",
"extract",
"and",
"then",
"classify",
"them",
"into",
"10",
"fine-grained",
"entity",
"classes.",
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"this",
"effort,",
"we",
"show",
"detailed",
"experimentation",
"results",
"on",
"the",
"effectiveness",
"of",
"word",
"embeddings,",
"brown",
"clusters,",
"part-of-speech",
"(POS)",
"tags,",
"shape",
"features,",
"gazetteers,",
"and",
"local",
"context",
"for",
"the",
"tweet",
"input",
"vector",
"representation",
"to",
"the",
"LSTM",
"model.",
"Also,",
"we",
"present",
"a",
"set",
"of",
"experiments,",
"to",
"better",
"design",
"the",
"network",
"parameters",
"for",
"the",
"Twitter",
"NER",
"task.",
"Our",
"system",
"was",
"ranked",
"the",
"fifth",
"out",
"of",
"ten",
"participants",
"with",
"a",
"final",
"f1-score",
"for",
"the",
"typed",
"classes",
"of",
"39{\\%}",
"and",
"55{\\%}",
"for",
"the",
"non",
"typed",
"ones."
] |
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[
"Existing",
"differentiable",
"neural",
"architecture",
"search",
"approaches",
"simply",
"assume",
"the",
"architectural",
"distribution",
"on",
"each",
"edge",
"is",
"independent",
"of",
"each",
"other,",
"which",
"conflicts",
"with",
"the",
"intrinsic",
"properties",
"of",
"architecture.",
"In",
"this",
"paper,",
"we",
"view",
"the",
"architectural",
"distribution",
"as",
"the",
"latent",
"representation",
"of",
"specific",
"data",
"points.",
"Then",
"we",
"propose",
"Variational",
"Information",
"Maximization",
"Neural",
"Architecture",
"Search",
"(VIM-NAS)",
"to",
"leverage",
"a",
"simple",
"but",
"effective",
"convolutional",
"neural",
"network",
"to",
"model",
"the",
"latent",
"representation,",
"and",
"optimize",
"for",
"a",
"tractable",
"variational",
"lower",
"bound",
"to",
"the",
"mutual",
"information",
"between",
"the",
"data",
"points",
"and",
"the",
"latent",
"representations.",
"VIM-NAS",
"automatically",
"learns",
"a",
"near",
"one-hot",
"distribution",
"from",
"a",
"continuous",
"distribution",
"with",
"extremely",
"fast",
"convergence",
"speed,",
"e.g.,",
"converging",
"with",
"one",
"epoch.",
"Experimental",
"results",
"demonstrate",
"VIM-NAS",
"achieves",
"state-of-the-art",
"performance",
"on",
"various",
"search",
"spaces,",
"including",
"DARTS",
"search",
"space,",
"NAS-Bench-1shot1,",
"NAS-Bench-201,",
"and",
"simplified",
"search",
"spaces",
"S1-S4.",
"Specifically,",
"VIM-NAS",
"achieves",
"a",
"top-1",
"error",
"rate",
"of",
"2.45%",
"and",
"15.80%",
"within",
"10",
"minutes",
"on",
"CIFAR-10",
"and",
"CIFAR-100,",
"respectively,",
"and",
"a",
"top-1",
"error",
"rate",
"of",
"24.00%",
"when",
"transferred",
"to",
"ImageNet."
] |
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[
"In",
"this",
"manuscript,",
"the",
"topic",
"of",
"multi-corpus",
"Speech",
"Emotion",
"Recognition",
"(SER)",
"is",
"approached",
"from",
"a",
"deep",
"transfer",
"learning",
"perspective.",
"A",
"large",
"corpus",
"of",
"emotional",
"speech",
"data,",
"EmoSet,",
"is",
"assembled",
"from",
"a",
"number",
"of",
"existing",
"SER",
"corpora.",
"In",
"total,",
"EmoSet",
"contains",
"84181",
"audio",
"recordings",
"from",
"26",
"SER",
"corpora",
"with",
"a",
"total",
"duration",
"of",
"over",
"65",
"hours.",
"The",
"corpus",
"is",
"then",
"utilised",
"to",
"create",
"a",
"novel",
"framework",
"for",
"multi-corpus",
"speech",
"emotion",
"recognition,",
"namely",
"EmoNet.",
"A",
"combination",
"of",
"a",
"deep",
"ResNet",
"architecture",
"and",
"residual",
"adapters",
"is",
"transferred",
"from",
"the",
"field",
"of",
"multi-domain",
"visual",
"recognition",
"to",
"multi-corpus",
"SER",
"on",
"EmoSet.",
"Compared",
"against",
"two",
"suitable",
"baselines",
"and",
"more",
"traditional",
"training",
"and",
"transfer",
"settings",
"for",
"the",
"ResNet",
",",
"the",
"residual",
"adapter",
"approach",
"enables",
"parameter",
"efficient",
"training",
"of",
"a",
"multi-domain",
"SER",
"model",
"on",
"all",
"26",
"corpora.",
"A",
"shared",
"model",
"with",
"only",
"$3.5$",
"times",
"the",
"number",
"of",
"parameters",
"of",
"a",
"model",
"trained",
"on",
"a",
"single",
"database",
"leads",
"to",
"increased",
"performance",
"for",
"21",
"of",
"the",
"26",
"corpora",
"in",
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"Measured",
"by",
"McNemar's",
"test,",
"these",
"improvements",
"are",
"further",
"significant",
"for",
"ten",
"datasets",
"at",
"$p<0.05$",
"while",
"there",
"are",
"just",
"two",
"corpora",
"that",
"see",
"only",
"significant",
"decreases",
"across",
"the",
"residual",
"adapter",
"transfer",
"experiments.",
"Finally,",
"we",
"make",
"our",
"EmoNet",
"framework",
"publicly",
"available",
"for",
"users",
"and",
"developers",
"at",
"https://github.com/EIHW/EmoNet.",
"EmoNet",
"provides",
"an",
"extensive",
"command",
"line",
"interface",
"which",
"is",
"comprehensively",
"documented",
"and",
"can",
"be",
"used",
"in",
"a",
"variety",
"of",
"multi-corpus",
"transfer",
"learning",
"settings."
