tokens
list | ner_tags
list |
|---|---|
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"analysis",
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"present",
"article,",
"we",
"propose",
"to",
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"generalization",
"ability",
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"benchmarks",
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"Occupational",
"data",
"mining",
"and",
"analysis",
"is",
"an",
"important",
"task",
"in",
"understanding",
"today's",
"industry",
"and",
"job",
"market.",
"Various",
"machine",
"learning",
"techniques",
"are",
"proposed",
"and",
"gradually",
"deployed",
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"operations",
"for",
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"blocks,",
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"tasks",
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"address",
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"data",
"mining",
"and",
"analysis",
"problems.",
"In",
"this",
"work,",
"we",
"present",
"the",
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"and",
"Professional",
"Occupations",
"Dataset",
"(IPOD),",
"which",
"consists",
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"190,000",
"job",
"titles",
"crawled",
"from",
"over",
"56,000",
"profiles",
"from",
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"also",
"illustrate",
"the",
"usefulness",
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"IPOD",
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"addressing",
"two",
"challenging",
"upstream",
"tasks,",
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"proposing",
"Title2vec,",
"a",
"contextual",
"job",
"title",
"vector",
"representation",
"using",
"a",
"bidirectional",
"Language",
"Model",
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"approach;",
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"addressing",
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"Named",
"Entity",
"Recognition",
"problem",
"using",
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"Random",
"Fields",
"(CRF",
")",
"and",
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"Long",
"Short-Term",
"Memory",
"with",
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"(LSTM-CRF",
").",
"Both",
"CRF",
"and",
"LSTM-CRF",
"outperform",
"human",
"and",
"baselines",
"in",
"both",
"exact-match",
"accuracy",
"and",
"F1",
"scores.",
"The",
"dataset",
"and",
"pre-trained",
"embeddings",
"are",
"available",
"at",
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] |
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"results",
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"first",
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"Spotting",
"Challenge",
"2019",
"by",
"evaluating",
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"temporal",
"pattern",
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"on",
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"temporal",
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"local",
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"classification",
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"global",
"fusion.",
"The",
"performance",
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"an",
"active",
"research",
"area.",
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"one",
"of",
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"machine",
"learning",
"models,",
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"been",
"utilized",
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"solve",
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"problems",
"including",
"issues",
"in",
"this",
"domain.",
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"this",
"work,",
"a",
"study",
"of",
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"its",
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"model",
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"window",
"sizes",
"and",
"electrode",
"orders.",
"Our",
"investigation",
"was",
"conducted",
"in",
"subject-independent",
"fashion.",
"Results",
"have",
"shown",
"that",
"temporal",
"information",
"in",
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"window",
"sizes",
"significantly",
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"performance",
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"leave-one-subject-out",
"cross",
"validation.",
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"information",
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"order",
"has",
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"effect",
"on",
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"SVM",
"classifier",
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"knowledge",
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"same",
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"these",
"empirical",
"results.",
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"by",
"different",
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"features",
"in",
"the",
"elicitation",
"process."
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"association",
"framework",
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"able",
"tohandle",
"missing",
"elements",
"in",
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"sequences.",
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"general",
"scope",
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"the",
"workis",
"the",
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"of",
"object-word",
"mappings",
"as",
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"in",
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"concepts",
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"directions.",
"This",
"scenario",
"has",
"beenlong",
"interested",
"in",
"Artificial",
"Intelligence,",
"Psychology,",
"and",
"Neuroscience.",
"Inthis",
"work,",
"we",
"extend",
"a",
"recent",
"approach",
"for",
"multimodal",
"sequences",
"(visual",
"andaudio)",
"to",
"also",
"cope",
"with",
"missing",
"elements",
"in",
"one",
"or",
"both",
"modalities.",
"Our",
"methoduses",
"two",
"parallel",
"Long",
"Short-Term",
"Memories",
"(LSTM",
"s)",
"with",
"a",
"learning",
"rule",
"basedon",
"EM-algorithm.",
"It",
"aligns",
"both",
"LSTM",
"outputs",
"via",
"Dynamic",
"Time",
"Warping",
"(DTW).",
"Wepropose",
"to",
"include",
"an",
"extra",
"step",
"for",
"the",
"combination",
"with",
"the",
"max",
"operation",
"forexploiting",
"the",
"common",
"elements",
"between",
"both",
"sequences.",
"The",
"motivation",
"behind",
"isthat",
"the",
"combination",
"acts",
"as",
"a",
"condition",
"selector",
"for",
"choosing",
"the",
"bestrepresentation",
"from",
"both",
"LSTM",
"s.",
"We",
"evaluated",
"the",
"proposed",
"extension",
"in",
"thefollowing",
"scenarios:",
"missing",
"elements",
"in",
"one",
"modality",
"(visual",
"or",
"audio)",
"andmissing",
"elements",
"in",
"both",
"modalities",
"(visual",
"and",
"sound).",
"The",
"performance",
"of",
"ourextension",
"reaches",
"better",
"results",
"than",
"the",
"original",
"model",
"and",
"similar",
"results",
"toindividual",
"LSTM",
"trained",
"in",
"each",
"modality."
] |
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[
"Multi-View",
"Stereo",
"(MVS)",
"is",
"a",
"core",
"task",
"in",
"3D",
"computer",
"vision.",
"With",
"the",
"surge",
"of",
"novel",
"deep",
"learning",
"methods,",
"learned",
"MVS",
"has",
"surpassed",
"the",
"accuracy",
"of",
"classical",
"approaches,",
"but",
"still",
"relies",
"on",
"building",
"a",
"memory",
"intensive",
"dense",
"cost",
"volume.",
"Novel",
"View",
"Synthesis",
"(NVS)",
"is",
"a",
"parallel",
"line",
"of",
"research",
"and",
"has",
"recently",
"seen",
"an",
"increase",
"in",
"popularity",
"with",
"Neural",
"Radiance",
"Field",
"(NeRF",
")",
"models,",
"which",
"optimize",
"a",
"per",
"scene",
"radiance",
"field.",
"However,",
"NeRF",
"methods",
"do",
"not",
"generalize",
"to",
"novel",
"scenes",
"and",
"are",
"slow",
"to",
"train",
"and",
"test.",
"We",
"propose",
"to",
"bridge",
"the",
"gap",
"between",
"these",
"two",
"methodologies",
"with",
"a",
"novel",
"network",
"that",
"can",
"recover",
"3D",
"scene",
"geometry",
"as",
"a",
"distance",
"function,",
"together",
"with",
"high-resolution",
"color",
"images.",
"Our",
"method",
"uses",
"only",
"a",
"sparse",
"set",
"of",
"images",
"as",
"input",
"and",
"can",
"generalize",
"well",
"to",
"novel",
"scenes.",
"Additionally,",
"we",
"propose",
"a",
"coarse-to-fine",
"sphere",
"tracing",
"approach",
"in",
"order",
"to",
"significantly",
"increase",
"speed.",
"We",
"show",
"on",
"various",
"datasets",
"that",
"our",
"method",
"reaches",
"comparable",
"accuracy",
"to",
"per-scene",
"optimized",
"methods",
"while",
"being",
"able",
"to",
"generalize",
"and",
"running",
"significantly",
"faster."
] |
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[
"Objective:",
"To",
"evaluate",
"the",
"impact",
"on",
"Electroencephalography",
"(EEG",
")",
"classification",
"of",
"different",
"kinds",
"of",
"attention",
"mechanisms",
"in",
"Deep",
"Learning",
"(DL)",
"models.",
"Methods:",
"We",
"compared",
"three",
"attention-enhanced",
"DL",
"models,",
"the",
"brand-new",
"InstaGATs,",
"an",
"LSTM",
"with",
"attention",
"and",
"a",
"CNN",
"with",
"attention.",
"We",
"used",
"these",
"models",
"to",
"classify",
"normal",
"and",
"abnormal",
"(i.e.,",
"artifactual",
"or",
"pathological)",
"EEG",
"patterns.",
"Results:",
"We",
"achieved",
"the",
"state",
"of",
"the",
"art",
"in",
"all",
"classification",
"problems,",
"regardless",
"the",
"large",
"variability",
"of",
"the",
"datasets",
"and",
"the",
"simple",
"architecture",
"of",
"the",
"attention-enhanced",
"models.",
"We",
"could",
"also",
"prove",
"that,",
"depending",
"on",
"how",
"the",
"attention",
"mechanism",
"is",
"applied",
"and",
"where",
"the",
"attention",
"layer",
"is",
"located",
"in",
"the",
"model,",
"we",
"can",
"alternatively",
"leverage",
"the",
"information",
"contained",
"in",
"the",
"time,",
"frequency",
"or",
"space",
"domain",
"of",
"the",
"dataset.",
"Conclusions:",
"with",
"this",
"work,",
"we",
"shed",
"light",
"over",
"the",
"role",
"of",
"different",
"attention",
"mechanisms",
"in",
"the",
"classification",
"of",
"normal",
"and",
"abnormal",
"EEG",
"patterns.",
"Moreover,",
"we",
"discussed",
"how",
"they",
"can",
"exploit",
"the",
"intrinsic",
"relationships",
"in",
"the",
"temporal,",
"frequency",
"and",
"spatial",
"domains",
"of",
"our",
"brain",
"activity.",
"Significance:",
"Attention",
"represents",
"a",
"promising",
"strategy",
"to",
"evaluate",
"the",
"quality",
"of",
"the",
"EEG",
"information,",
"and",
"its",
"relevance,",
"in",
"different",
"real-world",
"scenarios.",
"Moreover,",
"it",
"can",
"make",
"it",
"easier",
"to",
"parallelize",
"the",
"computation",
"and,",
"thus,",
"to",
"speed",
"up",
"the",
"analysis",
"of",
"big",
"electrophysiological",
"(e.g.,",
"EEG",
")",
"datasets."
] |
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[
"In",
"this",
"paper,",
"a",
"novel",
"racing",
"environment",
"for",
"OpenAI",
"Gym",
"is",
"introduced.",
"This",
"environment",
"operates",
"with",
"continuous",
"action-",
"and",
"state-spaces",
"and",
"requires",
"agents",
"to",
"learn",
"to",
"control",
"the",
"acceleration",
"and",
"steering",
"of",
"a",
"car",
"while",
"navigating",
"a",
"randomly",
"generated",
"racetrack.",
"Different",
"versions",
"of",
"two",
"actor-critic",
"learning",
"algorithms",
"are",
"tested",
"on",
"this",
"environment:",
"Sampled",
"Policy",
"Gradient",
"(SPG)",
"and",
"Proximal",
"Policy",
"Optimization",
"(PPO",
").",
"An",
"extension",
"of",
"SPG",
"is",
"introduced",
"that",
"aims",
"to",
"improve",
"learning",
"performance",
"by",
"weighting",
"action",
"samples",
"during",
"the",
"policy",
"update",
"step.",
"The",
"effect",
"of",
"using",
"experience",
"replay",
"(ER)",
"is",
"also",
"investigated.",
"To",
"this",
"end,",
"a",
"modification",
"to",
"PPO",
"is",
"introduced",
"that",
"allows",
"for",
"training",
"using",
"old",
"action",
"samples",
"by",
"optimizing",
"the",
"actor",
"in",
"log",
"space.",
"Finally,",
"a",
"new",
"technique",
"for",
"performing",
"ER",
"is",
"tested",
"that",
"aims",
"to",
"improve",
"learning",
"speed",
"without",
"sacrificing",
"performance",
"by",
"splitting",
"the",
"training",
"into",
"two",
"parts,",
"whereby",
"networks",
"are",
"first",
"trained",
"using",
"state",
"transitions",
"from",
"the",
"replay",
"buffer,",
"and",
"then",
"using",
"only",
"recent",
"experiences.",
"The",
"results",
"indicate",
"that",
"experience",
"replay",
"is",
"not",
"beneficial",
"to",
"PPO",
"in",
"continuous",
"action",
"spaces.",
"The",
"training",
"of",
"SPG",
"seems",
"to",
"be",
"more",
"stable",
"when",
"actions",
"are",
"weighted.",
"All",
"versions",
"of",
"SPG",
"outperform",
"PPO",
"when",
"ER",
"is",
"used.",
"The",
"ER",
"trick",
"is",
"effective",
"at",
"improving",
"training",
"speed",
"on",
"a",
"computationally",
"less",
"intensive",
"version",
"of",
"SPG."
] |
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[
"Many",
"real-world",
"applications",
"require",
"aligning",
"two",
"temporal",
"sequences,",
"including",
"bioinformatics,",
"handwriting",
"recognition,",
"activity",
"recognition,",
"and",
"human-robot",
"coordination.",
"Dynamic",
"Time",
"Warping",
"(DTW",
")",
"is",
"a",
"popular",
"alignment",
"method,",
"but",
"can",
"fail",
"on",
"high-dimensional",
"real-world",
"data",
"where",
"the",
"dimensions",
"of",
"aligned",
"sequences",
"are",
"often",
"unequal.",
"In",
"this",
"paper,",
"we",
"show",
"that",
"exploiting",
"the",
"multiscale",
"manifold",
"latent",
"structure",
"of",
"real-world",
"data",
"can",
"yield",
"improved",
"alignment.",
"We",
"introduce",
"a",
"novel",
"framework",
"called",
"Warping",
"on",
"Wavelets",
"(WOW)",
"that",
"integrates",
"DTW",
"with",
"a",
"a",
"multi-scale",
"manifold",
"learning",
"framework",
"called",
"Diffusion",
"Wavelets.",
"We",
"present",
"a",
"theoretical",
"analysis",
"of",
"the",
"WOW",
"family",
"of",
"algorithms",
"and",
"show",
"that",
"it",
"outperforms",
"previous",
"state",
"of",
"the",
"art",
"methods,",
"such",
"as",
"canonical",
"time",
"warping",
"(CTW)",
"and",
"manifold",
"warping,",
"on",
"several",
"real-world",
"datasets."
] |
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6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
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6,
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6,
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6,
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6
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[
"Most",
"image",
"segmentation",
"algorithms",
"are",
"trained",
"on",
"binary",
"masks",
"formulated",
"as",
"a",
"classification",
"task",
"per",
"pixel.",
"However,",
"in",
"applications",
"such",
"as",
"medical",
"imaging,",
"this",
"black-and-white",
"approach",
"is",
"too",
"constraining",
"because",
"the",
"contrast",
"between",
"two",
"tissues",
"is",
"often",
"ill-defined,",
"i.e.,",
"the",
"voxels",
"located",
"on",
"objects'",
"edges",
"contain",
"a",
"mixture",
"of",
"tissues.",
"Consequently,",
"assigning",
"a",
"single",
"hard",
"label",
"can",
"result",
"in",
"a",
"detrimental",
"approximation.",
"Instead,",
"a",
"soft",
"prediction",
"containing",
"non-binary",
"values",
"would",
"overcome",
"that",
"limitation.",
"We",
"introduce",
"SoftSeg,",
"a",
"deep",
"learning",
"training",
"approach",
"that",
"takes",
"advantage",
"of",
"soft",
"ground",
"truth",
"labels,",
"and",
"is",
"not",
"bound",
"to",
"binary",
"predictions.",
"SoftSeg",
"aims",
"at",
"solving",
"a",
"regression",
"instead",
"of",
"a",
"classification",
"problem.",
"This",
"is",
"achieved",
"by",
"using",
"(i)",
"no",
"binarization",
"after",
"preprocessing",
"and",
"data",
"augmentation,",
"(ii)",
"a",
"normalized",
"ReLU",
"final",
"activation",
"layer",
"(instead",
"of",
"sigmoid),",
"and",
"(iii)",
"a",
"regression",
"loss",
"function",
"(instead",
"of",
"the",
"traditional",
"Dice",
"loss).",
"We",
"assess",
"the",
"impact",
"of",
"these",
"three",
"features",
"on",
"three",
"open-source",
"MRI",
"segmentation",
"datasets",
"from",
"the",
"spinal",
"cord",
"gray",
"matter,",
"the",
"multiple",
"sclerosis",
"brain",
"lesion,",
"and",
"the",
"multimodal",
"brain",
"tumor",
"segmentation",
"challenges.",
"Across",
"multiple",
"cross-validation",
"iterations,",
"SoftSeg",
"outperformed",
"the",
"conventional",
"approach,",
"leading",
"to",
"an",
"increase",
"in",
"Dice",
"score",
"of",
"2.00%",
"on",
"the",
"gray",
"matter",
"dataset",
"(p=0.001),",
"3.30%",
"for",
"the",
"MS",
"lesions,",
"and",
"6.50%",
"for",
"the",
"brain",
"tumors.",
"SoftSeg",
"produces",
"consistent",
"soft",
"predictions",
"at",
"tissues'",
"interfaces",
"and",
"shows",
"an",
"increased",
"sensitivity",
"for",
"small",
"objects.",
"The",
"richness",
"of",
"soft",
"labels",
"could",
"represent",
"the",
"inter-expert",
"variability,",
"the",
"partial",
"volume",
"effect,",
"and",
"complement",
"the",
"model",
"uncertainty",
"estimation.",
"The",
"developed",
"training",
"pipeline",
"can",
"easily",
"be",
"incorporated",
"into",
"most",
"of",
"the",
"existing",
"deep",
"learning",
"architectures.",
"It",
"is",
"already",
"implemented",
"in",
"the",
"freely-available",
"deep",
"learning",
"toolbox",
"ivadomed",
"(https://ivadomed.org)."
] |
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[
"This",
"paper",
"describes",
"an",
"evaluation",
"of",
"an",
"existing",
"technique",
"that",
"locates",
"sentences",
"containing",
"descriptions",
"of",
"a",
"query",
"word",
"or",
"phrase",
".",
"The",
"experiments",
"expand",
"on",
"previous",
"tests",
"by",
"exploring",
"the",
"effectiveness",
"of",
"the",
"system",
"when",
"searching",
"from",
"a",
"much",
"larger",
"document",
"collection",
".",
"The",
"results",
"showed",
"the",
"system",
"working",
"significantly",
"better",
"than",
"when",
"searching",
"over",
"smaller",
"collections",
".",
"The",
"improvement",
"was",
"such",
",",
"that",
"a",
"more",
"stringent",
"definition",
"of",
"what",
"constituted",
"a",
"correct",
"description",
"was",
"devised",
"to",
"better",
"measure",
"effectiveness",
".",
"The",
"results",
"also",
"pointed",
"to",
"potentially",
"new",
"forms",
"of",
"evidence",
"that",
"might",
"be",
"used",
"in",
"improving",
"the",
"location",
"process",
".",
"Keywords",
"Information",
"retrieval",
",",
"descriptive",
"phrases",
",",
"WWW",
"."
] |
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6,
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1,
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5,
5,
5,
5,
5,
5,
3,
6,
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6,
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6,
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[
"We",
"study",
"the",
"inclusion",
"of",
"past",
"conversational",
"context",
"through",
"BERT",
"language",
"models",
"into",
"a",
"CTC-based",
"Automatic",
"Speech",
"Recognition",
"(ASR)",
"system",
"via",
"N-best",
"rescoring.",
"We",
"introduce",
"a",
"data-efficient",
"strategy",
"to",
"fine-tune",
"BERT",
"on",
"transcript",
"disambiguation",
"without",
"external",
"data.",
"Our",
"results",
"show",
"word",
"error",
"rate",
"recoveries",
"up",
"to",
"37.20%",
"with",
"context-augmented",
"BERT",
"rescoring.",
"We",
"do",
"this",
"in",
"low-resource",
"data",
"domains,",
"both",
"in",
"language",
"(Norwegian),",
"tone",
"(spontaneous,",
"conversational),",
"and",
"topics",
"(parliament",
"proceedings",
"and",
"customer",
"service",
"phone",
"calls).",
"We",
"show",
"how",
"the",
"nature",
"of",
"the",
"data",
"greatly",
"affects",
"the",
"performance",
"of",
"context-augmented",
"N-best",
"rescoring."
] |
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6,
6,
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6,
6,
6,
6,
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6,
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6,
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6
] |
[
"Lithium-ion",
"batteries",
"are",
"powering",
"the",
"ongoing",
"transportation",
"electrification",
"revolution.",
"Lithium-ion",
"batteries",
"possess",
"higher",
"energy",
"density",
"and",
"favourable",
"electrochemical",
"properties",
"which",
"make",
"it",
"a",
"preferable",
"energy",
"source",
"for",
"electric",
"vehicles.",
"Precise",
"estimation",
"of",
"battery",
"parameters",
"(Charge",
"capacity,",
"voltage",
"etc)",
"is",
"vital",
"to",
"estimate",
"the",
"available",
"range",
"in",
"an",
"electric",
"vehicle.",
"Graph-based",
"estimation",
"techniques",
"enable",
"us",
"to",
"understand",
"the",
"variable",
"dependencies",
"underpinning",
"them",
"to",
"improve",
"estimates.",
"In",
"this",
"paper",
"we",
"employ",
"Graph",
"Neural",
"Networks",
"for",
"battery",
"parameter",
"estimation,",
"we",
"introduce",
"a",
"unique",
"graph",
"autoencoder",
"time",
"series",
"estimation",
"approach.",
"Variables",
"in",
"battery",
"measurements",
"are",
"known",
"to",
"have",
"an",
"underlying",
"relationship",
"with",
"each",
"other",
"in",
"a",
"certain",
"causal",
"structure.",
"Therefore,",
"we",
"include",
"ideas",
"from",
"the",
"field",
"of",
"causal",
"structure",
"learning",
"as",
"a",
"regularisation",
"to",
"our",
"learned",
"adjacency",
"matrix",
"technique.",
"We",
"use",
"graph",
"autoencoder",
"based",
"on",
"a",
"non-linear",
"version",
"of",
"NOTEARS",
"Zheng",
"et",
"al.",
"-2018",
"as",
"this",
"allowed",
"us",
"to",
"perform",
"gradient-descent",
"in",
"learning",
"the",
"structure",
"(instead",
"of",
"treating",
"it",
"as",
"a",
"combinatorial",
"optimisation",
"problem).",
"The",
"proposed",
"architecture",
"outperforms",
"the",
"state-of-the-art",
"Graph",
"Time",
"Series",
"(GTS)",
"Shang",
"et",
"al.",
"(2021a)",
"architecture",
"for",
"battery",
"parameter",
"estimation.",
"We",
"call",
"our",
"method",
"GAETS",
"(Graph",
"AutoEncoder",
"Time",
"Series",
")."
] |
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6,
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6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
1,
3,
6,
6,
6,
6,
6,
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6,
6,
7,
1,
3,
6
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[
"Object",
"Detection",
"(OD)",
"is",
"an",
"important",
"computer",
"vision",
"problem",
"for",
"industry,",
"which",
"can",
"be",
"used",
"for",
"quality",
"control",
"in",
"the",
"production",
"lines,",
"among",
"other",
"applications.",
"Recently,",
"Deep",
"Learning",
"(DL)",
"methods",
"have",
"enabled",
"practitioners",
"to",
"train",
"OD",
"models",
"performing",
"well",
"on",
"complex",
"real",
"world",
"images.",
"However,",
"the",
"adoption",
"of",
"these",
"models",
"in",
"industry",
"is",
"still",
"limited",
"by",
"the",
"difficulty",
"and",
"the",
"significant",
"cost",
"of",
"collecting",
"high",
"quality",
"training",
"datasets.",
"On",
"the",
"other",
"hand,",
"when",
"applying",
"OD",
"to",
"the",
"context",
"of",
"production",
"lines,",
"CAD",
"models",
"of",
"the",
"objects",
"to",
"be",
"detected",
"are",
"often",
"available.",
"In",
"this",
"paper,",
"we",
"introduce",
"a",
"fully",
"automated",
"method",
"that",
"uses",
"a",
"CAD",
"model",
"of",
"an",
"object",
"and",
"returns",
"a",
"fully",
"trained",
"OD",
"model",
"for",
"detecting",
"this",
"object.",
"To",
"do",
"this,",
"we",
"created",
"a",
"Blender",
"script",
"that",
"generates",
"realistic",
"labeled",
"datasets",
"of",
"images",
"containing",
"the",
"object,",
"which",
"are",
"then",
"used",
"for",
"training",
"the",
"OD",
"model.",
"The",
"method",
"is",
"validated",
"experimentally",
"on",
"two",
"practical",
"examples,",
"showing",
"that",
"this",
"approach",
"can",
"generate",
"OD",
"models",
"performing",
"well",
"on",
"real",
"images,",
"while",
"being",
"trained",
"only",
"on",
"synthetic",
"images.",
"The",
"proposed",
"method",
"has",
"potential",
"to",
"facilitate",
"the",
"adoption",
"of",
"object",
"detection",
"models",
"in",
"industry",
"as",
"it",
"is",
"easy",
"to",
"adapt",
"for",
"new",
"objects",
"and",
"highly",
"flexible.",
"Hence,",
"it",
"can",
"result",
"in",
"significant",
"costs",
"reduction,",
"gains",
"in",
"productivity",
"and",
"improved",
"products",
"quality."
] |
[
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6,
6,
6,
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[
"Humanity",
"is",
"battling",
"one",
"of",
"the",
"most",
"deleterious",
"virus",
"in",
"modern",
"history,",
"the",
"COVID-19",
"pandemic,",
"but",
"along",
"with",
"the",
"pandemic",
"there's",
"an",
"infodemic",
"permeating",
"the",
"pupil",
"and",
"society",
"with",
"misinformation",
"which",
"exacerbates",
"the",
"current",
"malady.",
"We",
"try",
"to",
"detect",
"and",
"classify",
"fake",
"news",
"on",
"online",
"media",
"to",
"detect",
"fake",
"information",
"relating",
"to",
"COVID-19",
"and",
"coronavirus.",
"The",
"dataset",
"contained",
"fake",
"posts,",
"articles",
"and",
"news",
"gathered",
"from",
"fact",
"checking",
"websites",
"like",
"politifact",
"whereas",
"real",
"tweets",
"were",
"taken",
"from",
"verified",
"twitter",
"handles.",
"We",
"incorporated",
"multiple",
"conventional",
"classification",
"techniques",
"like",
"Naive",
"Bayes,",
"KNN,",
"Gradient",
"Boost",
"and",
"Random",
"Forest",
"along",
"with",
"Deep",
"learning",
"approaches,",
"specifically",
"CNN,",
"RNN,",
"DNN",
"and",
"the",
"ensemble",
"model",
"RMDL.",
"We",
"analyzed",
"these",
"approaches",
"with",
"two",
"feature",
"extraction",
"techniques,",
"TF-IDF",
"and",
"GloVe",
"Word",
"Embeddings",
"which",
"would",
"provide",
"deeper",
"insights",
"into",
"the",
"dataset",
"containing",
"COVID-19",
"info",
"on",
"online",
"media."
] |
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[
"Neural",
"network",
"pruning",
"reduces",
"the",
"computational",
"cost",
"of",
"an",
"over-parameterized",
"network",
"to",
"improve",
"its",
"efficiency.",
"Popular",
"methods",
"vary",
"from",
"$\\ell_1$-norm",
"sparsification",
"to",
"Neural",
"Architecture",
"Search",
"(NAS).",
"In",
"this",
"work,",
"we",
"propose",
"a",
"novel",
"pruning",
"method",
"that",
"optimizes",
"the",
"final",
"accuracy",
"of",
"the",
"pruned",
"network",
"and",
"distills",
"knowledge",
"from",
"the",
"over-parameterized",
"parent",
"network's",
"inner",
"layers.",
"To",
"enable",
"this",
"approach,",
"we",
"formulate",
"the",
"network",
"pruning",
"as",
"a",
"Knapsack",
"Problem",
"which",
"optimizes",
"the",
"trade-off",
"between",
"the",
"importance",
"of",
"neurons",
"and",
"their",
"associated",
"computational",
"cost.",
"Then",
"we",
"prune",
"the",
"network",
"channels",
"while",
"maintaining",
"the",
"high-level",
"structure",
"of",
"the",
"network.",
"The",
"pruned",
"network",
"is",
"fine-tuned",
"under",
"the",
"supervision",
"of",
"the",
"parent",
"network",
"using",
"its",
"inner",
"network",
"knowledge,",
"a",
"technique",
"we",
"refer",
"to",
"as",
"the",
"Inner",
"Knowledge",
"Distillation.",
"Our",
"method",
"leads",
"to",
"state-of-the-art",
"pruning",
"results",
"on",
"ImageNet,",
"CIFAR-10",
"and",
"CIFAR-100",
"using",
"ResNet",
"backbones.",
"To",
"prune",
"complex",
"network",
"structures",
"such",
"as",
"convolutions",
"with",
"skip-links",
"and",
"depth-wise",
"convolutions,",
"we",
"propose",
"a",
"block",
"grouping",
"approach",
"to",
"cope",
"with",
"these",
"structures.",
"Through",
"this",
"we",
"produce",
"compact",
"architectures",
"with",
"the",
"same",
"FLOPs",
"as",
"EfficientNet-B0",
"and",
"MobileNetV3",
"but",
"with",
"higher",
"accuracy,",
"by",
"$1\\%$",
"and",
"$0.3\\%$",
"respectively",
"on",
"ImageNet,",
"and",
"faster",
"runtime",
"on",
"GPU."
] |
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[
"In",
"this",
"paper,",
"we",
"present",
"a",
"Linguistic",
"Informed",
"Multi-Task",
"BERT",
"(LIMIT-BERT",
")",
"for",
"learning",
"language",
"representations",
"across",
"multiple",
"linguistic",
"tasks",
"by",
"Multi-Task",
"Learning",
"(MTL).",
"LIMIT-BERT",
"includes",
"five",
"key",
"linguistic",
"syntax",
"and",
"semantics",
"tasks:",
"Part-Of-Speech",
"(POS)",
"tags,",
"constituent",
"and",
"dependency",
"syntactic",
"parsing,",
"span",
"and",
"dependency",
"semantic",
"role",
"labeling",
"(SRL).",
"Besides,",
"LIMIT-BERT",
"adopts",
"linguistics",
"mask",
"strategy:",
"Syntactic",
"and",
"Semantic",
"Phrase",
"Masking",
"which",
"mask",
"all",
"of",
"the",
"tokens",
"corresponding",
"to",
"a",
"syntactic/semantic",
"phrase.",
"Different",
"from",
"recent",
"Multi-Task",
"Deep",
"Neural",
"Networks",
"(MT-DNN)",
"(Liu",
"et",
"al.,",
"2019),",
"our",
"LIMIT-BERT",
"is",
"linguistically",
"motivated",
"and",
"learning",
"in",
"a",
"semi-supervised",
"method",
"which",
"provides",
"large",
"amounts",
"of",
"linguistic-task",
"data",
"as",
"same",
"as",
"BERT",
"learning",
"corpus.",
"As",
"a",
"result,",
"LIMIT-BERT",
"not",
"only",
"improves",
"linguistic",
"tasks",
"performance",
"but",
"also",
"benefits",
"from",
"a",
"regularization",
"effect",
"and",
"linguistic",
"information",
"that",
"leads",
"to",
"more",
"general",
"representations",
"to",
"help",
"adapt",
"to",
"new",
"tasks",
"and",
"domains.",
"LIMIT-BERT",
"obtains",
"new",
"state-of-the-art",
"or",
"competitive",
"results",
"on",
"both",
"span",
"and",
"dependency",
"semantic",
"parsing",
"on",
"Propbank",
"benchmarks",
"and",
"both",
"dependency",
"and",
"constituent",
"syntactic",
"parsing",
"on",
"Penn",
"Treebank."
] |
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[
"One",
"of",
"the",
"most",
"important",
"tasks",
"in",
"network",
"management",
"is",
"identifyingdifferent",
"types",
"of",
"traffic",
"flows.",
"As",
"a",
"result,",
"a",
"type",
"of",
"management",
"service,called",
"Network",
"Traffic",
"Classifier",
"(NTC),",
"has",
"been",
"introduced.",
"One",
"type",
"of",
"NTCsthat",
"has",
"gained",
"huge",
"attention",
"in",
"recent",
"years",
"applies",
"deep",
"learning",
"on",
"packetsin",
"order",
"to",
"classify",
"flows.",
"Internet",
"is",
"an",
"imbalanced",
"environment",
"i.e.,",
"someclasses",
"of",
"applications",
"are",
"a",
"lot",
"more",
"populated",
"than",
"others",
"e.g.,",
"HTTP.Additionally,",
"one",
"of",
"the",
"challenges",
"in",
"deep",
"learning",
"methods",
"is",
"that",
"they",
"donot",
"perform",
"well",
"in",
"imbalanced",
"environments",
"in",
"terms",
"of",
"evaluation",
"metrics",
"suchas",
"precision,",
"recall,",
"and",
"$\\mathrm{F_1}$",
"measure.",
"In",
"order",
"to",
"solve",
"thisproblem,",
"we",
"recommend",
"the",
"use",
"of",
"augmentation",
"methods",
"to",
"balance",
"the",
"dataset.In",
"this",
"paper,",
"we",
"propose",
"a",
"novel",
"data",
"augmentation",
"approach",
"based",
"on",
"the",
"useof",
"Long",
"Short",
"Term",
"Memory",
"(LSTM",
")",
"networks",
"for",
"generating",
"traffic",
"flow",
"patternsand",
"Kernel",
"Density",
"Estimation",
"(KDE)",
"for",
"replicating",
"the",
"numerical",
"features",
"ofeach",
"class.",
"First,",
"we",
"use",
"the",
"LSTM",
"network",
"in",
"order",
"to",
"learn",
"and",
"generate",
"thesequence",
"of",
"packets",
"in",
"a",
"flow",
"for",
"classes",
"with",
"less",
"population.",
"Then,",
"wecomplete",
"the",
"features",
"of",
"the",
"sequence",
"with",
"generating",
"random",
"values",
"based",
"onthe",
"distribution",
"of",
"a",
"certain",
"feature,",
"which",
"will",
"be",
"estimated",
"using",
"KDE.Finally,",
"we",
"compare",
"the",
"training",
"of",
"a",
"Convolutional",
"Recurrent",
"Neural",
"Network(CRNN)",
"in",
"large-scale",
"imbalanced,",
"sampled,",
"and",
"augmented",
"datasets.",
"Thecontribution",
"of",
"our",
"augmentation",
"scheme",
"is",
"then",
"evaluated",
"on",
"all",
"of",
"thedatasets",
"through",
"measurements",
"of",
"precision,",
"recall,",
"and",
"F1",
"measure",
"for",
"everyclass",
"of",
"application.",
"The",
"results",
"demonstrate",
"that",
"our",
"scheme",
"is",
"well",
"suitedfor",
"network",
"traffic",
"flow",
"datasets",
"and",
"improves",
"the",
"performance",
"of",
"deep",
"learningalgorithms",
"when",
"it",
"comes",
"to",
"above-mentioned",
"metrics."
] |
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[
"In",
"this",
"paper,",
"we",
"explore",
"the",
"role",
"of",
"Instance",
"Normalization",
"in",
"low-level",
"vision",
"tasks.",
"Specifically,",
"we",
"present",
"a",
"novel",
"block:",
"Half",
"Instance",
"Normalization",
"Block",
"(HIN",
"Block),",
"to",
"boost",
"the",
"performance",
"of",
"image",
"restoration",
"networks.",
"Based",
"on",
"HIN",
"Block,",
"we",
"design",
"a",
"simple",
"and",
"powerful",
"multi-stage",
"network",
"named",
"HINet,",
"which",
"consists",
"of",
"two",
"subnetworks.",
"With",
"the",
"help",
"of",
"HIN",
"Block,",
"HINet",
"surpasses",
"the",
"state-of-the-art",
"(SOTA)",
"on",
"various",
"image",
"restoration",
"tasks.",
"For",
"image",
"denoising,",
"we",
"exceed",
"it",
"0.11dB",
"and",
"0.28",
"dB",
"in",
"PSNR",
"on",
"SIDD",
"dataset,",
"with",
"only",
"7.50%",
"and",
"30%",
"of",
"its",
"multiplier-accumulator",
"operations",
"(MACs),",
"6.8",
"times",
"and",
"2.9",
"times",
"speedup",
"respectively.",
"For",
"image",
"deblurring,",
"we",
"get",
"comparable",
"performance",
"with",
"22.50%",
"of",
"its",
"MACs",
"and",
"3.3",
"times",
"speedup",
"on",
"REDS",
"and",
"GoPro",
"datasets.",
"For",
"image",
"deraining,",
"we",
"exceed",
"it",
"by",
"0.3",
"dB",
"in",
"PSNR",
"on",
"the",
"average",
"result",
"of",
"multiple",
"datasets",
"with",
"1.4",
"times",
"speedup.",
"With",
"HINet,",
"we",
"won",
"1st",
"place",
"on",
"the",
"NTIRE",
"2021",
"Image",
"Deblurring",
"Challenge",
"-",
"Track2.",
"JPEG",
"Artifacts,",
"with",
"a",
"PSNR",
"of",
"29.70.",
"The",
"code",
"is",
"available",
"at",
"https://github.com/megvii-model/HINet."
] |
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[
"The",
"performances",
"of",
"Sign",
"Language",
"Recognition",
"(SLR",
")",
"systems",
"have",
"improved",
"considerably",
"in",
"recent",
"years.",
"However,",
"several",
"open",
"challenges",
"still",
"need",
"to",
"be",
"solved",
"to",
"allow",
"SLR",
"to",
"be",
"useful",
"in",
"practice.",
"The",
"research",
"in",
"the",
"field",
"is",
"in",
"its",
"infancy",
"in",
"regards",
"to",
"the",
"robustness",
"of",
"the",
"models",
"to",
"a",
"large",
"diversity",
"of",
"signs",
"and",
"signers,",
"and",
"to",
"fairness",
"of",
"the",
"models",
"to",
"performers",
"from",
"different",
"demographics.",
"This",
"work",
"summarises",
"the",
"ChaLearn",
"LAP",
"Large",
"Scale",
"Signer",
"Independent",
"Isolated",
"SLR",
"Challenge,",
"organised",
"at",
"CVPR",
"2021",
"with",
"the",
"goal",
"of",
"overcoming",
"some",
"of",
"the",
"aforementioned",
"challenges.",
"We",
"analyse",
"and",
"discuss",
"the",
"challenge",
"design,",
"top",
"winning",
"solutions",
"and",
"suggestions",
"for",
"future",
"research.",
"The",
"challenge",
"attracted",
"132",
"participants",
"in",
"the",
"RGB",
"track",
"and",
"59",
"in",
"the",
"RGB+Depth",
"track,",
"receiving",
"more",
"than",
"1.5K",
"submissions",
"in",
"total.",
"Participants",
"were",
"evaluated",
"using",
"a",
"new",
"large-scale",
"multi-modal",
"Turkish",
"Sign",
"Language",
"(AUTSL)",
"dataset,",
"consisting",
"of",
"226",
"sign",
"labels",
"and",
"36,302",
"isolated",
"sign",
"video",
"samples",
"performed",
"by",
"43",
"different",
"signers.",
"Winning",
"teams",
"achieved",
"more",
"than",
"96%",
"recognition",
"rate,",
"and",
"their",
"approaches",
"benefited",
"from",
"pose/hand/face",
"estimation,",
"transfer",
"learning,",
"external",
"data,",
"fusion/ensemble",
"of",
"modalities",
"and",
"different",
"strategies",
"to",
"model",
"spatio-temporal",
"information.",
"However,",
"methods",
"still",
"fail",
"to",
"distinguish",
"among",
"very",
"similar",
"signs,",
"in",
"particular",
"those",
"sharing",
"similar",
"hand",
"trajectories."