] |
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[
"Kernel",
"Point",
"Convolution",
"(KPConv)",
"achieves",
"cutting-edge",
"performance",
"on",
"3D",
"point",
"cloud",
"applications.",
"Unfortunately,",
"the",
"large",
"size",
"of",
"KPConv",
"network",
"limits",
"its",
"usage",
"in",
"mobile",
"scenarios.",
"In",
"addition,",
"we",
"observe",
"that",
"KPConv",
"ignores",
"the",
"kernel",
"relationship",
"and",
"treats",
"each",
"kernel",
"point",
"equally",
"when",
"formulating",
"neighbor-kernel",
"correlation",
"via",
"Euclidean",
"distance.",
"This",
"leads",
"to",
"a",
"weak",
"representation",
"power.",
"To",
"mitigate",
"the",
"above",
"issues,",
"we",
"propose",
"a",
"module",
"named",
"Mobile",
"Attention",
"Kernel",
"Point",
"Convolution",
"(MAKPConv)",
"to",
"improve",
"the",
"efficiency",
"and",
"quality",
"of",
"KPConv.",
"MAKPConv",
"employs",
"a",
"depthwise",
"kernel",
"to",
"reduce",
"resource",
"consumption",
"and",
"re-calibrates",
"the",
"contribution",
"of",
"kernel",
"points",
"towards",
"each",
"neighbor",
"point",
"via",
"Neighbor-Kernel",
"attention",
"to",
"improve",
"representation",
"power.",
"Furthermore,",
"we",
"capitalize",
"Inverted",
"Residual",
"Bottleneck",
"(IRB)",
"to",
"craft",
"a",
"design",
"space",
"and",
"employ",
"a",
"predictor-based",
"Neural",
"Architecture",
"Search",
"(NAS)",
"approach",
"to",
"automate",
"the",
"design",
"of",
"efficient",
"3D",
"networks",
"based",
"on",
"MAKPConv.",
"To",
"fully",
"exploit",
"the",
"immense",
"design",
"space",
"via",
"an",
"accurate",
"predictor,",
"we",
"identify",
"the",
"importance",
"of",
"carrying",
"feature",
"engineering",
"on",
"searchable",
"features",
"to",
"improve",
"neural",
"architecture",
"representations",
"and",
"propose",
"a",
"Wide",
"&",
"Deep",
"Predictor",
"to",
"unify",
"dense",
"and",
"sparse",
"neural",
"architecture",
"representations",
"for",
"lower",
"error",
"in",
"performance",
"prediction.",
"Experimental",
"evaluations",
"show",
"that",
"our",
"NAS-crafted",
"MAKPConv",
"network",
"uses",
"96%",
"fewer",
"parameters",
"on",
"3D",
"point",
"cloud",
"classification",
"and",
"segmentation",
"benchmarks",
"with",
"better",
"performance.",
"Compared",
"with",
"state-of-the-art",
"NAS-crafted",
"model",
"SPVNAS,",
"our",
"NAS-crafted",
"MAKPConv",
"network",
"achieves",
"~1%",
"better",
"mIOU",
"with",
"83%",
"fewer",
"parameters",
"and",
"52%",
"fewer",
"Multiply-Accumulates."
] |
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[
"This",
"work",
"proposes",
"a",
"novel",
"feature",
"selection",
"algorithm",
"to",
"classify",
"Songs",
"intodifferent",
"groups.",
"Classification",
"of",
"musical",
"content",
"is",
"often",
"a",
"non-trivial",
"joband",
"still",
"relatively",
"less",
"explored",
"area.",
"The",
"main",
"idea",
"conveyed",
"in",
"this",
"articleis",
"to",
"come",
"up",
"with",
"a",
"new",
"feature",
"selection",
"scheme",
"that",
"does",
"the",
"classificationjob",
"elegantly",
"and",
"with",
"high",
"accuracy",
"but",
"with",
"simpler",
"but",
"wisely",
"chosen",
"smallnumber",
"of",
"features",
"thus",
"being",
"less",
"prone",
"to",
"over-fitting.",
"This",
"uses",
"a",
"verybasic",
"general",
"idea",
"about",
"the",
"structure",
"of",
"the",
"audio",
"signal",
"which",
"is",
"generallyin",
"the",
"shape",
"of",
"a",
"trapezium.",
"So,",
"using",
"this",
"general",
"idea",
"of",
"the",
"MusicalCommunity",
"we",
"propose",
"three",
"frames",
"to",
"be",
"considered",
"and",
"analyzed",
"for",
"featureextraction",
"for",
"each",
"of",
"the",
"audio",
"signal",
"--",
"opening,",
"stanzas",
"and",
"closing",
"--",
"andit",
"has",
"been",
"established",
"with",
"the",
"help",
"of",
"a",
"lot",
"of",
"experiments",
"that",
"this",
"schemeleads",
"to",
"much",
"efficient",
"classification",
"with",
"less",
"complex",
"features",
"in",
"a",
"lowdimensional",
"feature",
"space",
"thus",
"is",
"also",
"a",
"computationally",
"less",
"expensive",
"method.Step",
"by",
"step",
"analysis",
"of",
"feature",
"extraction,",
"feature",
"ranking,",
"dimensionalityreduction",
"using",
"PCA",
"has",
"been",
"carried",
"in",
"this",
"article.",
"Sequential",
"Forwardselection",
"(SFS)",
"algorithm",
"is",
"used",
"to",
"explore",
"the",
"most",
"significant",
"features",
"bothwith",
"the",
"raw",
"Fisher",
"Discriminant",
"Ratio",
"(FDR)",
"and",
"also",
"with",
"the",
"significanteigen-values",
"after",
"PCA",
".",
"Also",
"during",
"classification",
"extensive",
"validation",
"andcross",
"validation",
"has",
"been",
"done",
"in",
"a",
"monte-carlo",
"manner",
"to",
"ensure",
"validity",
"ofthe",
"claims."
] |
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[
"Machine",
"learning",
"methods",
"with",
"quantitative",
"imaging",
"features",
"integration",
"have",
"recently",
"gained",
"a",
"lot",
"of",
"attention",
"for",
"lung",
"nodule",
"classification.",
"However,",
"there",
"is",
"a",
"dearth",
"of",
"studies",
"in",
"the",
"literature",
"on",
"effective",
"features",
"ranking",
"methods",
"for",
"classification",
"purpose.",
"Moreover,",
"optimal",
"number",
"of",
"features",
"required",
"for",
"the",
"classification",
"task",
"also",
"needs",
"to",
"be",
"evaluated.",
"In",
"this",
"study,",
"we",
"investigate",
"the",
"impact",
"of",
"supervised",
"and",
"unsupervised",
"feature",
"selection",
"techniques",
"on",
"machine",
"learning",
"methods",
"for",
"nodule",
"classification",
"in",
"Computed",
"Tomography",
"(CT)",
"images.",
"The",
"research",
"work",
"explores",
"the",
"classification",
"performance",
"of",
"Naive",
"Bayes",
"and",
"Support",
"Vector",
"Machine(SVM",
")",
"when",
"trained",
"with",
"2,",
"4,",
"8,",
"12,",
"16",
"and",
"20",
"highly",
"ranked",
"features",
"from",
"supervised",
"and",
"unsupervised",
"ranking",
"approaches.",
"The",
"best",
"classification",
"results",
"were",
"achieved",
"using",
"SVM",
"trained",
"with",
"8",
"radiomic",
"features",
"selected",
"from",
"supervised",
"feature",
"ranking",
"methods",
"and",
"the",
"accuracy",
"was",
"100%.",
"The",
"study",
"further",
"revealed",
"that",
"very",
"good",
"nodule",
"classification",
"can",
"be",
"achieved",
"by",
"training",
"any",
"of",
"the",
"SVM",
"or",
"Naive",
"Bayes",
"with",
"a",
"fewer",
"radiomic",
"features.",
"A",
"periodic",
"increment",
"in",
"the",
"number",
"of",
"radiomic",
"features",
"from",
"2",
"to",
"20",
"did",
"not",
"improve",
"the",
"classification",
"results",
"whether",
"the",
"selection",
"was",
"made",
"using",
"supervised",
"or",
"unsupervised",
"ranking",
"approaches."
] |
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[
"This",
"paper",
"presents",
"our",
"approach",
"to",
"address",
"the",
"EACL",
"WANLP-2021",
"Shared",
"Task",
"01:00",
"Nuanced",
"Arabic",
"Dialect",
"Identification",
"(NADI).",
"The",
"task",
"is",
"aimed",
"at",
"developing",
"a",
"system",
"that",
"identifies",
"the",
"geographical",
"location(country/province)",
"from",
"where",
"an",
"Arabic",
"tweet",
"in",
"the",
"form",
"of",
"modern",
"standard",
"Arabic",
"or",
"dialect",
"comes",
"from.",
"We",
"solve",
"the",
"task",
"in",
"two",
"parts.",
"The",
"first",
"part",
"involves",
"pre-processing",
"the",
"provided",
"dataset",
"by",
"cleaning,",
"adding",
"and",
"segmenting",
"various",
"parts",
"of",
"the",
"text.",
"This",
"is",
"followed",
"by",
"carrying",
"out",
"experiments",
"with",
"different",
"versions",
"of",
"two",
"Transformer",
"based",
"models,",
"AraBERT",
"and",
"AraELECTRA.",
"Our",
"final",
"approach",
"achieved",
"macro",
"F1-scores",
"of",
"0.216,",
"0.235,",
"0.054,",
"and",
"0.043",
"in",
"the",
"four",
"subtasks,",
"and",
"we",
"were",
"ranked",
"second",
"in",
"MSA",
"identification",
"subtasks",
"and",
"fourth",
"in",
"DA",
"identification",
"subtasks."
] |
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[
"Deep",
"Convolutional",
"Neural",
"Networks",
"(DCNNs)",
"are",
"hard",
"and",
"time-consuming",
"to",
"train.",
"Normalization",
"is",
"one",
"of",
"the",
"effective",
"solutions.",
"Among",
"previous",
"normalization",
"methods,",
"Batch",
"Normalization",
"(BN)",
"performs",
"well",
"at",
"medium",
"and",
"large",
"batch",
"sizes",
"and",
"is",
"with",
"good",
"generalizability",
"to",
"multiple",
"vision",
"tasks,",
"while",
"its",
"performance",
"degrades",
"significantly",
"at",
"small",
"batch",
"sizes.",
"In",
"this",
"paper,",
"we",
"find",
"that",
"BN",
"saturates",
"at",
"extreme",
"large",
"batch",
"sizes,",
"i.e.,",
"128",
"images",
"per",
"worker,",
"i.e.,",
"GPU,",
"as",
"well",
"and",
"propose",
"that",
"the",
"degradation/saturation",
"of",
"BN",
"at",
"small/extreme",
"large",
"batch",
"sizes",
"is",
"caused",
"by",
"noisy/confused",
"statistic",
"calculation.",
"Hence",
"without",
"adding",
"new",
"trainable",
"parameters,",
"using",
"multiple-layer",
"or",
"multi-iteration",
"information,",
"or",
"introducing",
"extra",
"computation,",
"Batch",
"Group",
"Normalization",
"(BGN)",
"is",
"proposed",
"to",
"solve",
"the",
"noisy/confused",
"statistic",
"calculation",
"of",
"BN",
"at",
"small/extreme",
"large",
"batch",
"sizes",
"with",
"introducing",
"the",
"channel,",
"height",
"and",
"width",
"dimension",
"to",
"compensate.",
"The",
"group",
"technique",
"in",
"Group",
"Normalization",
"(GN)",
"is",
"used",
"and",
"a",
"hyper-parameter",
"G",
"is",
"used",
"to",
"control",
"the",
"number",
"of",
"feature",
"instances",
"used",
"for",
"statistic",
"calculation,",
"hence",
"to",
"offer",
"neither",
"noisy",
"nor",
"confused",
"statistic",
"for",
"different",
"batch",
"sizes.",
"We",
"empirically",
"demonstrate",
"that",
"BGN",
"consistently",
"outperforms",
"BN,",
"Instance",
"Normalization",
"(IN),",
"Layer",
"Normalization",
"(LN),",
"GN,",
"and",
"Positional",
"Normalization",
"(PN),",
"across",
"a",
"wide",
"spectrum",
"of",
"vision",
"tasks,",
"including",
"image",
"classification,",
"Neural",
"Architecture",
"Search",
"(NAS),",
"adversarial",
"learning,",
"Few",
"Shot",
"Learning",
"(FSL)",
"and",
"Unsupervised",
"Domain",
"Adaptation",
"(UDA),",
"indicating",
"its",
"good",
"performance,",
"robust",
"stability",
"to",
"batch",
"size",
"and",
"wide",
"generalizability.",
"For",
"example,",
"for",
"training",
"ResNet-50",
"on",
"ImageNet",
"with",
"a",
"batch",
"size",
"of",
"2,",
"BN",
"achieves",
"Top1",
"accuracy",
"of",
"66.51%",
"while",
"BGN",
"achieves",
"76.10%",
"with",
"notable",
"improvement."