] |
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[
"In",
"this",
"paper,",
"we",
"propose",
"a",
"novel",
"method",
"and",
"a",
"practical",
"approach",
"to",
"predicting",
"early",
"onsets",
"of",
"sleep",
"syndromes,",
"including",
"restless",
"leg",
"syndrome,",
"insomnia,",
"based",
"on",
"an",
"algorithm",
"that",
"is",
"comprised",
"of",
"two",
"modules.",
"A",
"Fast",
"Fourier",
"Transform",
"is",
"applied",
"to",
"30",
"seconds",
"long",
"epochs",
"of",
"EEG",
"recordings",
"to",
"provide",
"localized",
"time-frequency",
"information,",
"and",
"a",
"deep",
"convolutional",
"LSTM",
"neural",
"network",
"is",
"trained",
"for",
"sleep",
"stage",
"classification.",
"Automating",
"sleep",
"stages",
"detection",
"from",
"EEG",
"data",
"offers",
"great",
"potential",
"to",
"tackling",
"sleep",
"irregularities",
"on",
"a",
"daily",
"basis.",
"Thereby,",
"a",
"novel",
"approach",
"for",
"sleep",
"stage",
"classification",
"is",
"proposed",
"which",
"combines",
"the",
"best",
"of",
"signal",
"processing",
"and",
"statistics.",
"In",
"this",
"study,",
"we",
"used",
"the",
"PhysioNet",
"Sleep",
"European",
"Data",
"Format",
"(EDF)",
"Database.",
"The",
"code",
"evaluation",
"showed",
"impressive",
"results,",
"reaching",
"an",
"accuracy",
"of",
"86.43,",
"precision",
"of",
"77.76,",
"recall",
"of",
"93,32,",
"F1-score",
"of",
"89.12",
"with",
"the",
"final",
"mean",
"FALSE",
"error",
"loss",
"of",
"0.09."
] |
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[
"Phrasal",
"Verbs",
"are",
"an",
"important",
"feature",
"of",
"the",
"English",
"language",
".",
"Properly",
"identifying",
"them",
"provides",
"the",
"basis",
"for",
"an",
"English",
"parser",
"to",
"decode",
"the",
"related",
"structures",
".",
"Phrasal",
"verbs",
"have",
"been",
"a",
"challenge",
"to",
"Natural",
"Language",
"Processing",
"-LRB-",
"NLP",
"-RRB-",
"because",
"they",
"sit",
"at",
"the",
"borderline",
"between",
"lexicon",
"and",
"syntax",
".",
"Traditional",
"NLP",
"frameworks",
"that",
"separate",
"the",
"lexicon",
"module",
"from",
"the",
"parser",
"make",
"it",
"difficult",
"to",
"handle",
"this",
"problem",
"properly",
".",
"This",
"paper",
"presents",
"a",
"finite",
"state",
"approach",
"that",
"integrates",
"a",
"phrasal",
"verb",
"expert",
"lexicon",
"between",
"shallow",
"parsing",
"and",
"deep",
"parsing",
"to",
"handle",
"morpho-syntactic",
"interaction",
".",
"With",
"precision\\/recall",
"combined",
"performance",
"benchmarked",
"consistently",
"at",
"95.8",
"%",
"-97.5",
"%",
",",
"the",
"Phrasal",
"Verb",
"identification",
"problem",
"has",
"basically",
"been",
"solved",
"with",
"the",
"presented",
"method",
"."
] |
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[
"This",
"paper",
"discusses",
"a",
"number",
"of",
"implications",
"of",
"using",
"either",
"a",
"conceptual",
"approach",
"or",
"a",
"lexico-semantic",
"approach",
"to",
"terminology",
"structuring",
",",
"especially",
"for",
"interpreting",
"data",
"supplied",
"by",
"corpora",
"for",
"the",
"purpose",
"of",
"building",
"specialized",
"dictionaries",
".",
"A",
"simple",
"example",
",",
"i.e.",
",",
"program",
",",
"will",
"serve",
"as",
"a",
"basis",
"for",
"showing",
"how",
"relationships",
"between",
"terms",
"are",
"captured",
"in",
"both",
"approaches",
".",
"My",
"aim",
"is",
"to",
"demonstrate",
"that",
"truly",
"conceptual",
"approaches",
"do",
"not",
"allow",
"a",
"flexible",
"integration",
"of",
"terms",
"and",
"relationships",
"between",
"terms",
"and",
"that",
"lexico-semantic",
"approaches",
"are",
"more",
"compatible",
"with",
"data",
"gathered",
"from",
"corpora",
".",
"I",
"will",
"also",
"discuss",
"some",
"of",
"the",
"implications",
"these",
"approaches",
"have",
"for",
"computational",
"terminology",
"and",
"other",
"corpus-based",
"terminological",
"endeavors",
"."
] |
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"This",
"paper",
"describes",
"the",
"system",
"submitted",
"to",
"SemEval-2017",
"Task",
"4-A",
"Sentiment",
"Analysis",
"in",
"Twitter",
"developed",
"by",
"the",
"UCSC-NLP",
"team.",
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"studied",
"how",
"relationships",
"between",
"sense",
"n-grams",
"and",
"sentiment",
"polarities",
"can",
"contribute",
"to",
"this",
"task,",
"i.e.",
"co-occurrences",
"of",
"WordNet",
"senses",
"in",
"the",
"tweet,",
"and",
"the",
"polarity.",
"Furthermore,",
"we",
"evaluated",
"the",
"effect",
"of",
"discarding",
"a",
"large",
"set",
"of",
"features",
"based",
"on",
"char-grams",
"reported",
"in",
"preceding",
"works.",
"Based",
"on",
"these",
"elements,",
"we",
"developed",
"a",
"SVM",
"system,",
"which",
"exploring",
"SentiWordNet",
"as",
"a",
"polarity",
"lexicon.",
"It",
"achieves",
"an",
"$F_1=0.624$of",
"average.",
"Among",
"39",
"submissions",
"to",
"this",
"task,",
"we",
"ranked",
"10th."
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"Traditional",
"Optical",
"Character",
"Recognition",
"(OCR)",
"systems",
"that",
"generate",
"text",
"of",
"highly",
"inflectional",
"Indic",
"languages",
"like",
"Hindi",
"tend",
"to",
"suffer",
"from",
"poor",
"accuracy",
"due",
"to",
"a",
"wide",
"alphabet",
"set,",
"compound",
"characters",
"and",
"difficulty",
"in",
"segmenting",
"characters",
"in",
"a",
"word.",
"Automatic",
"spelling",
"error",
"detection",
"and",
"context-sensitive",
"error",
"correction",
"can",
"be",
"used",
"to",
"improve",
"accuracy",
"by",
"post-processing",
"the",
"text",
"generated",
"by",
"these",
"OCR",
"systems.",
"A",
"majority",
"of",
"previously",
"developed",
"language",
"models",
"for",
"error",
"correction",
"of",
"Hindi",
"spelling",
"have",
"been",
"context-free.",
"In",
"this",
"paper,",
"we",
"present",
"Vartani",
"Spellcheck",
"-",
"a",
"context-sensitive",
"approach",
"for",
"spelling",
"correction",
"of",
"Hindi",
"text",
"using",
"a",
"state-of-the-art",
"transformer",
"-",
"BERT",
"in",
"conjunction",
"with",
"the",
"Levenshtein",
"distance",
"algorithm,",
"popularly",
"known",
"as",
"Edit",
"Distance.",
"We",
"use",
"a",
"lookup",
"dictionary",
"and",
"context-based",
"named",
"entity",
"recognition",
"(NER)",
"for",
"detection",
"of",
"possible",
"spelling",
"errors",
"in",
"the",
"text.",
"Our",
"proposed",
"technique",
"has",
"been",
"tested",
"on",
"a",
"large",
"corpus",
"of",
"text",
"generated",
"by",
"the",
"widely",
"used",
"Tesseract",
"OCR",
"on",
"the",
"Hindi",
"epic",
"Ramayana.",
"With",
"an",
"accuracy",
"of",
"81%,",
"the",
"results",
"show",
"a",
"significant",
"improvement",
"over",
"some",
"of",
"the",
"previously",
"established",
"context-sensitive",
"error",
"correction",
"mechanisms",
"for",
"Hindi.",
"We",
"also",
"explain",
"how",
"Vartani",
"Spellcheck",
"may",
"be",
"used",
"for",
"on-the-fly",
"autocorrect",
"suggestion",
"during",
"continuous",
"typing",
"in",
"a",
"text",
"editor",
"environment."
] |
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[
"This",
"paper",
"describes",
"the",
"neural",
"machine",
"translation",
"systems",
"developed",
"at",
"the",
"RWTH",
"Aachen",
"University",
"for",
"the",
"German-English,",
"Chinese-English",
"and",
"Kazakh-English",
"news",
"translation",
"tasks",
"of",
"the",
"Fourth",
"Conference",
"on",
"Machine",
"Translation",
"(WMT19).",
"For",
"all",
"tasks,",
"the",
"final",
"submitted",
"system",
"is",
"based",
"on",
"the",
"Transformer",
"architecture.",
"We",
"focus",
"on",
"improving",
"data",
"filtering",
"and",
"fine-tuning",
"as",
"well",
"as",
"systematically",
"evaluating",
"interesting",
"approaches",
"like",
"unigram",
"language",
"model",
"segmentation",
"and",
"transfer",
"learning.",
"For",
"the",
"De-En",
"task,",
"none",
"of",
"the",
"tested",
"methods",
"gave",
"a",
"significant",
"improvement",
"over",
"last",
"years",
"winning",
"system",
"and",
"we",
"end",
"up",
"with",
"the",
"same",
"performance,",
"resulting",
"in",
"39.6{\\%}",
"BLEU",
"on",
"newstest2019.",
"In",
"the",
"Zh-En",
"task,",
"we",
"show",
"1.3{\\%}",
"BLEU",
"improvement",
"over",
"our",
"last",
"year{'}s",
"submission,",
"which",
"we",
"mostly",
"attribute",
"to",
"the",
"splitting",
"of",
"long",
"sentences",
"during",
"translation.",
"We",
"further",
"report",
"results",
"on",
"the",
"Kazakh-English",
"task",
"where",
"we",
"gain",
"improvements",
"of",
"11.1{\\%}",
"BLEU",
"over",
"our",
"baseline",
"system.",
"On",
"the",
"same",
"task",
"we",
"present",
"a",
"recent",
"transfer",
"learning",
"approach,",
"which",
"uses",
"half",
"of",
"the",
"free",
"parameters",
"of",
"our",
"submission",
"system",
"and",
"performs",
"on",
"par",
"with",
"it."
] |
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[
"In",
"this",
"paper,",
"we",
"show",
"our",
"solution",
"to",
"the",
"Google",
"Landmark",
"Recognition",
"2021",
"Competition.",
"Firstly,",
"embeddings",
"of",
"images",
"are",
"extracted",
"via",
"various",
"architectures",
"(i.e.",
"CNN-,",
"Transformer-",
"and",
"hybrid-based),",
"which",
"are",
"optimized",
"by",
"ArcFace",
"loss.",
"Then",
"we",
"apply",
"an",
"efficient",
"pipeline",
"to",
"re-rank",
"predictions",
"by",
"adjusting",
"the",
"retrieval",
"score",
"with",
"classification",
"logits",
"and",
"non-landmark",
"distractors.",
"Finally,",
"the",
"ensembled",
"model",
"scores",
"0.489",
"on",
"the",
"private",
"leaderboard,",
"achieving",
"the",
"3rd",
"place",
"in",
"the",
"2021",
"edition",
"of",
"the",
"Google",
"Landmark",
"Recognition",
"Competition."
] |
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[
"In",
"this",
"paper",
"we",
"present",
"our",
"submission",
"for",
"the",
"EACL",
"2021",
"SRW;",
"a",
"methodology",
"that",
"aims",
"at",
"bridging",
"the",
"gap",
"between",
"high",
"and",
"low-resource",
"languages",
"in",
"the",
"context",
"of",
"Open",
"Information",
"Extraction,",
"showcasing",
"it",
"on",
"the",
"Greek",
"language.",
"The",
"goals",
"of",
"this",
"paper",
"are",
"twofold:",
"First,",
"we",
"build",
"Neural",
"Machine",
"Translation",
"(NMT)",
"models",
"for",
"English-to-Greek",
"and",
"Greek-to-English",
"based",
"on",
"the",
"Transformer",
"architecture.",
"Second,",
"we",
"leverage",
"these",
"NMT",
"models",
"to",
"produce",
"English",
"translations",
"of",
"Greek",
"text",
"as",
"input",
"for",
"our",
"NLP",
"pipeline,",
"to",
"which",
"we",
"apply",
"a",
"series",
"of",
"pre-processing",
"and",
"triple",
"extraction",
"tasks.",
"Finally,",
"we",
"back-translate",
"the",
"extracted",
"triples",
"to",
"Greek.",
"We",
"conduct",
"an",
"evaluation",
"of",
"both",
"our",
"NMT",
"and",
"OIE",
"methods",
"on",
"benchmark",
"datasets",
"and",
"demonstrate",
"that",
"our",
"approach",
"outperforms",
"the",
"current",
"state-of-the-art",
"for",
"the",
"Greek",
"natural",
"language."
] |
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[
"Learning",
"in",
"real-time",
"applications,",
"e.g.,",
"online",
"approximation",
"of",
"the",
"inverse",
"dynamics",
"model",
"for",
"model-based",
"robot",
"control,",
"requires",
"fast",
"online",
"regression",
"techniques.",
"Inspired",
"by",
"local",
"learning,",
"we",
"propose",
"a",
"method",
"to",
"speed",
"up",
"standard",
"Gaussian",
"Process",
"regression",
"(GPR",
")",
"with",
"local",
"GP",
"models",
"(LGP).",
"The",
"training",
"data",
"is",
"partitioned",
"in",
"local",
"regions,",
"for",
"each",
"an",
"individual",
"GP",
"model",
"is",
"trained.",
"The",
"prediction",
"for",
"a",
"query",
"point",
"is",
"performed",
"by",
"weighted",
"estimation",
"using",
"nearby",
"local",
"models.",
"Unlike",
"other",
"GP",
"approximations,",
"such",
"as",
"mixtures",
"of",
"experts,",
"we",
"use",
"a",
"distance",
"based",
"measure",
"for",
"partitioning",
"of",
"the",
"data",
"and",
"weighted",
"prediction.",
"The",
"proposed",
"method",
"achieves",
"online",
"learning",
"and",
"prediction",
"in",
"real-time.",
"Comparisons",
"with",
"other",
"nonparametric",
"regression",
"methods",
"show",
"that",
"LGP",
"has",
"higher",
"accuracy",
"than",
"LWPR",
"and",
"close",
"to",
"the",
"performance",
"of",
"standard",
"GPR",
"and",
"nu-SVR."
] |
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[
"Spoken",
"Language",
"Understanding",
"(SLU)",
"converts",
"hypotheses",
"from",
"automatic",
"speech",
"recognizer",
"(ASR)",
"into",
"structured",
"semantic",
"representations.",
"ASR",
"recognition",
"errors",
"can",
"severely",
"degenerate",
"the",
"performance",
"of",
"the",
"subsequent",
"SLU",
"module.",
"To",
"address",
"this",
"issue,",
"word",
"confusion",
"networks",
"(WCNs)",
"have",
"been",
"used",
"to",
"encode",
"the",
"input",
"for",
"SLU,",
"which",
"contain",
"richer",
"information",
"than",
"1-best",
"or",
"n-best",
"hypotheses",
"list.",
"To",
"further",
"eliminate",
"ambiguity,",
"the",
"last",
"system",
"act",
"of",
"dialogue",
"context",
"is",
"also",
"utilized",
"as",
"additional",
"input.",
"In",
"this",
"paper,",
"a",
"novel",
"BERT",
"based",
"SLU",
"model",
"(WCN-BERT",
"SLU)",
"is",
"proposed",
"to",
"encode",
"WCNs",
"and",
"the",
"dialogue",
"context",
"jointly.",
"It",
"can",
"integrate",
"both",
"structural",
"information",
"and",
"ASR",
"posterior",
"probabilities",
"of",
"WCNs",
"in",
"the",
"BERT",
"architecture.",
"Experiments",
"on",
"DSTC2,",
"a",
"benchmark",
"of",
"SLU,",
"show",
"that",
"the",
"proposed",
"method",
"is",
"effective",
"and",
"can",
"outperform",
"previous",
"state-of-the-art",
"models",
"significantly."
] |
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[
"Multi-output",
"Gaussian",
"processes",
"(MOGPs)",
"are",
"an",
"extension",
"of",
"Gaussian",
"Processes",
"(GPs)",
"for",
"predicting",
"multiple",
"output",
"variables",
"(also",
"called",
"channels,",
"tasks)",
"simultaneously.",
"In",
"this",
"paper",
"we",
"use",
"the",
"convolution",
"theorem",
"to",
"design",
"a",
"new",
"kernel",
"for",
"MOGPs,",
"by",
"modeling",
"cross",
"channel",
"dependencies",
"through",
"cross",
"convolution",
"of",
"time",
"and",
"phase",
"delayed",
"components",
"in",
"the",
"spectral",
"domain.",
"The",
"resulting",
"kernel",
"is",
"called",
"Multi-Output",
"Convolution",
"Spectral",
"Mixture",
"(MOCSM)",
"kernel.",
"Results",
"of",
"extensive",
"experiments",
"on",
"synthetic",
"and",
"real-life",
"datasets",
"demonstrate",
"the",
"advantages",
"of",
"the",
"proposed",
"kernel",
"and",
"its",
"state",
"of",
"the",
"art",
"performance.",
"MOCSM",
"enjoys",
"the",
"desirable",
"property",
"to",
"reduce",
"to",
"the",
"well",
"known",
"Spectral",
"Mixture",
"(SM)",
"kernel",
"when",
"a",
"single-channel",
"is",
"considered.",
"A",
"comparison",
"with",
"the",
"recently",
"introduced",
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"Spectral",
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"this",
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"not",
"the",
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"latter",
"kernel,",
"which",
"contains",
"quadratic",
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"scale",
"effects",
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"the",
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"are",
"either",
"very",
"close",
"or",
"very",
"far",
"from",
"each",
"other",
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"the",
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[
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"localize",
"and",
"identify",
"a",
"query",
"person",
"from",
"realistic,",
"uncropped",
"images.",
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"achieve",
"this",
"goal,",
"state-of-the-art",
"models",
"typically",
"add",
"a",
"re-id",
"branch",
"upon",
"two-stage",
"detectors",
"like",
"Faster",
"R-CNN.",
"Owing",
"to",
"the",
"ROI-Align",
"operation,",
"this",
"pipeline",
"yields",
"promising",
"accuracy",
"as",
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"features",
"are",
"explicitly",
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"with",
"the",
"corresponding",
"object",
"regions,",
"but",
"in",
"the",
"meantime,",
"it",
"introduces",
"high",
"computational",
"overhead",
"due",
"to",
"dense",
"object",
"anchors.",
"In",
"this",
"work,",
"we",
"present",
"an",
"anchor-free",
"approach",
"to",
"efficiently",
"tackling",
"this",
"challenging",
"task,",
"by",
"introducing",
"the",
"following",
"dedicated",
"designs.",
"First,",
"we",
"select",
"an",
"anchor-free",
"detector",
"(i.e.,",
"FCOS)",
"as",
"the",
"prototype",
"of",
"our",
"framework.",
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"to",
"the",
"lack",
"of",
"dense",
"object",
"anchors,",
"it",
"exhibits",
"significantly",
"higher",
"efficiency",
"compared",
"with",
"existing",
"person",
"search",
"models.",
"Second,",
"when",
"directly",
"accommodating",
"this",
"anchor-free",
"detector",
"for",
"person",
"search,",
"there",
"exist",
"several",
"major",
"challenges",
"in",
"learning",
"robust",
"re-id",
"features,",
"which",
"we",
"summarize",
"as",
"the",
"misalignment",
"issues",
"in",
"different",
"levels",
"(i.e.,",
"scale,",
"region,",
"and",
"task).",
"To",
"address",
"these",
"issues,",
"we",
"propose",
"an",
"aligned",
"feature",
"aggregation",
"module",
"to",
"generate",
"more",
"discriminative",
"and",
"robust",
"feature",
"embeddings.",
"Accordingly,",
"we",
"name",
"our",
"model",
"as",
"Feature-Aligned",
"Person",
"Search",
"Network",
"(AlignPS",
").",
"Third,",
"by",
"investigating",
"the",
"advantages",
"of",
"both",
"anchor-based",
"and",
"anchor-free",
"models,",
"we",
"further",
"augment",
"AlignPS",
"with",
"an",
"ROI-Align",
"head,",
"which",
"significantly",
"improves",
"the",
"robustness",
"of",
"re-id",
"features",
"while",
"still",
"keeping",
"our",
"model",
"highly",
"efficient.",
"Extensive",
"experiments",
"conducted",
"on",
"two",
"challenging",
"benchmarks",
"(i.e.,",
"CUHK-SYSU",
"and",
"PRW)",
"demonstrate",
"that",
"our",
"framework",
"achieves",
"state-of-the-art",
"or",
"competitive",
"performance,",
"while",
"displaying",
"higher",
"efficiency.",
"All",
"the",
"source",
"codes,",
"data,",
"and",
"trained",
"models",
"are",
"available",
"at:",
"https://github.com/daodaofr/alignps."
] |
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[
"In",
"recent",
"years,",
"the",
"amount",
"of",
"Cyber",
"Security",
"data",
"generated",
"in",
"the",
"form",
"of",
"unstructured",
"texts,",
"for",
"example,",
"social",
"media",
"resources,",
"blogs,",
"articles,",
"and",
"so",
"on",
"has",
"exceptionally",
"increased.",
"Named",
"Entity",
"Recognition",
"(NER",
")",
"is",
"an",
"initial",
"step",
"towards",
"converting",
"this",
"unstructured",
"data",
"into",
"structured",
"data",
"which",
"can",
"be",
"used",
"by",
"a",
"lot",
"of",
"applications.",
"The",
"existing",
"methods",
"on",
"NER",
"for",
"Cyber",
"Security",
"data",
"are",
"based",
"on",
"rules",
"and",
"linguistic",
"characteristics.",
"A",
"Deep",
"Learning",
"(DL)",
"based",
"approach",
"embedded",
"with",
"Conditional",
"Random",
"Fields",
"(CRF",
"s)",
"is",
"proposed",
"in",
"this",
"paper.",
"Several",
"DL",
"architectures",
"are",
"evaluated",
"to",
"find",
"the",
"most",
"optimal",
"architecture.",
"The",
"combination",
"of",
"Bidirectional",
"Gated",
"Recurrent",
"Unit",
"(Bi-GRU),",
"Convolutional",
"Neural",
"Network",
"(CNN),",
"and",
"CRF",
"performed",
"better",
"compared",
"to",
"various",
"other",
"DL",
"frameworks",
"on",
"a",
"publicly",
"available",
"benchmark",
"dataset.",
"This",
"may",
"be",
"due",
"to",
"the",
"reason",
"that",
"the",
"bidirectional",
"structures",
"preserve",
"the",
"features",
"related",
"to",
"the",
"future",
"and",
"previous",
"words",
"in",
"a",
"sequence."
] |
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[
"We",
"developed",
"a",
"Japanese",
"morphological",
"analyzer",
"that",
"uses",
"the",
"co-occurrence",
"of",
"words",
"to",
"select",
"the",
"correct",
"sequence",
"of",
"words",
"in",
"an",
"unsegmented",
"Japanese",
"sentence",
".",
"The",
"co-occurrence",
"information",
"can",
"be",
"obtained",
"from",
"cases",
"where",
"the",
"system",
"incorrectly",
"analyzes",
"sentences",
".",
"As",
"the",
"amount",
"of",
"information",
"increases",
",",
"the",
"accuracy",
"of",
"the",
"system",
"increases",
"with",
"a",
"small",
"risk",
"of",
"degradation",
".",
"Experimental",
"results",
"show",
"that",
"the",
"proposed",
"system",
"assigns",
"the",
"correct",
"phonological",
"representations",
"to",
"unsegmented",
"Japanese",
"sentences",
"more",
"precisely",
"than",
"do",
"other",
"popular",
"systems",
"."
] |
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[
"For",
"a",
"news",
"content",
"distribution",
"platform",
"like",
"Dailyhunt,",
"Named",
"Entity",
"Recognition",
"is",
"a",
"pivotal",
"task",
"for",
"building",
"better",
"user",
"recommendation",
"and",
"notification",
"algorithms.",
"Apart",
"from",
"identifying",
"names,",
"locations,",
"organisations",
"from",
"the",
"news",
"for",
"13+",
"Indian",
"languages",
"and",
"use",
"them",
"in",
"algorithms,",
"we",
"also",
"need",
"to",
"identify",
"n-grams",
"which",
"do",
"not",
"necessarily",
"fit",
"in",
"the",
"definition",
"of",
"Named-Entity,",
"yet",
"they",
"are",
"important.",
"For",
"example,",
"me\tO\ntoo\tO\nmovement,",
"beef\tO\nban,",
"alwar\tO\nmob\tO\nlynching.",
"In",
"this",
"exercise,",
"given",
"an",
"English",
"language",
"text,",
"we",
"are",
"trying",
"to",
"detect",
"case-less",
"n-grams",
"which",
"convey",
"important",
"information",
"and",
"can",
"be",
"used",
"as",
"topics",
"and/or",
"hashtags",
"for",
"a",
"news.",
"Model",
"is",
"built",
"using",
"Wikipedia",
"titles",
"data,",
"private",
"English",
"news",
"corpus",
"and",
"BERT-Multilingual",
"pre-trained",
"model,",
"Bi-GRU",
"and",
"CRF",
"architecture.",
"It",
"shows",
"promising",
"results",
"when",
"compared",
"with",
"industry",
"best",
"Flair,",
"Spacy",
"and",
"Stanford-caseless-NER",
"in",
"terms",
"of",
"F1",
"and",
"especially",
"Recall."
] |
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[
"This",
"work",
"is",
"about",
"the",
"semantic",
"segmentation",
"of",
"skin",
"lesion",
"boundary",
"and",
"their",
"attributes",
"using",
"Image-to-Image",
"Translation",
"with",
"Conditional",
"Adversarial",
"Nets.",
"Melanoma",
"is",
"a",
"type",
"of",
"skin",
"cancer",
"that",
"can",
"be",
"cured",
"if",
"detected",
"in",
"time.",
"Segmentation",
"into",
"dermoscopic",
"images",
"is",
"an",
"essential",
"procedure",
"for",
"computer-assisted",
"diagnosis",
"due",
"to",
"its",
"existing",
"artifacts",
"typical",
"of",
"skin",
"images.",
"To",
"alleviate",
"the",
"image",
"annotation",
"process,",
"we",
"propose",
"to",
"use",
"a",
"modified",
"Pix2Pix",
"network.",
"The",
"discriminator",
"network",
"learns",
"the",
"mapping",
"from",
"a",
"dermal",
"image",
"as",
"an",
"input",
"and",
"a",
"mask",
"image",
"of",
"six",
"channels",
"as",
"an",
"output.",
"Likewise,",
"the",
"discriminative",
"network",
"output",
"called",
"PatchGAN",
"is",
"varied",
"for",
"one",
"channel",
"and",
"six",
"output",
"channels.",
"The",
"photos",
"used",
"come",
"from",
"the",
"2018",
"ISIC",
"Challenge,",
"where",
"500",
"photographs",
"are",
"used",
"with",
"their",
"respective",
"semantic",
"map,",
"divided",
"into",
"75%",
"for",
"training",
"and",
"35%",
"for",
"testing.",
"Obtaining",
"for",
"100",
"training",
"epochs",
"high",
"Jaccard",
"indices",
"for",
"all",
"attributes",
"of",
"the",
"segmentation",
"map."
] |
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[
"Graph",
"Neural",
"Networks",
"(GNNs)",
"have",
"recently",
"received",
"significant",
"research",
"attention",
"due",
"to",
"their",
"superior",
"performance",
"on",
"a",
"variety",
"of",
"graph-related",
"learning",
"tasks.",
"Most",
"of",
"the",
"current",
"works",
"focus",
"on",
"either",
"static",
"or",
"dynamic",
"graph",
"settings,",
"addressing",
"a",
"single",
"particular",
"task,",
"e.g.,",
"node/graph",
"classification,",
"link",
"prediction.",
"In",
"this",
"work,",
"we",
"investigate",
"the",
"question:",
"can",
"GNNs",
"be",
"applied",
"to",
"continuously",
"learning",
"a",
"sequence",
"of",
"tasks?",
"Towards",
"that,",
"we",
"explore",
"the",
"Continual",
"Graph",
"Learning",
"(CGL)",
"paradigm",
"and",
"present",
"the",
"Experience",
"Replay",
"based",
"framework",
"ER-GNN",
"for",
"CGL",
"to",
"alleviate",
"the",
"catastrophic",
"forgetting",
"problem",
"in",
"existing",
"GNNs.",
"ER-GNN",
"stores",
"knowledge",
"from",
"previous",
"tasks",
"as",
"experiences",
"and",
"replays",
"them",
"when",
"learning",
"new",
"tasks",
"to",
"mitigate",
"the",
"catastrophic",
"forgetting",
"issue.",
"We",
"propose",
"three",
"experience",
"node",
"selection",
"strategies:",
"mean",
"of",
"feature,",
"coverage",
"maximization,",
"and",
"influence",
"maximization,",
"to",
"guide",
"the",
"process",
"of",
"selecting",
"experience",
"nodes.",
"Extensive",
"experiments",
"on",
"three",
"benchmark",
"datasets",
"demonstrate",
"the",
"effectiveness",
"of",
"our",
"ER-GNN",
"and",
"shed",
"light",
"on",
"the",
"incremental",
"graph",
"(non-Euclidean)",
"structure",
"learning."
] |
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[
"In",
"this",
"paper,",
"we",
"introduce",
"a",
"new",
"approach",
"to",
"dealing",
"with",
"the",
"problem",
"of",
"case-sensitiveness",
"in",
"Language",
"Modelling",
"(LM).",
"We",
"propose",
"simple",
"architecture",
"modification",
"to",
"the",
"RoBERTa",
"language",
"model,",
"accompanied",
"by",
"a",
"new",
"tokenization",
"strategy,",
"which",
"we",
"named",
"Unified",
"Case",
"LM",
"(UniCase).",
"We",
"tested",
"our",
"solution",
"on",
"the",
"GLUE",
"benchmark,",
"which",
"led",
"to",
"increased",
"performance",
"by",
"0.42",
"points.",
"Moreover,",
"we",
"prove",
"that",
"the",
"UniCase",
"model",
"works",
"much",
"better",
"when",
"we",
"have",
"to",
"deal",
"with",
"text",
"data,",
"where",
"all",
"tokens",
"are",
"uppercased",
"(+5.88",
"point)."
] |
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[
"There",
"has",
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"renewed",
"recent",
"interest",
"in",
"developing",
"effective",
"lower",
"boundsfor",
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"Time",
"Warping",
"(DTW",
")",
"distance",
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"time",
"series.",
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"indexing,",
"clustering,",
"forecasting,",
"regression",
"andclassification.",
"One",
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"classification",
"algorithms,",
"thenearest",
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"with",
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")",
"is",
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"quadratic",
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"of",
"DTW",
".",
"Lower",
"bound",
"search",
"can",
"speedup",
"NN-DTW",
"substantially.",
"An",
"effective",
"and",
"tight",
"lower",
"bound",
"quickly",
"prunes",
"offunpromising",
"nearest",
"neighbor",
"candidates",
"from",
"the",
"search",
"space",
"and",
"minimises",
"thenumber",
"of",
"the",
"costly",
"DTW",
"computations.",
"The",
"speed",
"up",
"provided",
"by",
"lower",
"boundsearch",
"becomes",
"increasingly",
"critical",
"as",
"training",
"set",
"size",
"increases.",
"Differentlower",
"bounds",
"provide",
"different",
"trade-offs",
"between",
"computation",
"time",
"andtightness.",
"Most",
"existing",
"lower",
"bounds",
"interact",
"with",
"DTW",
"warping",
"window",
"sizes.They",
"are",
"very",
"tight",
"and",
"effective",
"at",
"smaller",
"warping",
"window",
"sizes,",
"but",
"becomelooser",
"as",
"the",
"warping",
"window",
"increases,",
"thus",
"reducing",
"the",
"pruning",
"effectivenessfor",
"NN-DTW",
".",
"In",
"this",
"work,",
"we",
"present",
"a",
"new",
"class",
"of",
"lower",
"bounds",
"that",
"aretighter",
"than",
"the",
"popular",
"Keogh",
"lower",
"bound,",
"while",
"requiring",
"similar",
"computationtime.",
"Our",
"new",
"lower",
"bounds",
"take",
"advantage",
"of",
"the",
"DTW",
"boundary",
"condition,monotonicity",
"and",
"continuity",
"constraints",
"to",
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"a",
"tighter",
"lower",
"bound.",
"Ofparticular",
"significance,",
"they",
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"relatively",
"tight",
"even",
"for",
"large",
"windows.",
"Asingle",
"parameter",
"to",
"these",
"new",
"lower",
"bounds",
"controls",
"the",
"speed-tightnesstrade-off.",
"We",
"demonstrate",
"that",
"these",
"new",
"lower",
"bounds",
"provide",
"an",
"exceptionalbalance",
"between",
"computation",
"time",
"and",
"tightness",
"for",
"the",
"NN-DTW",
"time",
"seriesclassification",
"task,",
"resulting",
"in",
"greatly",
"improved",
"efficiency",
"for",
"NN-DTW",
"lowerbound",
"search."
] |
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[
"Multimodal",
"Machine",
"Translation",
"(MMT)",
"aims",
"to",
"introduce",
"information",
"from",
"other",
"modality,",
"generally",
"static",
"images,",
"to",
"improve",
"the",
"translation",
"quality.",
"Previous",
"works",
"propose",
"various",
"incorporation",
"methods,",
"but",
"most",
"of",
"them",
"do",
"not",
"consider",
"the",
"relative",
"importance",
"of",
"multiple",
"modalities.",
"Equally",
"treating",
"all",
"modalities",
"may",
"encode",
"too",
"much",
"useless",
"information",
"from",
"less",
"important",
"modalities.",
"In",
"this",
"paper,",
"we",
"introduce",
"the",
"multimodal",
"self-attention",
"in",
"Transformer",
"to",
"solve",
"the",
"issues",
"above",
"in",
"MMT.",
"The",
"proposed",
"method",
"learns",
"the",
"representation",
"of",
"images",
"based",
"on",
"the",
"text,",
"which",
"avoids",
"encoding",
"irrelevant",
"information",
"in",
"images.",
"Experiments",
"and",
"visualization",
"analysis",
"demonstrate",
"that",
"our",
"model",
"benefits",
"from",
"visual",
"information",
"and",
"substantially",
"outperforms",
"previous",
"works",
"and",
"competitive",
"baselines",
"in",
"terms",
"of",
"various",
"metrics."
] |
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[
"Recent",
"works",
"in",
"Grammatical",
"Error",
"Correction",
"(GEC)",
"have",
"leveraged",
"the",
"progress",
"in",
"Neural",
"Machine",
"Translation",
"(NMT),",
"to",
"learn",
"rewrites",
"from",
"parallel",
"corpora",
"of",
"grammatically",
"incorrect",
"and",
"corrected",
"sentences,",
"achieving",
"state-of-the-art",
"results.",
"At",
"the",
"same",
"time,",
"Generative",
"Adversarial",
"Networks",
"(GANs)",
"have",
"been",
"successful",
"in",
"generating",
"realistic",
"texts",
"across",
"many",
"different",
"tasks",
"by",
"learning",
"to",
"directly",
"minimize",
"the",
"difference",
"between",
"human-generated",
"and",
"synthetic",
"text.",
"In",
"this",
"work,",
"we",
"present",
"an",
"adversarial",
"learning",
"approach",
"to",
"GEC,",
"using",
"the",
"generator-discriminator",
"framework.",
"The",
"generator",
"is",
"a",
"Transformer",
"model,",
"trained",
"to",
"produce",
"grammatically",
"correct",
"sentences",
"given",
"grammatically",
"incorrect",
"ones.",
"The",
"discriminator",
"is",
"a",
"sentence-pair",
"classification",
"model,",
"trained",
"to",
"judge",
"a",
"given",
"pair",
"of",
"grammatically",
"incorrect-correct",
"sentences",
"on",
"the",
"quality",
"of",
"grammatical",
"correction.",
"We",
"pre-train",
"both",
"the",
"discriminator",
"and",
"the",
"generator",
"on",
"parallel",
"texts",
"and",
"then",
"fine-tune",
"them",
"further",
"using",
"a",
"policy",
"gradient",
"method",
"that",
"assigns",
"high",
"rewards",
"to",
"sentences",
"which",
"could",
"be",
"TRUE",
"corrections",
"of",
"the",
"grammatically",
"incorrect",
"text.",
"Experimental",
"results",
"on",
"FCE,",
"CoNLL-14,",
"and",
"BEA-19",
"datasets",
"show",
"that",
"Adversarial-GEC",
"can",
"achieve",
"competitive",
"GEC",
"quality",
"compared",
"to",
"NMT-based",
"baselines."
] |
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"Inspired",
"by",
"the",
"seminal",
"work",
"on",
"Stein",
"Variational",
"Inference",
"and",
"SteinVariational",
"Policy",
"Gradient,",
"we",
"derived",
"a",
"method",
"to",
"generate",
"samples",
"from",
"theposterior",
"variational",
"parameter",
"distribution",
"by",
"\\textit{explicitly}",
"minimizingthe",
"KL",
"divergence",
"to",
"match",
"the",
"target",
"distribution",
"in",
"an",
"amortize",
"fashion.Consequently,",
"we",
"applied",
"this",
"varational",
"inference",
"technique",
"into",
"vanillapolicy",
"gradient,",
"TRPO",
"and",
"PPO",
"with",
"Bayesian",
"Neural",
"Network",
"parameterizationsfor",
"reinforcement",
"learning",
"problems."