] |
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[
"This",
"paper",
"presents",
"a",
"method",
"that",
"conbines",
"a",
"set",
"of",
"unsupervised",
"algorithms",
"in",
"order",
"to",
"accurately",
"build",
"large",
"taxonomies",
"from",
"any",
"machine-readable",
"dictionary",
"-LRB-",
"MRD",
"-RRB-",
".",
"Our",
"aim",
"is",
"to",
"profit",
"from",
"conventional",
"MRDs",
",",
"with",
"no",
"explicit",
"semantic",
"coding",
".",
"We",
"propose",
"a",
"system",
"that",
"1",
"-RRB-",
"performs",
"fully",
"automatic",
"extraction",
"of",
"taxonomic",
"links",
"from",
"MRD",
"entries",
"and",
"2",
"-RRB-",
"ranks",
"the",
"extracted",
"relations",
"in",
"a",
"way",
"that",
"selective",
"manual",
"refinement",
"is",
"allowed",
".",
"Tested",
"accuracy",
"can",
"reach",
"around",
"100",
"%",
"depending",
"on",
"the",
"degree",
"of",
"coverage",
"selected",
",",
"showing",
"that",
"taxonomy",
"building",
"is",
"not",
"limited",
"to",
"structured",
"dictionaries",
"such",
"as",
"LDOCE",
"."
] |
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[
"Dialogue",
"State",
"Tracking",
"(DST)",
"is",
"a",
"core",
"component",
"of",
"virtual",
"assistants",
"such",
"as",
"Alexa",
"or",
"Siri.",
"To",
"accomplish",
"various",
"tasks,",
"these",
"assistants",
"need",
"to",
"support",
"an",
"increasing",
"number",
"of",
"services",
"and",
"APIs.",
"The",
"Schema-Guided",
"State",
"Tracking",
"track",
"of",
"the",
"8th",
"Dialogue",
"System",
"Technology",
"Challenge",
"highlighted",
"the",
"DST",
"problem",
"for",
"unseen",
"services.",
"The",
"organizers",
"introduced",
"the",
"Schema-Guided",
"Dialogue",
"(SGD",
")",
"dataset",
"with",
"multi-domain",
"conversations",
"and",
"released",
"a",
"zero-shot",
"dialogue",
"state",
"tracking",
"model.",
"In",
"this",
"work,",
"we",
"propose",
"a",
"GOaL-Oriented",
"Multi-task",
"BERT-based",
"dialogue",
"state",
"tracker",
"(GOLOMB)",
"inspired",
"by",
"architectures",
"for",
"reading",
"comprehension",
"question",
"answering",
"systems.",
"The",
"model",
"queries",
"dialogue",
"history",
"with",
"descriptions",
"of",
"slots",
"and",
"services",
"as",
"well",
"as",
"possible",
"values",
"of",
"slots.",
"This",
"allows",
"to",
"transfer",
"slot",
"values",
"in",
"multi-domain",
"dialogues",
"and",
"have",
"a",
"capability",
"to",
"scale",
"to",
"unseen",
"slot",
"types.",
"Our",
"model",
"achieves",
"a",
"joint",
"goal",
"accuracy",
"of",
"53.97%",
"on",
"the",
"SGD",
"dataset,",
"outperforming",
"the",
"baseline",
"model."
] |
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[
"Existing",
"literature",
"on",
"Question",
"Answering",
"(QA)",
"mostly",
"focuses",
"on",
"algorithmic",
"novelty,",
"data",
"augmentation,",
"or",
"increasingly",
"large",
"pre-trained",
"language",
"models",
"like",
"XLNet",
"and",
"RoBERT",
"a.",
"Additionally,",
"a",
"lot",
"of",
"systems",
"on",
"the",
"QA",
"leaderboards",
"do",
"not",
"have",
"associated",
"research",
"documentation",
"in",
"order",
"to",
"successfully",
"replicate",
"their",
"experiments.",
"In",
"this",
"paper,",
"we",
"outline",
"these",
"algorithmic",
"components",
"such",
"as",
"Attention-over-Attention,",
"coupled",
"with",
"data",
"augmentation",
"and",
"ensembling",
"strategies",
"that",
"have",
"shown",
"to",
"yield",
"state-of-the-art",
"results",
"on",
"benchmark",
"datasets",
"like",
"SQuAD,",
"even",
"achieving",
"super-human",
"performance.",
"Contrary",
"to",
"these",
"prior",
"results,",
"when",
"we",
"evaluate",
"on",
"the",
"recently",
"proposed",
"Natural",
"Questions",
"benchmark",
"dataset,",
"we",
"find",
"that",
"an",
"incredibly",
"simple",
"approach",
"of",
"transfer",
"learning",
"from",
"BERT",
"outperforms",
"the",
"previous",
"state-of-the-art",
"system",
"trained",
"on",
"4",
"million",
"more",
"examples",
"than",
"ours",
"by",
"1.9",
"F1",
"points.",
"Adding",
"ensembling",
"strategies",
"further",
"improves",
"that",
"number",
"by",
"2.3",
"F1",
"points."
] |
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[
"In",
"transmission",
"X-ray",
"microscopy",
"(TXM)",
"systems,",
"the",
"rotation",
"of",
"a",
"scanned",
"sample",
"might",
"be",
"restricted",
"to",
"a",
"limited",
"angular",
"range",
"to",
"avoid",
"collision",
"to",
"other",
"system",
"parts",
"or",
"high",
"attenuation",
"at",
"certain",
"tilting",
"angles.",
"Image",
"reconstruction",
"from",
"such",
"limited",
"angle",
"data",
"suffers",
"from",
"artifacts",
"due",
"to",
"missing",
"data.",
"In",
"this",
"work,",
"deep",
"learning",
"is",
"applied",
"to",
"limited",
"angle",
"reconstruction",
"in",
"TXMs",
"for",
"the",
"first",
"time.",
"With",
"the",
"challenge",
"to",
"obtain",
"sufficient",
"real",
"data",
"for",
"training,",
"training",
"a",
"deep",
"neural",
"network",
"from",
"synthetic",
"data",
"is",
"investigated.",
"Particularly,",
"the",
"U-Net",
",",
"the",
"state-of-the-art",
"neural",
"network",
"in",
"biomedical",
"imaging,",
"is",
"trained",
"from",
"synthetic",
"ellipsoid",
"data",
"and",
"multi-category",
"data",
"to",
"reduce",
"artifacts",
"in",
"filtered",
"back-projection",
"(FBP)",
"reconstruction",
"images.",
"The",
"proposed",
"method",
"is",
"evaluated",
"on",
"synthetic",
"data",
"and",
"real",
"scanned",
"chlorella",
"data",
"in",
"$100^\\circ$",
"limited",
"angle",
"tomography.",
"For",
"synthetic",
"test",
"data,",
"the",
"U-Net",
"significantly",
"reduces",
"root-mean-square",
"error",
"(RMSE)",
"from",
"$2.55",
"\\times",
"10^{-3}$",
"{\\mu}m$^{-1}$",
"in",
"the",
"FBP",
"reconstruction",
"to",
"$1.21",
"\\times",
"10^{-3}$",
"{\\mu}m$^{-1}$",
"in",
"the",
"U-Net",
"reconstruction,",
"and",
"also",
"improves",
"structural",
"similarity",
"(SSIM",
")",
"index",
"from",
"0.625",
"to",
"0.920.",
"With",
"penalized",
"weighted",
"least",
"square",
"denoising",
"of",
"measured",
"projections,",
"the",
"RMSE",
"and",
"SSIM",
"are",
"further",
"improved",
"to",
"$1.16",
"\\times",
"10^{-3}$",
"{\\mu}m$^{-1}$",
"and",
"0.932,",
"respectively.",
"For",
"real",
"test",
"data,",
"the",
"proposed",
"method",
"remarkably",
"improves",
"the",
"3-D",
"visualization",
"of",
"the",
"subcellular",
"structures",
"in",
"the",
"chlorella",
"cell,",
"which",
"indicates",
"its",
"important",
"value",
"for",
"nano-scale",
"imaging",
"in",
"biology,",
"nanoscience",
"and",
"materials",
"science."
] |
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[
"Nowadays,",
"deep",
"learning",
"methods,",
"especially",
"the",
"Graph",
"Convolutional",
"Network",
"(GCN",
"),",
"have",
"shown",
"impressive",
"performance",
"in",
"hyperspectral",
"image",
"(HSI)",
"classification.",
"However,",
"the",
"current",
"GCN",
"#NAME?",
"methods",
"treat",
"graph",
"construction",
"and",
"image",
"classification",
"as",
"two",
"separate",
"tasks,",
"which",
"often",
"results",
"in",
"suboptimal",
"performance.",
"Another",
"defect",
"of",
"these",
"methods",
"is",
"that",
"they",
"mainly",
"focus",
"on",
"modeling",
"the",
"local",
"pairwise",
"importance",
"between",
"graph",
"nodes",
"while",
"lack",
"the",
"capability",
"to",
"capture",
"the",
"global",
"contextual",
"information",
"of",
"HSI.",
"In",
"this",
"paper,",
"we",
"propose",
"a",
"Multi-level",
"GCN",
"with",
"Automatic",
"Graph",
"Learning",
"method",
"(MGCN",
"-AGL)",
"for",
"HSI",
"classification,",
"which",
"can",
"automatically",
"learn",
"the",
"graph",
"information",
"at",
"both",
"local",
"and",
"global",
"levels.",
"By",
"employing",
"attention",
"mechanism",
"to",
"characterize",
"the",
"importance",
"among",
"spatially",
"neighboring",
"regions,",
"the",
"most",
"relevant",
"information",
"can",
"be",
"adaptively",
"incorporated",
"to",
"make",
"decisions,",
"which",
"helps",
"encode",
"the",
"spatial",
"context",
"to",
"form",
"the",
"graph",
"information",
"at",
"local",
"level.",
"Moreover,",
"we",
"utilize",
"multiple",
"pathways",
"for",
"local-level",
"graph",
"convolution,",
"in",
"order",
"to",
"leverage",
"the",
"merits",
"from",
"the",
"diverse",
"spatial",
"context",
"of",
"HSI",
"and",
"to",
"enhance",
"the",
"expressive",
"power",
"of",
"the",
"generated",
"representations.",
"To",
"reconstruct",
"the",
"global",
"contextual",
"relations,",
"our",
"MGCN",
"#NAME?",
"encodes",
"the",
"long",
"range",
"dependencies",
"among",
"image",
"regions",
"based",
"on",
"the",
"expressive",
"representations",
"that",
"have",
"been",
"produced",
"at",
"local",
"level.",
"Then",
"inference",
"can",
"be",
"performed",
"along",
"the",
"reconstructed",
"graph",
"edges",
"connecting",
"faraway",
"regions.",
"Finally,",
"the",
"multi-level",
"information",
"is",
"adaptively",
"fused",
"to",
"generate",
"the",
"network",
"output.",
"In",
"this",
"means,",
"the",
"graph",
"learning",
"and",
"image",
"classification",
"can",
"be",
"integrated",
"into",
"a",
"unified",
"framework",
"and",
"benefit",
"each",
"other.",
"Extensive",
"experiments",
"have",
"been",
"conducted",
"on",
"three",
"real-world",
"hyperspectral",
"datasets,",
"which",
"are",
"shown",
"to",
"outperform",
"the",
"state-of-the-art",
"methods."
] |
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[
"Transformer-based",
"language",
"models",
"such",
"as",
"BERT",
"have",
"outperformed",
"previous",
"models",
"on",
"a",
"large",
"number",
"of",
"English",
"benchmarks,",
"but",
"their",
"evaluation",
"is",
"often",
"limited",
"to",
"English",
"or",
"a",
"small",
"number",
"of",
"well-resourced",
"languages.",
"In",
"this",
"work,",
"we",
"evaluate",
"monolingual,",
"multilingual,",
"and",
"randomly",
"initialized",
"language",
"models",
"from",
"the",
"BERT",
"family",
"on",
"a",
"variety",
"of",
"Uralic",
"languages",
"including",
"Estonian,",
"Finnish,",
"Hungarian,",
"Erzya,",
"Moksha,",
"Karelian,",
"Livvi,",
"Komi",
"Permyak,",
"Komi",
"Zyrian,",
"Northern",
"S\\'ami,",
"and",
"Skolt",
"S\\'ami.",
"When",
"monolingual",
"models",
"are",
"available",
"(currently",
"only",
"et,",
"fi,",
"hu),",
"these",
"perform",
"better",
"on",
"their",
"native",
"language,",
"but",
"in",
"general",
"they",
"transfer",
"worse",
"than",
"multilingual",
"models",
"or",
"models",
"of",
"genetically",
"unrelated",
"languages",
"that",
"share",
"the",
"same",
"character",
"set.",
"Remarkably,",
"straightforward",
"transfer",
"of",
"high-resource",
"models,",
"even",
"without",
"special",
"efforts",
"toward",
"hyperparameter",
"optimization,",
"yields",
"what",
"appear",
"to",
"be",
"state",
"of",
"the",
"art",
"POS",
"and",
"NER",
"tools",
"for",
"the",
"minority",
"Uralic",
"languages",
"where",
"there",
"is",
"sufficient",
"data",
"for",
"finetuning."