] |
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[
"Commonsense",
"can",
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"like",
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"Language",
"Understanding",
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"underspecification.",
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"on",
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"present",
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"multilingual",
"knowledge",
"graph",
"ConceptNet,",
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"in",
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"Entity",
"Recognition",
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"Our",
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"BiLSTM",
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"a",
"CRF",
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"pre-trained",
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"layers",
"and",
"dropout",
"layers.",
"Moreover,",
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"using",
"word",
"representations,",
"we",
"used",
"also",
"character-based",
"representation",
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"the",
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"and",
"the",
"orthographic",
"information.",
"Our",
"experiments",
"and",
"evaluations",
"showed",
"an",
"improvement",
"in",
"the",
"overall",
"performance",
"with",
"2.86",
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"Commonsense",
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"NLP",
"tasks",
"but",
"to",
"the",
"best",
"of",
"our",
"knowledge,",
"there",
"is",
"no",
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"relating",
"the",
"integration",
"of",
"a",
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"knowledge",
"base",
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"NER."
] |
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[
"We",
"focus",
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"task",
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"3D",
"object",
"detection",
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"bounding",
"box",
"of",
"an",
"object",
"in",
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"form",
"at",
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"fullextent.",
"We",
"introduce",
"Deep",
"Sliding",
"Shapes,",
"a",
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"ConvNet",
"formulation",
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"3D",
"object",
"boundingboxes.",
"In",
"our",
"approach,",
"we",
"propose",
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"first",
"3D",
"Region",
"Proposal",
"Network",
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")to",
"learn",
"objectness",
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"shapes",
"and",
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"first",
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"ObjectRecognition",
"Network",
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"colorfeatures",
"in",
"2D.",
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"particular,",
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"amodal",
"RPN",
"at",
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"to",
"regress",
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"boxes.Experiments",
"show",
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"our",
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"outperforms",
"the",
"state-of-the-art",
"by",
"13.8",
"inmAP",
"and",
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"the",
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"Shapes.",
"All",
"source",
"code",
"andpre-trained",
"models",
"will",
"be",
"available",
"at",
"GitHub."
] |
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"event",
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"newswire",
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".",
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"describe",
"a",
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"event",
"chains",
".",
"The",
"first",
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"distributional",
"methods",
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"relations",
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"events",
"sharing",
"coreferring",
"arguments",
".",
"The",
"second",
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"temporal",
"classifier",
"to",
"partially",
"order",
"the",
"connected",
"events",
".",
"Finally",
",",
"the",
"third",
"prunes",
"and",
"clusters",
"self-contained",
"chains",
"from",
"the",
"space",
"of",
"events",
".",
"We",
"introduce",
"two",
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":",
"the",
"narrative",
"cloze",
"to",
"evaluate",
"event",
"relatedness",
",",
"and",
"an",
"order",
"coherence",
"task",
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"order",
".",
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"show",
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"36",
"%",
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"baseline",
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"narrative",
"prediction",
"and",
"25",
"%",
"for",
"temporal",
"coherence",
"."
] |
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"Vision-based",
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"capacity",
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"neuralnetworks",
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"However,",
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"network",
"leads",
"to",
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"costs(power,",
"latency,",
"silicon",
"area,",
"MAC",
"count).",
"Many",
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"optimizations",
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"offer",
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"sparsity,",
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"designing",
"actual",
"hardware",
"to",
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"isdifficult.",
"On",
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"other",
"hand,",
"distillation",
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"DQN",
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"high",
"capacity",
"teacherQ-function",
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"via",
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")",
"algorithm.",
"Our",
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"adapts",
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"distillation",
"work",
"to",
"the",
"actor-critic",
"Proximal",
"Policy",
"Optimizationalgorithm.",
"PPO",
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"to",
"implement",
"and",
"has",
"much",
"higher",
"performance",
"than",
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"We",
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"a",
"distilled",
"PPO",
"student",
"can",
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"a",
"DQN",
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"We",
"also",
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"low",
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"Finally,",
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"the",
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"In",
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[
"This",
"paper",
"presents",
"a",
"production",
"Semi-Supervised",
"Learning",
"(SSL)",
"pipeline",
"based",
"on",
"the",
"student-teacher",
"framework,",
"which",
"leverages",
"millions",
"of",
"unlabeled",
"examples",
"to",
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"Natural",
"Language",
"Understanding",
"(NLU)",
"tasks.",
"We",
"investigate",
"two",
"questions",
"related",
"to",
"the",
"use",
"of",
"unlabeled",
"data",
"in",
"production",
"SSL",
"context:",
"1)",
"how",
"to",
"select",
"samples",
"from",
"a",
"huge",
"unlabeled",
"data",
"pool",
"that",
"are",
"beneficial",
"for",
"SSL",
"training,",
"and",
"2)",
"how",
"do",
"the",
"selected",
"data",
"affect",
"the",
"performance",
"of",
"different",
"state-of-the-art",
"SSL",
"techniques.",
"We",
"compare",
"four",
"widely",
"used",
"SSL",
"techniques,",
"Pseudo-Label",
"(PL),",
"Knowledge",
"Distillation",
"(KD),",
"Virtual",
"Adversarial",
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"(VAT)",
"and",
"Cross-View",
"Training",
"(CVT)",
"in",
"conjunction",
"with",
"two",
"data",
"selection",
"methods",
"including",
"committee-based",
"selection",
"and",
"submodular",
"optimization",
"based",
"selection.",
"We",
"further",
"examine",
"the",
"benefits",
"and",
"drawbacks",
"of",
"these",
"techniques",
"when",
"applied",
"to",
"intent",
"classification",
"(IC)",
"and",
"named",
"entity",
"recognition",
"(NER)",
"tasks,",
"and",
"provide",
"guidelines",
"specifying",
"when",
"each",
"of",
"these",
"methods",
"might",
"be",
"beneficial",
"to",
"improve",
"large",
"scale",
"NLU",
"systems."
] |
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[
"Semantic",
"segmentation",
"is",
"a",
"crucial",
"task",
"in",
"biomedical",
"image",
"processing,",
"which",
"recent",
"breakthroughs",
"in",
"deep",
"learning",
"have",
"allowed",
"to",
"improve.",
"However,",
"deep",
"learning",
"methods",
"in",
"general",
"are",
"not",
"yet",
"widely",
"used",
"in",
"practice",
"since",
"they",
"require",
"large",
"amount",
"of",
"data",
"for",
"training",
"complex",
"models.",
"This",
"is",
"particularly",
"challenging",
"for",
"biomedical",
"images,",
"because",
"data",
"and",
"ground",
"truths",
"are",
"a",
"scarce",
"resource.",
"Annotation",
"efforts",
"for",
"biomedical",
"images",
"come",
"with",
"a",
"real",
"cost,",
"since",
"experts",
"have",
"to",
"manually",
"label",
"images",
"at",
"pixel-level",
"on",
"samples",
"usually",
"containing",
"many",
"instances",
"of",
"the",
"target",
"anatomy",
"(e.g.",
"in",
"histology",
"samples:",
"neurons,",
"astrocytes,",
"mitochondria,",
"etc.).",
"In",
"this",
"paper",
"we",
"provide",
"a",
"framework",
"for",
"Deep",
"Active",
"Learning",
"applied",
"to",
"a",
"real-world",
"scenario.",
"Our",
"framework",
"relies",
"on",
"the",
"U-Net",
"architecture",
"and",
"overall",
"uncertainty",
"measure",
"to",
"suggest",
"which",
"sample",
"to",
"annotate.",
"It",
"takes",
"advantage",
"of",
"the",
"uncertainty",
"measure",
"obtained",
"by",
"taking",
"Monte",
"Carlo",
"samples",
"while",
"using",
"Dropout",
"regularization",
"scheme.",
"Experiments",
"were",
"done",
"on",
"spinal",
"cord",
"and",
"brain",
"microscopic",
"histology",
"samples",
"to",
"perform",
"a",
"myelin",
"segmentation",
"task.",
"Two",
"realistic",
"small",
"datasets",
"of",
"14",
"and",
"24",
"images",
"were",
"used,",
"from",
"different",
"acquisition",
"settings",
"(Serial",
"Block-Face",
"Electron",
"Microscopy",
"and",
"Transmitting",
"Electron",
"Microscopy",
")",
"and",
"showed",
"that",
"our",
"method",
"reached",
"a",
"maximum",
"Dice",
"value",
"after",
"adding",
"3",
"uncertainty-selected",
"samples",
"to",
"the",
"initial",
"training",
"set,",
"versus",
"15",
"randomly-selected",
"samples,",
"thereby",
"significantly",
"reducing",
"the",
"annotation",
"effort.",
"We",
"focused",
"on",
"a",
"plausible",
"scenario",
"and",
"showed",
"evidence",
"that",
"this",
"straightforward",
"implementation",
"achieves",
"a",
"high",
"segmentation",
"performance",
"with",
"very",
"few",
"labelled",
"samples.",
"We",
"believe",
"our",
"framework",
"may",
"benefit",
"any",
"biomedical",
"researcher",
"willing",
"to",
"obtain",
"fast",
"and",
"accurate",
"image",
"segmentation",
"on",
"their",
"own",
"dataset.",
"The",
"code",
"is",
"freely",
"available",
"at",
"https://github.com/neuropoly/deep-active-learning."
] |
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[
"Recent",
"work",
"on",
"evaluating",
"grammatical",
"knowledge",
"in",
"pretrained",
"sentence",
"encoders",
"gives",
"a",
"fine-grained",
"view",
"of",
"a",
"small",
"number",
"of",
"phenomena.",
"We",
"introduce",
"a",
"new",
"analysis",
"dataset",
"that",
"also",
"has",
"broad",
"coverage",
"of",
"linguistic",
"phenomena.",
"We",
"annotate",
"the",
"development",
"set",
"of",
"the",
"Corpus",
"of",
"Linguistic",
"Acceptability",
"(CoLA;",
"Warstadt",
"et",
"al.,",
"2018)",
"for",
"the",
"presence",
"of",
"13",
"classes",
"of",
"syntactic",
"phenomena",
"including",
"various",
"forms",
"of",
"argument",
"alternations,",
"movement,",
"and",
"modification.",
"We",
"use",
"this",
"analysis",
"set",
"to",
"investigate",
"the",
"grammatical",
"knowledge",
"of",
"three",
"pretrained",
"encoders:",
"BERT",
"(Devlin",
"et",
"al.,",
"2018),",
"GPT",
"(Radford",
"et",
"al.,",
"2018),",
"and",
"the",
"BiLSTM",
"baseline",
"from",
"Warstadt",
"et",
"al.",
"We",
"find",
"that",
"these",
"models",
"have",
"a",
"strong",
"command",
"of",
"complex",
"or",
"non-canonical",
"argument",
"structures",
"like",
"ditransitives",
"(Sue",
"gave",
"Dan",
"a",
"book)",
"and",
"passives",
"(The",
"book",
"was",
"read).",
"Sentences",
"with",
"long",
"distance",
"dependencies",
"like",
"questions",
"(What",
"do",
"you",
"think",
"I",
"ate?)",
"challenge",
"all",
"models,",
"but",
"for",
"these,",
"BERT",
"and",
"GPT",
"have",
"a",
"distinct",
"advantage",
"over",
"the",
"baseline.",
"We",
"conclude",
"that",
"recent",
"sentence",
"encoders,",
"despite",
"showing",
"near-human",
"performance",
"on",
"acceptability",
"classification",
"overall,",
"still",
"fail",
"to",
"make",
"fine-grained",
"grammaticality",
"distinctions",
"for",
"many",
"complex",
"syntactic",
"structures."
] |
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[
"Although",
"BERT",
"is",
"widely",
"used",
"by",
"the",
"NLP",
"community,",
"little",
"is",
"known",
"about",
"its",
"inner",
"workings.",
"Several",
"attempts",
"have",
"been",
"made",
"to",
"shed",
"light",
"on",
"certain",
"aspects",
"of",
"BERT",
",",
"often",
"with",
"contradicting",
"conclusions.",
"A",
"much",
"raised",
"concern",
"focuses",
"on",
"BERT",
"'s",
"over-parameterization",
"and",
"under-utilization",
"issues.",
"To",
"this",
"end,",
"we",
"propose",
"o",
"novel",
"approach",
"to",
"fine-tune",
"BERT",
"in",
"a",
"structured",
"manner.",
"Specifically,",
"we",
"focus",
"on",
"Large",
"Scale",
"Multilabel",
"Text",
"Classification",
"(LMTC)",
"where",
"documents",
"are",
"assigned",
"with",
"one",
"or",
"more",
"labels",
"from",
"a",
"large",
"predefined",
"set",
"of",
"hierarchically",
"organized",
"labels.",
"Our",
"approach",
"guides",
"specific",
"BERT",
"layers",
"to",
"predict",
"labels",
"from",
"specific",
"hierarchy",
"levels.",
"Experimenting",
"with",
"two",
"LMTC",
"datasets",
"we",
"show",
"that",
"this",
"structured",
"fine-tuning",
"approach",
"not",
"only",
"yields",
"better",
"classification",
"results",
"but",
"also",
"leads",
"to",
"better",
"parameter",
"utilization."
] |
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[
"Building",
"the",
"Natural",
"Language",
"Understanding",
"(NLU)",
"modules",
"of",
"task-oriented",
"Spoken",
"Dialogue",
"Systems",
"(SDS)",
"involves",
"a",
"definition",
"of",
"intents",
"and",
"entities,",
"collection",
"of",
"task-relevant",
"data,",
"annotating",
"the",
"data",
"with",
"intents",
"and",
"entities,",
"and",
"then",
"repeating",
"the",
"same",
"process",
"over",
"and",
"over",
"again",
"for",
"adding",
"any",
"functionality/enhancement",
"to",
"the",
"SDS.",
"In",
"this",
"work,",
"we",
"showcase",
"an",
"Intent",
"Bulk",
"Labeling",
"system",
"where",
"SDS",
"developers",
"can",
"interactively",
"label",
"and",
"augment",
"training",
"data",
"from",
"unlabeled",
"utterance",
"corpora",
"using",
"advanced",
"clustering",
"and",
"visual",
"labeling",
"methods.",
"We",
"extend",
"the",
"Deep",
"Aligned",
"Clustering",
"work",
"with",
"a",
"better",
"backbone",
"BERT",
"model,",
"explore",
"techniques",
"to",
"select",
"the",
"seed",
"data",
"for",
"labeling,",
"and",
"develop",
"a",
"data",
"balancing",
"method",
"using",
"an",
"oversampling",
"technique",
"that",
"utilizes",
"paraphrasing",
"models.",
"We",
"also",
"look",
"at",
"the",
"effect",
"of",
"data",
"augmentation",
"on",
"the",
"clustering",
"process.",
"Our",
"results",
"show",
"that",
"we",
"can",
"achieve",
"over",
"10%",
"gain",
"in",
"clustering",
"accuracy",
"on",
"some",
"datasets",
"using",
"the",
"combination",
"of",
"the",
"above",
"techniques.",
"Finally,",
"we",
"extract",
"utterance",
"embeddings",
"from",
"the",
"clustering",
"model",
"and",
"plot",
"the",
"data",
"to",
"interactively",
"bulk",
"label",
"the",
"samples,",
"reducing",
"the",
"time",
"and",
"effort",
"for",
"data",
"labeling",
"of",
"the",
"whole",
"dataset",
"significantly."
] |
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[
"Convolutional",
"neural",
"networks",
"(CNNs)",
"have",
"been",
"used",
"quite",
"successfully",
"for",
"semantic",
"segmentation",
"of",
"brain",
"tumors.",
"However,",
"current",
"CNNs",
"and",
"attention",
"mechanisms",
"are",
"stochastic",
"in",
"nature",
"and",
"neglect",
"the",
"morphological",
"indicators",
"used",
"by",
"radiologists",
"to",
"manually",
"annotate",
"regions",
"of",
"interest.",
"In",
"this",
"paper,",
"we",
"introduce",
"a",
"channel",
"and",
"spatial",
"wise",
"asymmetric",
"attention",
"(CASPIAN)",
"by",
"leveraging",
"the",
"inherent",
"structure",
"of",
"tumors",
"to",
"detect",
"regions",
"of",
"saliency.",
"To",
"demonstrate",
"the",
"efficacy",
"of",
"our",
"proposed",
"layer,",
"we",
"integrate",
"this",
"into",
"a",
"well-established",
"convolutional",
"neural",
"network",
"(CNN)",
"architecture",
"to",
"achieve",
"higher",
"Dice",
"scores,",
"with",
"less",
"GPU",
"resources.",
"Also,",
"we",
"investigate",
"the",
"inclusion",
"of",
"auxiliary",
"multiscale",
"and",
"multiplanar",
"attention",
"branches",
"to",
"increase",
"the",
"spatial",
"context",
"crucial",
"in",
"semantic",
"segmentation",
"tasks.",
"The",
"resulting",
"architecture",
"is",
"the",
"new",
"CASPIANET++,",
"which",
"achieves",
"Dice",
"Scores",
"of",
"91.19%",
"whole",
"tumor,",
"87.60%",
"for",
"tumor",
"core",
"and",
"81.03%",
"for",
"enhancing",
"tumor.",
"Furthermore,",
"driven",
"by",
"the",
"scarcity",
"of",
"brain",
"tumor",
"data,",
"we",
"investigate",
"the",
"Noisy",
"Student",
"method",
"for",
"segmentation",
"tasks.",
"Our",
"new",
"Noisy",
"Student",
"Curriculum",
"Learning",
"paradigm,",
"which",
"infuses",
"noise",
"incrementally",
"to",
"increase",
"the",
"complexity",
"of",
"the",
"training",
"images",
"exposed",
"to",
"the",
"network,",
"further",
"boosts",
"the",
"enhancing",
"tumor",
"region",
"to",
"81.53%.",
"Additional",
"validation",
"performed",
"on",
"the",
"BraTS2020",
"data",
"shows",
"that",
"the",
"Noisy",
"Student",
"Curriculum",
"Learning",
"method",
"works",
"well",
"without",
"any",
"additional",
"training",
"or",
"finetuning."
] |
[
6,
6,
6,
6,
6,
6,
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[
"In",
"this",
"paper,",
"a",
"new",
"offline",
"actor-critic",
"learning",
"algorithm",
"is",
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"Policy",
"Gradient",
"(SPG).",
"SPG",
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"space",
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"policy",
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"the",
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"samples.",
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"allows",
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"more",
"globally",
"thandeterministic",
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"),",
"enabling",
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"to",
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"and",
"the",
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"algorithmsCACLA",
"and",
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"in",
"a",
"pellet",
"collection",
"task",
"and",
"a",
"self",
"play",
"environment",
"in",
"thegame",
"Agar.io.",
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"online",
"game",
"Agar.io",
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"popular",
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"theinternet",
"due",
"to",
"intuitive",
"game",
"design",
"and",
"the",
"ability",
"to",
"instantly",
"competeagainst",
"players",
"around",
"the",
"world.",
"From",
"the",
"point",
"of",
"view",
"of",
"artificialintelligence",
"this",
"game",
"is",
"also",
"very",
"intriguing:",
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"game",
"has",
"a",
"continuous",
"inputand",
"action",
"space",
"and",
"allows",
"to",
"have",
"diverse",
"agents",
"with",
"complex",
"strategiescompete",
"against",
"each",
"other.",
"The",
"experimental",
"results",
"show",
"that",
"Q-Learning",
"andCACLA",
"outperform",
"a",
"pre-programmed",
"greedy",
"bot",
"in",
"the",
"pellet",
"collection",
"task,",
"butall",
"algorithms",
"fail",
"to",
"outperform",
"this",
"bot",
"in",
"a",
"fighting",
"scenario.",
"The",
"SPGalgorithm",
"is",
"analyzed",
"to",
"have",
"great",
"extendability",
"through",
"offline",
"explorationand",
"it",
"matches",
"DPG",
"in",
"performance",
"even",
"in",
"its",
"basic",
"form",
"without",
"extensivesampling."