] |
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[
"Temporal",
"Action",
"Localization",
"(TAL)",
"task",
"in",
"which",
"the",
"aim",
"is",
"to",
"predict",
"the",
"start",
"and",
"end",
"of",
"each",
"action",
"and",
"its",
"class",
"label",
"has",
"many",
"applications",
"in",
"the",
"real",
"world.",
"But",
"due",
"to",
"its",
"complexity,",
"researchers",
"have",
"not",
"reached",
"great",
"results",
"compared",
"to",
"the",
"action",
"recognition",
"task.",
"The",
"complexity",
"is",
"related",
"to",
"predicting",
"precise",
"start",
"and",
"end",
"times",
"for",
"different",
"actions",
"in",
"any",
"video.",
"In",
"this",
"paper,",
"we",
"propose",
"a",
"new",
"network",
"based",
"on",
"Gated",
"Recurrent",
"Unit",
"(GRU",
")",
"and",
"two",
"novel",
"post-processing",
"ideas",
"for",
"TAL",
"task.",
"Specifically,",
"we",
"propose",
"a",
"new",
"design",
"for",
"the",
"output",
"layer",
"of",
"the",
"GRU",
"resulting",
"in",
"the",
"so-called",
"GRU",
"#NAME?",
"model.",
"Moreover,",
"linear",
"interpolation",
"is",
"used",
"to",
"generate",
"the",
"action",
"proposals",
"with",
"precise",
"start",
"and",
"end",
"times.",
"Finally,",
"to",
"rank",
"the",
"generated",
"proposals",
"appropriately,",
"we",
"use",
"a",
"Learn",
"to",
"Rank",
"(LTR)",
"approach.",
"We",
"evaluated",
"the",
"performance",
"of",
"the",
"proposed",
"method",
"on",
"Thumos14",
"dataset.",
"Results",
"show",
"the",
"superiority",
"of",
"the",
"performance",
"of",
"the",
"proposed",
"method",
"compared",
"to",
"state-of-the-art.",
"Especially",
"in",
"the",
"mean",
"Average",
"Precision",
"(mAP)",
"metric",
"at",
"Intersection",
"over",
"Union",
"(IoU)",
"0.7,",
"we",
"get",
"27.52%",
"which",
"is",
"5.12%",
"better",
"than",
"that",
"of",
"state-of-the-art",
"methods."
] |
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[
"Literature-based",
"knowledge",
"discovery",
"process",
"identifies",
"the",
"important",
"but",
"implicit",
"relations",
"among",
"information",
"embedded",
"in",
"published",
"literature.",
"Existing",
"techniques",
"from",
"Information",
"Retrieval",
"and",
"Natural",
"Language",
"Processing",
"attempt",
"to",
"identify",
"the",
"hidden",
"or",
"unpublished",
"connections",
"between",
"information",
"concepts",
"within",
"published",
"literature,",
"however,",
"these",
"techniques",
"undermine",
"the",
"concept",
"of",
"predicting",
"the",
"future",
"and",
"emerging",
"relations",
"among",
"scientific",
"knowledge",
"components",
"encapsulated",
"within",
"the",
"literature.",
"Keyword",
"Co-occurrence",
"Network",
"(KCN),",
"built",
"upon",
"author",
"selected",
"keywords",
"(i.e.,",
"knowledge",
"entities),",
"is",
"considered",
"as",
"a",
"knowledge",
"graph",
"that",
"focuses",
"both",
"on",
"these",
"knowledge",
"components",
"and",
"knowledge",
"structure",
"of",
"a",
"scientific",
"domain",
"by",
"examining",
"the",
"relationships",
"between",
"knowledge",
"entities.",
"Using",
"data",
"from",
"two",
"multidisciplinary",
"research",
"domains",
"other",
"than",
"the",
"medical",
"domain,",
"capitalizing",
"on",
"bibliometrics,",
"the",
"dynamicity",
"of",
"temporal",
"KCNs,",
"and",
"a",
"Long",
"Short",
"Term",
"Memory",
"recurrent",
"neural",
"network,",
"this",
"study",
"proposed",
"a",
"framework",
"to",
"successfully",
"predict",
"the",
"future",
"literature-based",
"discoveries",
"-",
"the",
"emerging",
"connections",
"among",
"knowledge",
"units.",
"Framing",
"the",
"problem",
"as",
"a",
"dynamic",
"supervised",
"link",
"prediction",
"task,",
"the",
"proposed",
"framework",
"integrates",
"some",
"novel",
"node",
"and",
"edge-level",
"features.",
"Temporal",
"importance",
"of",
"keywords",
"computed",
"from",
"both",
"bipartite",
"and",
"unipartite",
"networks,",
"communities",
"of",
"keywords,",
"built",
"upon",
"genealogical",
"relations,",
"and",
"relative",
"importance",
"of",
"temporal",
"citation",
"counts",
"used",
"in",
"the",
"feature",
"construction",
"process.",
"Both",
"node",
"and",
"edge-level",
"features",
"were",
"input",
"into",
"an",
"LSTM",
"network",
"to",
"forecast",
"the",
"feature",
"values",
"for",
"positive",
"and",
"negatively",
"labeled",
"non-connected",
"keyword",
"pairs",
"and",
"classify",
"them",
"accurately.",
"High",
"classification",
"performance",
"rates",
"suggest",
"that",
"these",
"features",
"are",
"supportive",
"both",
"in",
"predicting",
"the",
"emerging",
"connections",
"between",
"scientific",
"knowledge",
"units",
"and",
"emerging",
"trend",
"analysis."
] |
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[
"This",
"paper",
"describes",
"our",
"systems",
"for",
"the",
"VarDial",
"2018",
"evaluation",
"campaign.",
"We",
"participated",
"in",
"all",
"language",
"identification",
"tasks,",
"namely,",
"Arabic",
"dialect",
"identification",
"(ADI),",
"German",
"dialect",
"identification",
"(GDI),",
"discriminating",
"between",
"Dutch",
"and",
"Flemish",
"in",
"Subtitles",
"(DFS),",
"and",
"Indo-Aryan",
"Language",
"Identification",
"(ILI).",
"In",
"all",
"of",
"the",
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"and",
"relations",
"may",
"appear",
"in",
"different",
"graph",
"contexts,",
"and",
"accordingly,",
"exhibit",
"different",
"properties.",
"This",
"work",
"presents",
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"Knowledge",
"Graph",
"Embedding",
"(CoKE),",
"a",
"novel",
"paradigm",
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"takes",
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"such",
"contextual",
"nature,",
"and",
"learns",
"dynamic,",
"flexible,",
"and",
"fully",
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"entity",
"and",
"relation",
"embeddings.",
"Two",
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"of",
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"contexts",
"are",
"studied:",
"edges",
"and",
"paths,",
"both",
"formulated",
"as",
"sequences",
"of",
"entities",
"and",
"relations.",
"CoKE",
"takes",
"a",
"sequence",
"as",
"input",
"and",
"uses",
"a",
"Transformer",
"encoder",
"to",
"obtain",
"contextualized",
"representations.",
"These",
"representations",
"are",
"hence",
"naturally",
"adaptive",
"to",
"the",
"input,",
"capturing",
"contextual",
"meanings",
"of",
"entities",
"and",
"relations",
"therein.",
"Evaluation",
"on",
"a",
"wide",
"variety",
"of",
"public",
"benchmarks",
"verifies",
"the",
"superiority",
"of",
"CoKE",
"in",
"link",
"prediction",
"and",
"path",
"query",
"answering.",
"It",
"performs",
"consistently",
"better",
"than,",
"or",
"at",
"least",
"equally",
"well",
"as",
"current",
"state-of-the-art",
"in",
"almost",
"every",
"case,",
"in",
"particular",
"offering",
"an",
"absolute",
"improvement",
"of",
"21.00%",
"in",
"H@10",
"on",
"path",
"query",
"answering.",
"Our",
"code",
"is",
"available",
"at",
"\\url{https://github.com/PaddlePaddle/Research/tree/master/KG/CoKE}."
] |
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[
"Face",
"swapping",
"has",
"both",
"positive",
"applications",
"such",
"as",
"entertainment,",
"human-computer",
"interaction,",
"etc.,",
"and",
"negative",
"applications",
"such",
"as",
"DeepFake",
"threats",
"to",
"politics,",
"economics,",
"etc.",
"Nevertheless,",
"it",
"is",
"necessary",
"to",
"understand",
"the",
"scheme",
"of",
"advanced",
"methods",
"for",
"high-quality",
"face",
"swapping",
"and",
"generate",
"enough",
"and",
"representative",
"face",
"swapping",
"images",
"to",
"train",
"DeepFake",
"detection",
"algorithms.",
"This",
"paper",
"proposes",
"the",
"first",
"Megapixel",
"level",
"method",
"for",
"one",
"shot",
"Face",
"Swapping",
"(or",
"MegaFS",
"for",
"short).",
"Firstly,",
"MegaFS",
"organizes",
"face",
"representation",
"hierarchically",
"by",
"the",
"proposed",
"Hierarchical",
"Representation",
"Face",
"Encoder",
"(HieRFE)",
"in",
"an",
"extended",
"latent",
"space",
"to",
"maintain",
"more",
"facial",
"details,",
"rather",
"than",
"compressed",
"representation",
"in",
"previous",
"face",
"swapping",
"methods.",
"Secondly,",
"a",
"carefully",
"designed",
"Face",
"Transfer",
"Module",
"(FTM)",
"is",
"proposed",
"to",
"transfer",
"the",
"identity",
"from",
"a",
"source",
"image",
"to",
"the",
"target",
"by",
"a",
"non-linear",
"trajectory",
"without",
"explicit",
"feature",
"disentanglement.",
"Finally,",
"the",
"swapped",
"faces",
"can",
"be",
"synthesized",
"by",
"StyleGAN2",
"with",
"the",
"benefits",
"of",
"its",
"training",
"stability",
"and",
"powerful",
"generative",
"capability.",
"Each",
"part",
"of",
"MegaFS",
"can",
"be",
"trained",
"separately",
"so",
"the",
"requirement",
"of",
"our",
"model",
"for",
"GPU",
"memory",
"can",
"be",
"satisfied",
"for",
"megapixel",
"face",
"swapping.",
"In",
"summary,",
"complete",
"face",
"representation,",
"stable",
"training,",
"and",
"limited",
"memory",
"usage",
"are",
"the",
"three",
"novel",
"contributions",
"to",
"the",
"success",
"of",
"our",
"method.",
"Extensive",
"experiments",
"demonstrate",
"the",
"superiority",
"of",
"MegaFS",
"and",
"the",
"first",
"megapixel",
"level",
"face",
"swapping",
"database",
"is",
"released",
"for",
"research",
"on",
"DeepFake",
"detection",
"and",
"face",
"image",
"editing",
"in",
"the",
"public",
"domain.",
"The",
"dataset",
"is",
"at",
"this",
"link."
] |
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[
"Multi-Criteria",
"Chinese",
"Word",
"Segmentation",
"(MCCWS)",
"aims",
"at",
"finding",
"word",
"boundaries",
"in",
"a",
"Chinese",
"sentence",
"composed",
"of",
"continuous",
"characters",
"while",
"multiple",
"segmentation",
"criteria",
"exist.",
"The",
"unified",
"framework",
"has",
"been",
"widely",
"used",
"in",
"MCCWS",
"and",
"shows",
"its",
"effectiveness.",
"Besides,",
"the",
"pre-trained",
"BERT",
"language",
"model",
"has",
"been",
"also",
"introduced",
"into",
"the",
"MCCWS",
"task",
"in",
"a",
"multi-task",
"learning",
"framework.",
"In",
"this",
"paper,",
"we",
"combine",
"the",
"superiority",
"of",
"the",
"unified",
"framework",
"and",
"pretrained",
"language",
"model,",
"and",
"propose",
"a",
"unified",
"MCCWS",
"model",
"based",
"on",
"BERT",
".",
"Moreover,",
"we",
"augment",
"the",
"unified",
"BERT",
"#NAME?",
"MCCWS",
"model",
"with",
"the",
"bigram",
"features",
"and",
"an",
"auxiliary",
"criterion",
"classification",
"task.",
"Experiments",
"on",
"eight",
"datasets",
"with",
"diverse",
"criteria",
"demonstrate",
"that",
"our",
"methods",
"could",
"achieve",
"new",
"state-of-the-art",
"results",
"for",
"MCCWS."
] |
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[
"Dynamic",
"Time",
"Warping",
"(DTW",
")",
"is",
"widely",
"used",
"for",
"temporal",
"data",
"processing.",
"However,",
"existing",
"methods",
"can",
"neither",
"learn",
"the",
"discriminative",
"prototypes",
"of",
"different",
"classes",
"nor",
"exploit",
"such",
"prototypes",
"for",
"further",
"analysis.",
"We",
"propose",
"Discriminative",
"Prototype",
"DTW",
"(DP-DTW",
"),",
"a",
"novel",
"method",
"to",
"learn",
"class-specific",
"discriminative",
"prototypes",
"for",
"temporal",
"recognition",
"tasks.",
"DP-DTW",
"shows",
"superior",
"performance",
"compared",
"to",
"conventional",
"DTW",
"s",
"on",
"time",
"series",
"classification",
"benchmarks.",
"Combined",
"with",
"end-to-end",
"deep",
"learning,",
"DP-DTW",
"can",
"handle",
"challenging",
"weakly",
"supervised",
"action",
"segmentation",
"problems",
"and",
"achieves",
"state",
"of",
"the",
"art",
"results",
"on",
"standard",
"benchmarks.",
"Moreover,",
"detailed",
"reasoning",
"on",
"the",
"input",
"video",
"is",
"enabled",
"by",
"the",
"learned",
"action",
"prototypes.",
"Specifically,",
"an",
"action-based",
"video",
"summarization",
"can",
"be",
"obtained",
"by",
"aligning",
"the",
"input",
"sequence",
"with",
"action",
"prototypes."