] |
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[
"The",
"phenomenon",
"of",
"mixing",
"the",
"vocabulary",
"and",
"syntax",
"of",
"multiple",
"languages",
"within",
"the",
"same",
"utterance",
"is",
"called",
"Code-Mixing.",
"This",
"is",
"more",
"evident",
"in",
"multilingual",
"societies.",
"In",
"this",
"paper,",
"we",
"have",
"developed",
"a",
"system",
"for",
"SemEval",
"2020:00:00",
"Task",
"9",
"on",
"Sentiment",
"Analysis",
"for",
"Code-Mixed",
"Social",
"Media",
"Text.",
"Our",
"system",
"first",
"generates",
"two",
"types",
"of",
"embeddings",
"for",
"the",
"social",
"media",
"text.",
"In",
"those,",
"the",
"first",
"one",
"is",
"character",
"level",
"embeddings",
"to",
"encode",
"the",
"character",
"level",
"information",
"and",
"to",
"handle",
"the",
"out-of-vocabulary",
"entries",
"and",
"the",
"second",
"one",
"is",
"FastText",
"word",
"embeddings",
"for",
"capturing",
"morphology",
"and",
"semantics.",
"These",
"two",
"embeddings",
"were",
"passed",
"to",
"the",
"LSTM",
"network",
"and",
"the",
"system",
"outperformed",
"the",
"baseline",
"model."
] |
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[
"Graph",
"is",
"a",
"ubiquitous",
"data",
"structure",
"in",
"data",
"science",
"that",
"is",
"widely",
"applied",
"in",
"social",
"networks,",
"knowledge",
"representation",
"graphs,",
"recommendation",
"systems,",
"etc.",
"When",
"given",
"a",
"graph",
"dataset",
"consisting",
"of",
"one",
"graph",
"or",
"more",
"graphs,",
"where",
"the",
"graphs",
"are",
"weighted",
"in",
"general,",
"the",
"first",
"step",
"is",
"often",
"to",
"find",
"clusters",
"in",
"the",
"graphs.",
"In",
"this",
"paper,",
"we",
"present",
"some",
"ongoing",
"research",
"results",
"on",
"graph",
"clustering",
"algorithms",
"for",
"clustering",
"weighted",
"graph",
"datasets,",
"which",
"we",
"name",
"as",
"Weighted",
"Graph",
"Node",
"Clustering",
"via",
"Gumbel",
"Softmax",
"(WGCGS",
"for",
"short).",
"We",
"apply",
"WGCGS",
"on",
"the",
"Karate",
"club",
"weighted",
"network",
"dataset.",
"Our",
"experiments",
"demonstrate",
"that",
"WGCGS",
"can",
"efficiently",
"and",
"effectively",
"find",
"clusters",
"in",
"the",
"Karate",
"club",
"weighted",
"network",
"dataset.",
"Our",
"algorithm's",
"effectiveness",
"is",
"demonstrated",
"by",
"-1",
"comparing",
"the",
"clustering",
"result",
"obtained",
"from",
"our",
"algorithm",
"and",
"the",
"given",
"labels",
"of",
"the",
"dataset;",
"and",
"-2",
"comparing",
"various",
"metrics",
"between",
"our",
"clustering",
"algorithm",
"and",
"other",
"state-of-the-art",
"graph",
"clustering",
"algorithms."
] |
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[
"Document",
"retrieval",
"is",
"a",
"critical",
"component",
"of",
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"answering",
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"QA",
"-RRB-",
",",
"yet",
"little",
"work",
"has",
"been",
"done",
"towards",
"statistical",
"modeling",
"of",
"queries",
"and",
"towards",
"automatic",
"generation",
"of",
"high",
"quality",
"query",
"content",
"for",
"QA",
".",
"This",
"paper",
"introduces",
"a",
"new",
",",
"cluster-based",
"query",
"expansion",
"method",
"that",
"learns",
"queries",
"known",
"to",
"be",
"successful",
"when",
"applied",
"to",
"similar",
"questions",
".",
"We",
"show",
"that",
"cluster-based",
"expansion",
"improves",
"the",
"retrieval",
"performance",
"of",
"a",
"statistical",
"question",
"answering",
"system",
"when",
"used",
"in",
"addition",
"to",
"existing",
"query",
"expansion",
"methods",
".",
"This",
"paper",
"presents",
"experiments",
"with",
"several",
"feature",
"selection",
"methods",
"used",
"individually",
"and",
"in",
"combination",
".",
"We",
"show",
"that",
"documents",
"retrieved",
"using",
"the",
"cluster-based",
"approach",
"are",
"inherently",
"different",
"than",
"documents",
"retrieved",
"using",
"existing",
"methods",
"and",
"provide",
"a",
"higher",
"data",
"diversity",
"to",
"answers",
"extractors",
"."
] |
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"This",
"research",
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"and",
"evaluates",
"scoring",
"and",
"assessment",
"methods",
"for",
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"Reality",
"(VR)",
"training",
"simulators.",
"VR",
"simulators",
"capture",
"detailed",
"n-dimensional",
"human",
"motion",
"data",
"which",
"is",
"useful",
"for",
"performance",
"analysis.",
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"made",
"medical",
"haptic",
"VR",
"training",
"simulators",
"were",
"developed",
"and",
"used",
"to",
"record",
"data",
"from",
"271",
"trainees",
"of",
"multiple",
"clinical",
"experience",
"levels.",
"DTW",
"Multivariate",
"Prototyping",
"(DTW",
"-MP)",
"is",
"proposed.",
"VR",
"data",
"was",
"classified",
"as",
"Novice,",
"Intermediate",
"or",
"Expert.",
"Accuracy",
"of",
"algorithms",
"applied",
"for",
"time-series",
"classification",
"were:",
"dynamic",
"time",
"warping",
"1-nearest",
"neighbor",
"(DTW",
"-1NN)",
"60%,",
"nearest",
"centroid",
"SoftDTW",
"classification",
"77.5%,",
"Deep",
"Learning:",
"ResNet",
"85%,",
"FCN",
"75%,",
"CNN",
"72.50%",
"and",
"MCDCNN",
"28.5%.",
"Expert",
"VR",
"data",
"recordings",
"can",
"be",
"used",
"for",
"guidance",
"of",
"novices.",
"Assessment",
"feedback",
"can",
"help",
"trainees",
"to",
"improve",
"skills",
"and",
"consistency.",
"Motion",
"analysis",
"can",
"identify",
"different",
"techniques",
"used",
"by",
"individuals.",
"Mistakes",
"can",
"be",
"detected",
"dynamically",
"in",
"real-time,",
"raising",
"alarms",
"to",
"prevent",
"injuries."
] |
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[
"Contextual",
"word-representations",
"became",
"a",
"standard",
"in",
"modern",
"natural",
"language",
"processing",
"systems.",
"These",
"models",
"use",
"subword",
"tokenization",
"to",
"handle",
"large",
"vocabularies",
"and",
"unknown",
"words.",
"Word-level",
"usage",
"of",
"such",
"systems",
"requires",
"a",
"way",
"of",
"pooling",
"multiple",
"subwords",
"that",
"correspond",
"to",
"a",
"single",
"word.",
"In",
"this",
"paper",
"we",
"investigate",
"how",
"the",
"choice",
"of",
"subword",
"pooling",
"affects",
"the",
"downstream",
"performance",
"on",
"three",
"tasks:",
"morphological",
"probing,",
"POS",
"tagging",
"and",
"NER",
",",
"in",
"9",
"typologically",
"diverse",
"languages.",
"We",
"compare",
"these",
"in",
"two",
"massively",
"multilingual",
"models,",
"mBERT",
"and",
"XLM-RoBERTa.",
"For",
"morphological",
"tasks,",
"the",
"widely",
"used",
"{`}choose",
"the",
"first",
"subword{'}",
"is",
"the",
"worst",
"strategy",
"and",
"the",
"best",
"results",
"are",
"obtained",
"by",
"using",
"attention",
"over",
"the",
"subwords.",
"For",
"POS",
"tagging",
"both",
"of",
"these",
"strategies",
"perform",
"poorly",
"and",
"the",
"best",
"choice",
"is",
"to",
"use",
"a",
"small",
"LSTM",
"over",
"the",
"subwords.",
"The",
"same",
"strategy",
"works",
"best",
"for",
"NER",
"and",
"we",
"show",
"that",
"mBERT",
"is",
"better",
"than",
"XLM-RoBERTa",
"in",
"all",
"9",
"languages.",
"We",
"publicly",
"release",
"all",
"code,",
"data",
"and",
"the",
"full",
"result",
"tables",
"at",
"https://github.com/juditacs/subword-choice",
"."
] |
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[
"Neural",
"Architecture",
"Search",
"(NAS)",
"has",
"been",
"explosively",
"studied",
"to",
"automate",
"the",
"discovery",
"of",
"top-performer",
"neural",
"networks.",
"Current",
"works",
"require",
"heavy",
"training",
"of",
"supernet",
"or",
"intensive",
"architecture",
"evaluations,",
"thus",
"suffering",
"from",
"heavy",
"resource",
"consumption",
"and",
"often",
"incurring",
"search",
"bias",
"due",
"to",
"truncated",
"training",
"or",
"approximations.",
"Can",
"we",
"select",
"the",
"best",
"neural",
"architectures",
"without",
"involving",
"any",
"training",
"and",
"eliminate",
"a",
"drastic",
"portion",
"of",
"the",
"search",
"cost?",
"We",
"provide",
"an",
"affirmative",
"answer,",
"by",
"proposing",
"a",
"novel",
"framework",
"called",
"training-free",
"neural",
"architecture",
"search",
"(TE-NAS).",
"TE-NAS",
"ranks",
"architectures",
"by",
"analyzing",
"the",
"spectrum",
"of",
"the",
"neural",
"tangent",
"kernel",
"(NTK)",
"and",
"the",
"number",
"of",
"linear",
"regions",
"in",
"the",
"input",
"space.",
"Both",
"are",
"motivated",
"by",
"recent",
"theory",
"advances",
"in",
"deep",
"networks",
"and",
"can",
"be",
"computed",
"without",
"any",
"training",
"and",
"any",
"label.",
"We",
"show",
"that:",
"-1",
"these",
"two",
"measurements",
"imply",
"the",
"trainability",
"and",
"expressivity",
"of",
"a",
"neural",
"network;",
"-2",
"they",
"strongly",
"correlate",
"with",
"the",
"network's",
"test",
"accuracy.",
"Further",
"on,",
"we",
"design",
"a",
"pruning-based",
"NAS",
"mechanism",
"to",
"achieve",
"a",
"more",
"flexible",
"and",
"superior",
"trade-off",
"between",
"the",
"trainability",
"and",
"expressivity",
"during",
"the",
"search.",
"In",
"NAS-Bench-201",
"and",
"DARTS",
"search",
"spaces,",
"TE-NAS",
"completes",
"high-quality",
"search",
"but",
"only",
"costs",
"0.5",
"and",
"4",
"GPU",
"hours",
"with",
"one",
"1080Ti",
"on",
"CIFAR-10",
"and",
"ImageNet,",
"respectively.",
"We",
"hope",
"our",
"work",
"inspires",
"more",
"attempts",
"in",
"bridging",
"the",
"theoretical",
"findings",
"of",
"deep",
"networks",
"and",
"practical",
"impacts",
"in",
"real",
"NAS",
"applications.",
"Code",
"is",
"available",
"at:",
"https://github.com/VITA-Group/TENAS."
] |
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[
"From",
"face",
"recognition",
"systems",
"installed",
"in",
"phones",
"to",
"self-driving",
"cars,",
"the",
"field",
"of",
"AI",
"is",
"witnessing",
"rapid",
"transformations",
"and",
"is",
"being",
"integrated",
"into",
"our",
"everyday",
"lives",
"at",
"an",
"incredible",
"pace.",
"Any",
"major",
"failure",
"in",
"these",
"system's",
"predictions",
"could",
"be",
"devastating,",
"leaking",
"sensitive",
"information",
"or",
"even",
"costing",
"lives",
"(as",
"in",
"the",
"case",
"of",
"self-driving",
"cars).",
"However,",
"deep",
"neural",
"networks,",
"which",
"form",
"the",
"basis",
"of",
"such",
"systems,",
"are",
"highly",
"susceptible",
"to",
"a",
"specific",
"type",
"of",
"attack,",
"called",
"adversarial",
"attacks.",
"A",
"hacker",
"can,",
"even",
"with",
"bare",
"minimum",
"computation,",
"generate",
"adversarial",
"examples",
"(images",
"or",
"data",
"points",
"that",
"belong",
"to",
"another",
"class,",
"but",
"consistently",
"fool",
"the",
"model",
"to",
"get",
"misclassified",
"as",
"genuine)",
"and",
"crumble",
"the",
"basis",
"of",
"such",
"algorithms.",
"In",
"this",
"paper,",
"we",
"compile",
"and",
"test",
"numerous",
"approaches",
"to",
"defend",
"against",
"such",
"adversarial",
"attacks.",
"Out",
"of",
"the",
"ones",
"explored,",
"we",
"found",
"two",
"effective",
"techniques,",
"namely",
"Dropout",
"and",
"Denoising",
"Autoencoders,",
"and",
"show",
"their",
"success",
"in",
"preventing",
"such",
"attacks",
"from",
"fooling",
"the",
"model.",
"We",
"demonstrate",
"that",
"these",
"techniques",
"are",
"also",
"resistant",
"to",
"both",
"higher",
"noise",
"levels",
"as",
"well",
"as",
"different",
"kinds",
"of",
"adversarial",
"attacks",
"(although",
"not",
"tested",
"against",
"all).",
"We",
"also",
"develop",
"a",
"framework",
"for",
"deciding",
"the",
"suitable",
"defense",
"technique",
"to",
"use",
"against",
"attacks,",
"based",
"on",
"the",
"nature",
"of",
"the",
"application",
"and",
"resource",
"constraints",
"of",
"the",
"Deep",
"Neural",
"Network."
] |
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[
"We",
"describe",
"here",
"the",
"experiments",
"we",
"did",
"for",
"the",
"the",
"news",
"translation",
"shared",
"task",
"of",
"WMT",
"2019",
"We",
"focused",
"on",
"the",
"new",
"German-to-French",
"language",
"direction,",
"and",
"mostly",
"used",
"current",
"standard",
"approaches",
"to",
"develop",
"a",
"Neural",
"Machine",
"Translation",
"system.",
"We",
"make",
"use",
"of",
"the",
"Tensor2Tensor",
"implementation",
"of",
"the",
"Transformer",
"model.",
"After",
"carefully",
"cleaning",
"the",
"data",
"and",
"noting",
"the",
"importance",
"of",
"the",
"good",
"use",
"of",
"recent",
"monolingual",
"data",
"for",
"the",
"task,",
"we",
"obtain",
"our",
"final",
"result",
"by",
"combining",
"the",
"output",
"of",
"a",
"diverse",
"set",
"of",
"trained",
"models",
"through",
"the",
"use",
"of",
"their",
"{``}checkpoint",
"agreement{''}."
] |
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[
"During",
"online",
"decision",
"making",
"in",
"Multi-Armed",
"Bandits",
"(MAB),",
"one",
"needs",
"to",
"conduct",
"inference",
"on",
"the",
"TRUE",
"mean",
"reward",
"of",
"each",
"arm",
"based",
"on",
"data",
"collected",
"so",
"far",
"at",
"each",
"step.",
"However,",
"since",
"the",
"arms",
"are",
"adaptively",
"selected--thereby",
"yielding",
"non-iid",
"data--conducting",
"inference",
"accurately",
"is",
"not",
"straightforward.",
"In",
"particular,",
"sample",
"averaging,",
"which",
"is",
"used",
"in",
"the",
"family",
"of",
"UCB",
"and",
"Thompson",
"sampling",
"(TS",
")",
"algorithms,",
"does",
"not",
"provide",
"a",
"good",
"choice",
"as",
"it",
"suffers",
"from",
"bias",
"and",
"a",
"lack",
"of",
"good",
"statistical",
"properties",
"(e.g.",
"asymptotic",
"normality).",
"Our",
"thesis",
"in",
"this",
"paper",
"is",
"that",
"more",
"sophisticated",
"inference",
"schemes",
"that",
"take",
"into",
"account",
"the",
"adaptive",
"nature",
"of",
"the",
"sequentially",
"collected",
"data",
"can",
"unlock",
"further",
"performance",
"gains,",
"even",
"though",
"both",
"UCB",
"and",
"TS",
"type",
"algorithms",
"are",
"optimal",
"in",
"the",
"worst",
"case.",
"In",
"particular,",
"we",
"propose",
"a",
"variant",
"of",
"TS",
"#NAME?",
"algorithms--which",
"we",
"call",
"doubly",
"adaptive",
"TS",
"#NAME?",
"leverages",
"recent",
"advances",
"in",
"causal",
"inference",
"and",
"adaptively",
"reweights",
"the",
"terms",
"of",
"a",
"doubly",
"robust",
"estimator",
"on",
"the",
"TRUE",
"mean",
"reward",
"of",
"each",
"arm.",
"Through",
"20",
"synthetic",
"domain",
"experiments",
"and",
"a",
"semi-synthetic",
"experiment",
"based",
"on",
"data",
"from",
"an",
"A/B",
"test",
"of",
"a",
"web",
"service,",
"we",
"demonstrate",
"that",
"using",
"an",
"adaptive",
"inferential",
"scheme",
"(while",
"still",
"retaining",
"the",
"exploration",
"efficacy",
"of",
"TS",
")",
"provides",
"clear",
"benefits",
"in",
"online",
"decision",
"making:",
"the",
"proposed",
"DATS",
"algorithm",
"has",
"superior",
"empirical",
"performance",
"to",
"existing",
"baselines",
"(UCB",
"and",
"TS",
")",
"in",
"terms",
"of",
"regret",
"and",
"sample",
"complexity",
"in",
"identifying",
"the",
"best",
"arm.",
"In",
"addition,",
"we",
"also",
"provide",
"a",
"finite-time",
"regret",
"bound",
"of",
"doubly",
"adaptive",
"TS",
"that",
"matches",
"(up",
"to",
"log",
"factors)",
"those",
"of",
"UCB",
"and",
"TS",
"algorithms,",
"thereby",
"establishing",
"that",
"its",
"improved",
"practical",
"benefits",
"do",
"not",
"come",
"at",
"the",
"expense",
"of",
"worst-case",
"suboptimality."
] |
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[
"Understanding",
"expressed",
"sentiment",
"and",
"emotions",
"are",
"two",
"crucial",
"factors",
"in",
"human",
"multimodal",
"language.",
"This",
"paper",
"describes",
"a",
"Transformer",
"#NAME?",
"joint-encoding",
"(TBJE)",
"for",
"the",
"task",
"of",
"Emotion",
"Recognition",
"and",
"Sentiment",
"Analysis.",
"In",
"addition",
"to",
"use",
"the",
"Transformer",
"architecture,",
"our",
"approach",
"relies",
"on",
"a",
"modular",
"co-attention",
"and",
"a",
"glimpse",
"layer",
"to",
"jointly",
"encode",
"one",
"or",
"more",
"modalities.",
"The",
"proposed",
"solution",
"has",
"also",
"been",
"submitted",
"to",
"the",
"ACL20:",
"Second",
"Grand-Challenge",
"on",
"Multimodal",
"Language",
"to",
"be",
"evaluated",
"on",
"the",
"CMU-MOSEI",
"dataset.",
"The",
"code",
"to",
"replicate",
"the",
"presented",
"experiments",
"is",
"open-source:",
"https://github.com/jbdel/MOSEI_UMONS."