] |
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[
"One",
"of",
"the",
"important",
"research",
"topics",
"in",
"image",
"generative",
"models",
"is",
"to",
"disentangle",
"the",
"spatial",
"contents",
"and",
"styles",
"for",
"their",
"separate",
"control.",
"Although",
"StyleGAN",
"can",
"generate",
"content",
"feature",
"vectors",
"from",
"random",
"noises,",
"the",
"resulting",
"spatial",
"content",
"control",
"is",
"primarily",
"intended",
"for",
"minor",
"spatial",
"variations,",
"and",
"the",
"disentanglement",
"of",
"global",
"content",
"and",
"styles",
"is",
"by",
"no",
"means",
"complete.",
"Inspired",
"by",
"a",
"mathematical",
"understanding",
"of",
"normalization",
"and",
"attention,",
"here",
"we",
"present",
"a",
"novel",
"hierarchical",
"adaptive",
"Diagonal",
"spatial",
"ATtention",
"(DAT)",
"layers",
"to",
"separately",
"manipulate",
"the",
"spatial",
"contents",
"from",
"styles",
"in",
"a",
"hierarchical",
"manner.",
"Using",
"DAT",
"and",
"AdaIN,",
"our",
"method",
"enables",
"coarse-to-fine",
"level",
"disentanglement",
"of",
"spatial",
"contents",
"and",
"styles.",
"In",
"addition,",
"our",
"generator",
"can",
"be",
"easily",
"integrated",
"into",
"the",
"GAN",
"inversion",
"framework",
"so",
"that",
"the",
"content",
"and",
"style",
"of",
"translated",
"images",
"from",
"multi-domain",
"image",
"translation",
"tasks",
"can",
"be",
"flexibly",
"controlled.",
"By",
"using",
"various",
"datasets,",
"we",
"confirm",
"that",
"the",
"proposed",
"method",
"not",
"only",
"outperforms",
"the",
"existing",
"models",
"in",
"disentanglement",
"scores,",
"but",
"also",
"provides",
"more",
"flexible",
"control",
"over",
"spatial",
"features",
"in",
"the",
"generated",
"images."
] |
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[
"We",
"propose",
"to",
"leverage",
"Transformer",
"architectures",
"for",
"non-autoregressive",
"human",
"motion",
"prediction",
".",
"Our",
"approach",
"decodes",
"elements",
"in",
"parallel",
"from",
"a",
"query",
"sequence,",
"instead",
"of",
"conditioning",
"on",
"previous",
"predictions",
"such",
"as",
"instate-of-the-art",
"RNN-based",
"approaches.",
"In",
"such",
"a",
"way",
"our",
"approach",
"is",
"less",
"computational",
"intensive",
"and",
"potentially",
"avoids",
"error",
"accumulation",
"to",
"long",
"term",
"elements",
"in",
"the",
"sequence.",
"In",
"that",
"context,",
"our",
"contributions",
"are",
"fourfold:",
"(i)",
"we",
"frame",
"human",
"motion",
"prediction",
"as",
"a",
"sequence-to-sequence",
"problem",
"and",
"propose",
"a",
"non-autoregressive",
"Transformer",
"to",
"infer",
"the",
"sequences",
"of",
"poses",
"in",
"parallel;",
"(ii)",
"we",
"propose",
"to",
"decode",
"sequences",
"of",
"3D",
"poses",
"from",
"a",
"query",
"sequence",
"generated",
"in",
"advance",
"with",
"elements",
"from",
"the",
"input",
"sequence;(iii)",
"we",
"propose",
"to",
"perform",
"skeleton-based",
"activity",
"classification",
"from",
"the",
"encoder",
"memory,",
"in",
"the",
"hope",
"that",
"identifying",
"the",
"activity",
"can",
"improve",
"predictions;(iv)",
"we",
"show",
"that",
"despite",
"its",
"simplicity,",
"our",
"approach",
"achieves",
"competitive",
"results",
"in",
"two",
"public",
"datasets,",
"although",
"surprisingly",
"more",
"for",
"short",
"term",
"predictions",
"rather",
"than",
"for",
"long",
"term",
"ones."
] |
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1,
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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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[
"In",
"the",
"last",
"decade,",
"the",
"field",
"of",
"Neural",
"Language",
"Modelling",
"has",
"witnessed",
"enormous",
"changes,",
"with",
"the",
"development",
"of",
"novel",
"models",
"through",
"the",
"use",
"of",
"Transformer",
"architectures.",
"However,",
"even",
"these",
"models",
"struggle",
"to",
"model",
"long",
"sequences",
"due",
"to",
"memory",
"constraints",
"and",
"increasing",
"computational",
"complexity.",
"Coreference",
"annotations",
"over",
"the",
"training",
"data",
"can",
"provide",
"context",
"far",
"beyond",
"the",
"modelling",
"limitations",
"of",
"such",
"language",
"models.",
"In",
"this",
"paper",
"we",
"present",
"an",
"extension",
"over",
"the",
"Transformer",
"#NAME?",
"architecture",
"used",
"in",
"neural",
"language",
"models,",
"specifically",
"in",
"GPT2,",
"in",
"order",
"to",
"incorporate",
"entity",
"annotations",
"during",
"training.",
"Our",
"model,",
"GPT2E,",
"extends",
"the",
"Transformer",
"layers",
"architecture",
"of",
"GPT2",
"to",
"Entity-Transformer",
"s,",
"an",
"architecture",
"designed",
"to",
"handle",
"coreference",
"information",
"when",
"present.",
"To",
"that",
"end,",
"we",
"achieve",
"richer",
"representations",
"for",
"entity",
"mentions,",
"with",
"insignificant",
"training",
"cost.",
"We",
"show",
"the",
"comparative",
"model",
"performance",
"between",
"GPT2",
"and",
"GPT2E",
"in",
"terms",
"of",
"Perplexity",
"on",
"the",
"CoNLL",
"2012",
"and",
"LAMBADA",
"datasets",
"as",
"well",
"as",
"the",
"key",
"differences",
"in",
"the",
"entity",
"representations",
"and",
"their",
"effects",
"in",
"downstream",
"tasks",
"such",
"as",
"Named",
"Entity",
"Recognition.",
"Furthermore,",
"our",
"approach",
"can",
"be",
"adopted",
"by",
"the",
"majority",
"of",
"Transformer",
"#NAME?",
"language",
"models."
] |
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6
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