] |
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[
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"Generative",
"Networks",
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"their",
"output",
"and",
"latent",
"space",
"are",
"currently",
"trained",
"via",
"Variational",
"Autoencoders",
"(VAE",
"s).",
"In",
"the",
"absence",
"of",
"a",
"known",
"analytical",
"form",
"for",
"the",
"posterior",
"and",
"likelihood",
"expectation,",
"VAE",
"s",
"resort",
"to",
"approximations,",
"including",
"(Amortized)",
"Variational",
"Inference",
"(AVI)",
"and",
"Monte-Carlo",
"(MC)",
"sampling.",
"We",
"exploit",
"the",
"Continuous",
"Piecewise",
"Affine",
"(CPA)",
"property",
"of",
"modern",
"DGNs",
"to",
"derive",
"their",
"posterior",
"and",
"marginal",
"distributions",
"as",
"well",
"as",
"the",
"latter's",
"first",
"moments.",
"These",
"findings",
"enable",
"us",
"to",
"derive",
"an",
"analytical",
"Expectation-Maximization",
"(EM)",
"algorithm",
"that",
"enables",
"gradient-free",
"DGN",
"learning.",
"We",
"demonstrate",
"empirically",
"that",
"EM",
"training",
"of",
"DGNs",
"produces",
"greater",
"likelihood",
"than",
"VAE",
"training.",
"Our",
"findings",
"will",
"guide",
"the",
"design",
"of",
"new",
"VAE",
"AVI",
"that",
"better",
"approximate",
"the",
"TRUE",
"posterior",
"and",
"open",
"avenues",
"to",
"apply",
"standard",
"statistical",
"tools",
"for",
"model",
"comparison,",
"anomaly",
"detection,",
"and",
"missing",
"data",
"imputation."
] |
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[
"The",
"paper",
"presents",
"details",
"of",
"our",
"system",
"in",
"the",
"IWSLT",
"Video",
"Speech",
"Translation",
"evaluation.",
"The",
"system",
"works",
"in",
"a",
"cascade",
"form,",
"which",
"contains",
"three",
"modules:",
"1)",
"A",
"proprietary",
"ASR",
"system.",
"2)",
"A",
"disfluency",
"correction",
"system",
"aims",
"to",
"remove",
"interregnums",
"or",
"other",
"disfluent",
"expressions",
"with",
"a",
"fine-tuned",
"BERT",
"and",
"a",
"series",
"of",
"rule-based",
"algorithms.",
"3)",
"An",
"NMT",
"System",
"based",
"on",
"the",
"Transformer",
"and",
"trained",
"with",
"massive",
"publicly",
"available",
"corpus."
] |
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[
"Named",
"entity",
"recognition",
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"a",
"natural",
"language",
"processing",
"task",
"to",
"recognize",
"and",
"extract",
"spans",
"of",
"text",
"associated",
"with",
"named",
"entities",
"and",
"classify",
"them",
"in",
"semantic",
"Categories.",
"Google",
"BERT",
"is",
"a",
"deep",
"bidirectional",
"language",
"model,",
"pre-trained",
"on",
"large",
"corpora",
"that",
"can",
"be",
"fine-tuned",
"to",
"solve",
"many",
"NLP",
"tasks",
"such",
"as",
"question",
"answering,",
"named",
"entity",
"recognition,",
"part",
"of",
"speech",
"tagging",
"and",
"etc.",
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"this",
"paper,",
"we",
"use",
"the",
"pre-trained",
"deep",
"bidirectional",
"network,",
"BERT",
",",
"to",
"make",
"a",
"model",
"for",
"named",
"entity",
"recognition",
"in",
"Persian.",
"We",
"also",
"compare",
"the",
"results",
"of",
"our",
"model",
"with",
"the",
"previous",
"state",
"of",
"the",
"art",
"results",
"achieved",
"on",
"Persian",
"NER",
".",
"Our",
"evaluation",
"metric",
"is",
"CONLL",
"2003",
"score",
"in",
"two",
"levels",
"of",
"word",
"and",
"phrase.",
"This",
"model",
"achieved",
"second",
"place",
"in",
"NSURL-2019",
"task",
"7",
"competition",
"which",
"associated",
"with",
"NER",
"for",
"the",
"Persian",
"language.",
"our",
"results",
"in",
"this",
"competition",
"are",
"83.5",
"and",
"88.4",
"f1",
"CONLL",
"score",
"respectively",
"in",
"phrase",
"and",
"word",
"level",
"evaluation."
] |
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"A",
"range",
"of",
"research",
"has",
"explored",
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"problem",
"of",
"generating",
"referring",
"expressions",
"that",
"uniquely",
"identify",
"a",
"single",
"entity",
"from",
"the",
"shared",
"context",
".",
"But",
"what",
"about",
"expressions",
"that",
"identify",
"sets",
"of",
"entities",
"?",
"In",
"this",
"paper",
",",
"I",
"adapt",
"recent",
"semantic",
"research",
"on",
"plural",
"descriptions",
"--",
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"covers",
"to",
"abstract",
"collective",
"and",
"distributive",
"readings",
"and",
"using",
"sets",
"of",
"assignments",
"to",
"represent",
"dependencies",
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"references",
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"to",
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"problem",
"for",
"set-identifying",
"expressions",
"that",
"largely",
"mirrors",
"the",
"search",
"problem",
"for",
"singular",
"referring",
"expressions",
".",
"By",
"structuring",
"the",
"search",
"space",
"only",
"in",
"terms",
"of",
"the",
"words",
"that",
"can",
"be",
"added",
"to",
"the",
"description",
",",
"the",
"proposal",
"defuses",
"potential",
"combinatorial",
"explosions",
"that",
"might",
"otherwise",
"arise",
"with",
"reference",
"to",
"sets",
"."
] |
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[
"The",
"Traveling",
"Salesman",
"Problem",
"(TSP)",
"is",
"the",
"most",
"popular",
"and",
"most",
"studied",
"combinatorial",
"problem,",
"starting",
"with",
"von",
"Neumann",
"in",
"1951",
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"has",
"driven",
"the",
"discovery",
"of",
"several",
"optimization",
"techniques",
"such",
"as",
"cutting",
"planes,",
"branch-and-bound,",
"local",
"search,",
"Lagrangian",
"relaxation,",
"and",
"simulated",
"annealing.",
"The",
"last",
"five",
"years",
"have",
"seen",
"the",
"emergence",
"of",
"promising",
"techniques",
"where",
"(graph)",
"neural",
"networks",
"have",
"been",
"capable",
"to",
"learn",
"new",
"combinatorial",
"algorithms.",
"The",
"main",
"question",
"is",
"whether",
"deep",
"learning",
"can",
"learn",
"better",
"heuristics",
"from",
"data,",
"i.e.",
"replacing",
"human-engineered",
"heuristics?",
"This",
"is",
"appealing",
"because",
"developing",
"algorithms",
"to",
"tackle",
"efficiently",
"NP-hard",
"problems",
"may",
"require",
"years",
"of",
"research,",
"and",
"many",
"industry",
"problems",
"are",
"combinatorial",
"by",
"nature.",
"In",
"this",
"work,",
"we",
"propose",
"to",
"adapt",
"the",
"recent",
"successful",
"Transformer",
"architecture",
"originally",
"developed",
"for",
"natural",
"language",
"processing",
"to",
"the",
"combinatorial",
"TSP.",
"Training",
"is",
"done",
"by",
"reinforcement",
"learning,",
"hence",
"without",
"TSP",
"training",
"solutions,",
"and",
"decoding",
"uses",
"beam",
"search.",
"We",
"report",
"improved",
"performances",
"over",
"recent",
"learned",
"heuristics",
"with",
"an",
"optimal",
"gap",
"of",
"0.00%",
"for",
"TSP50",
"and",
"0.39%",
"for",
"TSP100."
] |
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[
"Co-Salient",
"Object",
"Detection",
"(CoSOD)",
"aims",
"at",
"simulating",
"the",
"human",
"visual",
"system",
"to",
"discover",
"the",
"common",
"and",
"salient",
"objects",
"from",
"a",
"group",
"of",
"relevant",
"images.",
"Recent",
"methods",
"typically",
"develop",
"sophisticated",
"deep",
"learning",
"based",
"models",
"have",
"greatly",
"improved",
"the",
"performance",
"of",
"CoSOD",
"task.",
"But",
"there",
"are",
"still",
"two",
"major",
"drawbacks",
"that",
"need",
"to",
"be",
"further",
"addressed,",
"1)",
"sub-optimal",
"inter-image",
"relationship",
"modeling;",
"2)",
"lacking",
"consideration",
"of",
"inter-image",
"separability.",
"In",
"this",
"paper,",
"we",
"propose",
"the",
"Co-Salient",
"Object",
"Detection",
"Transformer",
"(CoSformer)",
"network",
"to",
"capture",
"both",
"salient",
"and",
"common",
"visual",
"patterns",
"from",
"multiple",
"images.",
"By",
"leveraging",
"Transformer",
"architecture,",
"the",
"proposed",
"method",
"address",
"the",
"influence",
"of",
"the",
"input",
"orders",
"and",
"greatly",
"improve",
"the",
"stability",
"of",
"the",
"CoSOD",
"task.",
"We",
"also",
"introduce",
"a",
"novel",
"concept",
"of",
"inter-image",
"separability.",
"We",
"construct",
"a",
"contrast",
"learning",
"scheme",
"to",
"modeling",
"the",
"inter-image",
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"paper,",
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"verify",
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"the",
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"DNNs",
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"Finally,",
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"cross-modal",
"relations.",
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"attention",
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"community.",
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"the",
"human",
"perspective,",
"to",
"answer",
"a",
"visual",
"question,",
"one",
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"read",
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"question",
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"refer",
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"image",
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"generate",
"an",
"answer.",
"This",
"answer",
"will",
"then",
"be",
"checked",
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"the",
"question",
"and",
"image",
"again",
"for",
"the",
"final",
"confirmation.",
"In",
"this",
"paper,",
"we",
"mimic",
"this",
"process",
"and",
"propose",
"a",
"fully",
"attention",
"based",
"VQA",
"architecture.",
"Moreover,",
"an",
"answer-checking",
"module",
"is",
"proposed",
"to",
"perform",
"a",
"unified",
"attention",
"on",
"the",
"jointly",
"answer,",
"question",
"and",
"image",
"representation",
"to",
"update",
"the",
"answer.",
"This",
"mimics",
"the",
"human",
"answer",
"checking",
"process",
"to",
"consider",
"the",
"answer",
"in",
"the",
"context.",
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"answer-checking",
"modules",
"and",
"transferred",
"BERT",
"layers,",
"our",
"model",
"achieves",
"the",
"state-of-the-art",
"accuracy",
"71.57\\%",
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"fewer",
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"Recent",
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"the",
"proposed",
"edits.",
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"same",
"time,",
"advancements",
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"output,",
"which",
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"paper,",
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"up",
"the",
"ante",
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"potential",
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"GEC",
"and",
"offer",
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"strengths",
"and",
"weaknesses.",
"We",
"show",
"that,",
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"line",
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"recent",
"results",
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"other",
"NLP",
"tasks,",
"Transformer",
"architectures",
"achieve",
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"provide",
"a",
"competitive",
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"for",
"future",
"machine",
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"models."
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[
"Classification",
"is",
"an",
"important",
"topic",
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"and",
"machine",
"learning",
"withgreat",
"potential",
"in",
"many",
"real",
"applications.",
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"this",
"paper,",
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"investigate",
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"margin",
"classification",
"methods,",
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"Machine",
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")",
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"thehigh-dimensional,",
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"size",
"data",
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"the",
"imbalanced",
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"unifiedfamily",
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"machines,",
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"FLexible",
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"isproposed,",
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"special",
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"family",
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"and",
"differences",
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"DWD.",
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"the",
"imbalanced",
"data,",
"that",
"is,",
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"with",
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"the",
"minority",
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"SVM",
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"resistant",
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"the",
"imbalanced",
"data",
"issue,",
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"overfits",
"high-dimensional",
"data",
"sets",
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"high-dimensionalsetting,",
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"boundary",
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"ofsample",
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"FLAME",
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"helps",
"to",
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"DWD,",
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"FLAME",
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"are",
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"and",
"real",
"data",
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"are",
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"the",
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] |
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"Emotion",
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"in",
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"essential",
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"empathetic",
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"systems.",
"Existing",
"studies",
"on",
"ERC",
"primarily",
"focus",
"on",
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"context",
"information",
"in",
"a",
"conversation,",
"however,",
"ignoring",
"the",
"differentiated",
"emotional",
"behaviors",
"within",
"and",
"across",
"different",
"modalities.",
"Designing",
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"strategies",
"that",
"fit",
"the",
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"multi-modal",
"emotional",
"behaviors",
"can",
"produce",
"more",
"accurate",
"emotional",
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"Thus,",
"we",
"propose",
"the",
"DialogueTransformer",
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"explore",
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"emotional",
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"and",
"inter-modal",
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"For",
"intra-modal,",
"we",
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"a",
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"Hierarchical",
"Transformer",
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"structures",
"according",
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"differentiated",
"context",
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"within",
"each",
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"For",
"inter-modal,",
"we",
"constitute",
"a",
"novel",
"Multi-Grained",
"Interactive",
"Fusion",
"that",
"applies",
"both",
"neuron-",
"and",
"vector-grained",
"feature",
"interactions",
"to",
"learn",
"the",
"differentiated",
"contributions",
"across",
"all",
"modalities.",
"Experimental",
"results",
"show",
"that",
"DialogueTRM",
"outperforms",
"the",
"state-of-the-art",
"by",
"a",
"significant",
"margin",
"on",
"three",
"benchmark",
"datasets."
] |
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"model,",
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"attack",
"vectors,",
"and",
"securing",
"the",
"machine",
"learning",
"models",
"after",
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"This",
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"for",
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"each",
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"post",
"deployment",
"is",
"called",
"the",
"BAD",
"(Build,",
"Attack,",
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"Defend)",
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"Two",
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"the",
"adversarial",
"life",
"cycle",
"for",
"a",
"black",
"box",
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"As",
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"the",
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"Toxic",
"Bias",
"dataset",
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"report,",
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"As",
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"surface",
"demonstrated",
"in",
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"preventable.",
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"for",
"securing",
"a",
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"learning",
"model",
"in",
"a",
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[
"In",
"this",
"paper,",
"Object",
"Detection",
"and",
"Tracking",
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"events",
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"Stop,",
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"track",
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"in",
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"result,",
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"within",
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"The",
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"the",
"detection",
"capacity",
"of",
"ODTS",
"could",
"be",
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"automatically",
"without",
"any",
"changes",
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"the",
"program",
"codes",
"as",
"the",
"training",
"dataset",
"becomes",
"rich."
] |
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[
"This",
"paper",
"investigates",
"how",
"to",
"realize",
"better",
"and",
"more",
"efficient",
"embedding",
"learning",
"to",
"tackle",
"the",
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"video",
"object",
"segmentation",
"under",
"challenging",
"multi-object",
"scenarios.",
"The",
"state-of-the-art",
"methods",
"learn",
"to",
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"features",
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"single",
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"object",
"and",
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"have",
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"scenarios,",
"consuming",
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"problem,",
"we",
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"with",
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"s",
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"detail,",
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"Thus,",
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"segmentation",
"decoding",
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"objects",
"as",
"efficiently",
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"processing",
"a",
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"For",
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"association,",
"a",
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"Transformer",
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"single-object",
"benchmarks",
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"state-of-the-art",
"competitors",
"on",
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"popular",
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"DAVIS",
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"(83.0%),",
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"2016",
"(91.0%),",
"while",
"keeping",
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"than",
"3X",
"faster",
"multi-object",
"run-time.",
"Meanwhile,",
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"AOT-T",
"can",
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"speed",
"on",
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"above",
"benchmarks.",
"We",
"ranked",
"1st",
"in",
"the",
"3rd",
"Large-scale",
"Video",
"Object",
"Segmentation",
"Challenge.",
"The",
"code",
"will",
"be",
"publicly",
"available",
"at",
"https://github.com/z-x-yang/AOT."
] |
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[
"In",
"this",
"paper",
"we",
"present",
"a",
"new",
",",
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"data-driven",
"method",
"for",
"coreference",
"resolution",
"as",
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",",
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"resolution",
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"the",
"individual",
"languages",
"."
] |
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[
"Within",
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"--",
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"super-resolution,",
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"typicallycall",
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"ConditionalGenerative",
"Adversarial",
"Networks",
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"shown",
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"be",
"highly",
"versatilein",
"learning",
"general",
"image-to-image",
"translations,",
"but",
"have",
"not",
"yet",
"been",
"adaptedacross",
"MIR.",
"In",
"this",
"work,",
"we",
"present",
"an",
"end-to-end",
"supervisable",
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"toperform",
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"aforementioned",
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"tasks,",
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"of",
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"Finally,",
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"we",
"present",
"the",
"first",
"application",
"of",
"GANs",
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"guided",
"instrumentsynthesis."
] |
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[
"Existing",
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"mathematical",
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"language",
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"Network",
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"to",
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"Our",
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"Sinhala",
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"performance",
"on",
"super-resolution",
"tasks",
"at",
"different",
"magnification",
"factors,",
"on",
"faces",
"and",
"natural",
"images.",
"We",
"conduct",
"human",
"evaluation",
"on",
"a",
"standard",
"8X",
"face",
"super-resolution",
"task",
"on",
"CelebA-HQ,",
"comparing",
"with",
"SOTA",
"GAN",
"methods.",
"SR3",
"achieves",
"a",
"fool",
"rate",
"close",
"to",
"50%,",
"suggesting",
"photo-realistic",
"outputs,",
"while",
"GANs",
"do",
"not",
"exceed",
"a",
"fool",
"rate",
"of",
"34%.",
"We",
"further",
"show",
"the",
"effectiveness",
"of",
"SR3",
"in",
"cascaded",
"image",
"generation,",
"where",
"generative",
"models",
"are",
"chained",
"with",
"super-resolution",
"models,",
"yielding",
"a",
"competitive",
"FID",
"score",
"of",
"11.3",
"on",
"ImageNet."
] |
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[
"End-to-end",
"Object",
"Detection",
"with",
"Transformer",
"(DETR)proposes",
"to",
"perform",
"object",
"detection",
"with",
"Transformer",
"and",
"achieve",
"comparable",
"performance",
"with",
"two-stage",
"object",
"detection",
"like",
"Faster-RCNN.",
"However,",
"DETR",
"needs",
"huge",
"computational",
"resources",
"for",
"training",
"and",
"inference",
"due",
"to",
"the",
"high-resolution",
"spatial",
"input.",
"In",
"this",
"paper,",
"a",
"novel",
"variant",
"of",
"transformer",
"named",
"Adaptive",
"Clustering",
"Transformer",
"(ACT)",
"has",
"been",
"proposed",
"to",
"reduce",
"the",
"computation",
"cost",
"for",
"high-resolution",
"input.",
"ACT",
"cluster",
"the",
"query",
"features",
"adaptively",
"using",
"Locality",
"Sensitive",
"Hashing",
"(LSH)",
"and",
"ap-proximate",
"the",
"query-key",
"interaction",
"using",
"the",
"prototype-key",
"interaction.",
"ACT",
"can",
"reduce",
"the",
"quadratic",
"O(N2)",
"complexity",
"inside",
"self-attention",
"into",
"O(NK)",
"where",
"K",
"is",
"the",
"number",
"of",
"prototypes",
"in",
"each",
"layer.",
"ACT",
"can",
"be",
"a",
"drop-in",
"module",
"replacing",
"the",
"original",
"self-attention",
"module",
"without",
"any",
"training.",
"ACT",
"achieves",
"a",
"good",
"balance",
"between",
"accuracy",
"and",
"computation",
"cost",
"(FLOPs).",
"The",
"code",
"is",
"available",
"as",
"supplementary",
"for",
"the",
"ease",
"of",
"experiment",
"replication",
"and",
"verification."
] |
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[
"We",
"propose",
"a",
"novel",
"procedure",
"to",
"improve",
"liver",
"and",
"lesion",
"segmentation",
"from",
"CT",
"scans",
"for",
"U-Net",
"based",
"models.",
"Our",
"method",
"extends",
"standard",
"segmentation",
"pipelines",
"to",
"focus",
"on",
"higher",
"target",
"recall",
"or",
"reduction",
"of",
"noisy",
"false-positive",
"predictions,",
"boosting",
"overall",
"segmentation",
"performance.",
"To",
"achieve",
"this,",
"we",
"include",
"segmentation",
"errors",
"into",
"a",
"new",
"learning",
"process",
"appended",
"to",
"the",
"main",
"training",
"setup,",
"allowing",
"the",
"model",
"to",
"find",
"features",
"which",
"explain",
"away",
"previous",
"errors.",
"We",
"evaluate",
"this",
"on",
"semantically",
"distinct",
"architectures:",
"cascaded",
"two-",
"and",
"three-dimensional",
"as",
"well",
"as",
"combined",
"learning",
"setups",
"for",
"multitask",
"segmentation.",
"Liver",
"and",
"lesion",
"segmentation",
"data",
"are",
"provided",
"by",
"the",
"Liver",
"Tumor",
"Segmentation",
"challenge",
"(LiTS),",
"with",
"an",
"increase",
"in",
"dice",
"score",
"of",
"up",
"to",
"2",
"points."
] |
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[
"Epidemiology",
"models",
"are",
"central",
"in",
"understanding",
"and",
"controlling",
"large",
"scale",
"pandemics.",
"Several",
"epidemiology",
"models",
"require",
"simulation-based",
"inference",
"such",
"as",
"Approximate",
"Bayesian",
"Computation",
"(ABC",
")",
"to",
"fit",
"their",
"parameters",
"to",
"observations.",
"ABC",
"inference",
"is",
"highly",
"amenable",
"to",
"efficient",
"hardware",
"acceleration.",
"In",
"this",
"work,",
"we",
"develop",
"parallel",
"ABC",
"inference",
"of",
"a",
"stochastic",
"epidemiology",
"model",
"for",
"COVID-19.",
"The",
"statistical",
"inference",
"framework",
"is",
"implemented",
"and",
"compared",
"on",
"Intel",
"Xeon",
"CPU,",
"NVIDIA",
"Tesla",
"V100",
"GPU",
"and",
"the",
"Graphcore",
"Mk1",
"IPU,",
"and",
"the",
"results",
"are",
"discussed",
"in",
"the",
"context",
"of",
"their",
"computational",
"architectures.",
"Results",
"show",
"that",
"GPUs",
"are",
"4x",
"and",
"IPUs",
"are",
"30x",
"faster",
"than",
"Xeon",
"CPUs.",
"Extensive",
"performance",
"analysis",
"indicates",
"that",
"the",
"difference",
"between",
"IPU",
"and",
"GPU",
"can",
"be",
"attributed",
"to",
"higher",
"communication",
"bandwidth,",
"closeness",
"of",
"memory",
"to",
"compute,",
"and",
"higher",
"compute",
"power",
"in",
"the",
"IPU.",
"The",
"proposed",
"framework",
"scales",
"across",
"16",
"IPUs,",
"with",
"scaling",
"overhead",
"not",
"exceeding",
"8%",
"for",
"the",
"experiments",
"performed.",
"We",
"present",
"an",
"example",
"of",
"our",
"framework",
"in",
"practice,",
"performing",
"inference",
"on",
"the",
"epidemiology",
"model",
"across",
"three",
"countries,",
"and",
"giving",
"a",
"brief",
"overview",
"of",
"the",
"results."
] |
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[
"In",
"this",
"paper,",
"we",
"describe",
"the",
"process",
"of",
"creating",
"a",
"statistical",
"Language",
"Model",
"(LM)",
"for",
"the",
"Tunisian",
"Dialect.",
"Indeed,",
"this",
"work",
"is",
"part",
"of",
"the",
"realization",
"of",
"Automatic",
"Speech",
"Recognition",
"(ASR)",
"system",
"for",
"the",
"Tunisian",
"Railway",
"Transport",
"Network.",
"Since",
"our",
"eld",
"of",
"work",
"has",
"been",
"limited,",
"there",
"are",
"several",
"words",
"with",
"similar",
"behaviors",
"(semantic",
"for",
"example)",
"but",
"they",
"do",
"not",
"have",
"the",
"same",
"appearance",
"probability;",
"their",
"class",
"groupings",
"will",
"therefore",
"be",
"possible.",
"For",
"these",
"reasons,",
"we",
"propose",
"to",
"build",
"an",
"n-class",
"LM",
"that",
"is",
"based",
"mainly",
"on",
"the",
"integration",
"of",
"purely",
"semantic",
"data.",
"Indeed,",
"each",
"class",
"represents",
"an",
"abstraction",
"of",
"similar",
"labels.",
"In",
"order",
"to",
"improve",
"the",
"sequence",
"labeling",
"task,",
"we",
"proposed",
"to",
"use",
"a",
"discriminative",
"algorithm",
"based",
"on",
"the",
"Conditional",
"Random",
"Field",
"(CRF",
")",
"model.",
"To",
"better",
"judge",
"our",
"choice",
"of",
"creating",
"an",
"n-class",
"word",
"model,",
"we",
"compared",
"the",
"created",
"model",
"with",
"the",
"3-gram",
"type",
"model",
"on",
"the",
"same",
"test",
"corpus",
"of",
"evaluation.",
"Additionally,",
"to",
"assess",
"the",
"impact",
"of",
"using",
"the",
"CRF",
"model",
"to",
"perform",
"the",
"semantic",
"labelling",
"task",
"in",
"order",
"to",
"construct",
"semantic",
"classes,",
"we",
"compared",
"the",
"n-class",
"created",
"model",
"with",
"using",
"the",
"CRF",
"in",
"the",
"semantic",
"labelling",
"task",
"and",
"the",
"n-",
"class",
"model",
"without",
"using",
"the",
"CRF",
"in",
"the",
"semantic",
"labelling",
"task.",
"The",
"drawn",
"comparison",
"of",
"the",
"predictive",
"power",
"of",
"the",
"n-class",
"model",
"obtained",
"by",
"applying",
"the",
"CRF",
"model",
"in",
"the",
"semantic",
"labelling",
"is",
"that",
"it",
"is",
"better",
"than",
"the",
"other",
"two",
"models",
"presenting",
"the",
"highest",
"value",
"of",
"its",
"perplexity."
] |
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[
"Graph",
"Neural",
"Networks",
"(GNN)",
"have",
"been",
"extensively",
"used",
"to",
"extract",
"meaningful",
"representations",
"from",
"graph",
"structured",
"data",
"and",
"to",
"perform",
"predictive",
"tasks",
"such",
"as",
"node",
"classification",
"and",
"link",
"prediction.",
"In",
"recent",
"years,",
"there",
"has",
"been",
"a",
"lot",
"of",
"work",
"incorporating",
"edge",
"features",
"along",
"with",
"node",
"features",
"for",
"prediction",
"tasks.",
"One",
"of",
"the",
"main",
"difficulties",
"in",
"using",
"edge",
"features",
"is",
"that",
"they",
"are",
"often",
"handcrafted,",
"hard",
"to",
"get,",
"specific",
"to",
"a",
"particular",
"domain,",
"and",
"may",
"contain",
"redundant",
"information.",
"In",
"this",
"work,",
"we",
"present",
"a",
"framework",
"for",
"creating",
"new",
"edge",
"features,",
"applicable",
"to",
"any",
"domain,",
"via",
"a",
"combination",
"of",
"self-supervised",
"and",
"unsupervised",
"learning.",
"In",
"addition",
"to",
"this,",
"we",
"use",
"Forman-Ricci",
"curvature",
"as",
"an",
"additional",
"edge",
"feature",
"to",
"encapsulate",
"the",
"local",
"geometry",
"of",
"the",
"graph.",
"We",
"then",
"encode",
"our",
"edge",
"features",
"via",
"a",
"Set",
"Transformer",
"and",
"combine",
"them",
"with",
"node",
"features",
"extracted",
"from",
"popular",
"GNN",
"architectures",
"for",
"node",
"classification",
"in",
"an",
"end-to-end",
"training",
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"over",
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"biomarkers",
"and",
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"devices.",
"Quantization",
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"weights",
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"block,",
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"assign",
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"classifiers",
"and",
"two",
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"algorithms",
"for",
"detecting",
"surveillance",
"sound",
"events.",
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"tests",
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"also",
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"had",
"high",
"computational",
"cost",
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"402",
"ms),",
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"use",
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"SGD",
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"seems",
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"be",
"a",
"good",
"alternative",
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"has",
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"to",
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"with",
"quicker",
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"time",
"($\\approx$",
"165",
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"automatic",
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"13.6",
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"verbs",
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"and",
"4",
"%",
"on",
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"sense",
"granularities",
"."
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"data-driven",
"approach",
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"increase",
"on",
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"pickling",
"line.",
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"base",
"algorithm",
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"as",
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"taking",
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"the",
"unexpected",
"volatility",
"of",
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"technological",
"processes.",
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"demonstrate",
"how",
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"Q-Learning",
"can",
"be",
"applied",
"to",
"a",
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"task",
"in",
"a",
"heavy",
"industry,",
"resulting",
"in",
"significant",
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"of",
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"existing",
"automation",
"systems.The",
"problem",
"of",
"input",
"data",
"scarcity",
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"a",
"two-step",
"combination",
"of",
"LSTM",
"and",
"CGAN,",
"which",
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"tabular",
"representation",
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"the",
"data",
"and",
"its",
"sequential",
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"RL",
"training,",
"a",
"necessity",
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"setting,",
"has",
"become",
"possible",
"through",
"the",
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"kinematic",
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"The",
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"such",
"as",
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"driving,",
"intelligent",
"surveillance,",
"robotics,",
"etc.",
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"given",
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"boxes",
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"deep",
"learning",
"method",
"based",
"on",
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"Multi-Head",
"Attention",
"architecture.",
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"a",
"new",
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"of",
"loss",
"function,",
"which",
"takes",
"into",
"account",
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"box",
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"orientation.",
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"model",
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"shows",
"an",
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"terms",
"of",
"robustness",
"over",
"current",
"state-of-the-art",
"end-to-end",
"deep",
"learning",
"models.",
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"also",
"outperforms",
"state-of-the-art",
"object",
"tracking",
"methods",
"on",
"VOT2018",
"dataset",
"in",
"terms",
"of",
"expected",
"average",
"overlap",
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[
"Deep",
"learning",
"models",
"are",
"the",
"current",
"State-of-the-art",
"methodologies",
"towards",
"many",
"real-world",
"problems.",
"However,",
"they",
"need",
"a",
"substantial",
"amount",
"of",
"labeled",
"data",
"to",
"be",
"trained",
"appropriately.",
"Acquiring",
"labeled",
"data",
"can",
"be",
"challenging",
"in",
"some",
"particular",
"domains",
"or",
"less-resourced",
"languages.",
"There",
"are",
"some",
"practical",
"solutions",
"regarding",
"these",
"issues,",
"such",
"as",
"Active",
"Learning",
"and",
"Transfer",
"Learning.",
"Active",
"learning{'}s",
"idea",
"is",
"simple:",
"let",
"the",
"model",
"choose",
"the",
"samples",
"for",
"annotation",
"instead",
"of",
"labeling",
"the",
"whole",
"dataset.",
"This",
"method",
"leads",
"to",
"a",
"more",
"efficient",
"annotation",
"process.",
"Active",
"Learning",
"models",
"can",
"achieve",
"the",
"baseline",
"performance",
"(the",
"accuracy",
"of",
"the",
"model",
"trained",
"on",
"the",
"whole",
"dataset),",
"with",
"a",
"considerably",
"lower",
"amount",
"of",
"labeled",
"data.",
"Several",
"active",
"learning",
"approaches",
"are",
"tested",
"in",
"this",
"work,",
"and",
"their",
"compatibility",
"with",
"Persian",
"is",
"examined",
"using",
"a",
"brand-new",
"sentiment",
"analysis",
"dataset",
"that",
"is",
"also",
"introduced",
"in",
"this",
"work.",
"MirasOpinion,",
"which",
"to",
"our",
"knowledge",
"is",
"the",
"largest",
"Persian",
"sentiment",
"analysis",
"dataset,",
"is",
"crawled",
"from",
"a",
"Persian",
"e-commerce",
"website",
"and",
"annotated",
"using",
"a",
"crowd-sourcing",
"policy.",
"LDA",
"sampling,",
"which",
"is",
"an",
"efficient",
"Active",
"Learning",
"strategy",
"using",
"Topic",
"Modeling,",
"is",
"proposed",
"in",
"this",
"research.",
"Active",
"Learning",
"Strategies",
"have",
"shown",
"promising",
"results",
"in",
"the",
"Persian",
"language,",
"and",
"LDA",
"sampling",
"showed",
"a",
"competitive",
"performance",
"compared",
"to",
"other",
"approaches."
] |
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[
"The",
"field",
"of",
"Grammatical",
"Error",
"Correction",
"(GEC)",
"has",
"produced",
"various",
"systems",
"to",
"deal",
"with",
"focused",
"phenomena",
"or",
"general",
"text",
"editing.",
"We",
"propose",
"an",
"automatic",
"way",
"to",
"combine",
"black-box",
"systems.",
"Our",
"method",
"automatically",
"detects",
"the",
"strength",
"of",
"a",
"system",
"or",
"the",
"combination",
"of",
"several",
"systems",
"per",
"error",
"type,",
"improving",
"precision",
"and",
"recall",
"while",
"optimizing",
"$F$",
"score",
"directly.",
"We",
"show",
"consistent",
"improvement",
"over",
"the",
"best",
"standalone",
"system",
"in",
"all",
"the",
"configurations",
"tested.",
"This",
"approach",
"also",
"outperforms",
"average",
"ensembling",
"of",
"different",
"RNN",
"models",
"with",
"random",
"initializations.",
"In",
"addition,",
"we",
"analyze",
"the",
"use",
"of",
"BERT",
"for",
"GEC",
"-",
"reporting",
"promising",
"results",
"on",
"this",
"end.",
"We",
"also",
"present",
"a",
"spellchecker",
"created",
"for",
"this",
"task",
"which",
"outperforms",
"standard",
"spellcheckers",
"tested",
"on",
"the",
"task",
"of",
"spellchecking.",
"This",
"paper",
"describes",
"a",
"system",
"submission",
"to",
"Building",
"Educational",
"Applications",
"2019",
"Shared",
"Task:",
"Grammatical",
"Error",
"Correction",
".",
"Combining",
"the",
"output",
"of",
"top",
"BEA",
"2019",
"shared",
"task",
"systems",
"using",
"our",
"approach,",
"currently",
"holds",
"the",
"highest",
"reported",
"score",
"in",
"the",
"open",
"phase",
"of",
"the",
"BEA",
"2019",
"shared",
"task,",
"improving",
"F0.5",
"by",
"3.7",
"points",
"over",
"the",
"best",
"result",
"reported."
] |
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[
"We",
"study",
"a",
"search-based",
"paraphrase",
"generation",
"scheme",
"where",
"candidate",
"paraphrases",
"are",
"generated",
"by",
"iterated",
"transformations",
"from",
"the",
"original",
"sentence",
"and",
"evaluated",
"in",
"terms",
"of",
"syntax",
"quality,",
"semantic",
"distance,",
"and",
"lexical",
"distance.",
"The",
"semantic",
"distance",
"is",
"derived",
"from",
"BERT,",
"and",
"the",
"lexical",
"quality",
"is",
"based",
"on",
"GPT2",
"perplexity.",
"To",
"solve",
"this",
"multi-objective",
"search",
"problem,",
"we",
"propose",
"two",
"algorithms:",
"Monte-Carlo",
"Tree",
"Search",
"For",
"Paraphrase",
"Generation",
"(MCPG)",
"and",
"Pareto",
"Tree",
"Search",
"(PTS).",
"We",
"provide",
"an",
"extensive",
"set",
"of",
"experiments",
"on",
"5",
"datasets",
"with",
"a",
"rigorous",
"reproduction",
"and",
"validation",
"for",
"several",
"state-of-the-art",
"paraphrase",
"generation",
"algorithms.",
"These",
"experiments",
"show",
"that,",
"although",
"being",
"non",
"explicitly",
"supervised,",
"our",
"algorithms",
"perform",
"well",
"against",
"these",
"baselines."
] |
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[
"It",
"has",
"been",
"an",
"important",
"task",
"for",
"recommender",
"systems",
"to",
"suggest",
"satisfying",
"activities",
"to",
"a",
"group",
"of",
"users",
"in",
"people's",
"daily",
"social",
"life.",
"The",
"major",
"challenge",
"in",
"this",
"task",
"is",
"how",
"to",
"aggregate",
"personal",
"preferences",
"of",
"group",
"members",
"to",
"infer",
"the",
"decision",
"of",
"a",
"group.",
"Conventional",
"group",
"recommendation",
"methods",
"applied",
"a",
"predefined",
"strategy",
"for",
"preference",
"aggregation.",
"However,",
"these",
"static",
"strategies",
"are",
"too",
"simple",
"to",
"model",
"the",
"real",
"and",
"complex",
"process",
"of",
"group",
"decision-making,",
"especially",
"for",
"occasional",
"groups",
"which",
"are",
"formed",
"ad-hoc.",
"Moreover,",
"group",
"members",
"should",
"have",
"non-uniform",
"influences",
"or",
"weights",
"in",
"a",
"group,",
"and",
"the",
"weight",
"of",
"a",
"user",
"can",
"be",
"varied",
"in",
"different",
"groups.",
"Therefore,",
"an",
"ideal",
"group",
"recommender",
"system",
"should",
"be",
"able",
"to",
"accurately",
"learn",
"not",
"only",
"users'",
"personal",
"preferences",
"but",
"also",
"the",
"preference",
"aggregation",
"strategy",
"from",
"data.",
"In",
"this",
"paper,",
"we",
"propose",
"a",
"novel",
"end-to-end",
"group",
"recommender",
"system",
"named",
"CAGR",
"(short",
"for",
"Centrality",
"Aware",
"Group",
"Recommender\"),",
"which",
"takes",
"Bipartite",
"Graph",
"Embedding",
"Model",
"(BGEM),",
"the",
"self-attention",
"mechanism",
"and",
"Graph",
"Convolutional",
"Networks",
"(GCNs)",
"as",
"basic",
"building",
"blocks",
"to",
"learn",
"group",
"and",
"user",
"representations",
"in",
"a",
"unified",
"way.",
"Specifically,",
"we",
"first",
"extend",
"BGEM",
"to",
"model",
"group-item",
"interactions,",
"and",
"then",
"in",
"order",
"to",
"overcome",
"the",
"limitation",
"and",
"sparsity",
"of",
"the",
"interaction",
"data",
"generated",
"by",
"occasional",
"groups,",
"we",
"propose",
"a",
"self-attentive",
"mechanism",
"to",
"represent",
"groups",
"based",
"on",
"the",
"group",
"members.",
"In",
"addition,",
"to",
"overcome",
"the",
"sparsity",
"issue",
"of",
"user-item",
"interaction",
"data,",
"we",
"leverage",
"the",
"user",
"social",
"networks",
"to",
"enhance",
"user",
"representation",
"learning,",
"obtaining",
"centrality-aware",
"user",
"representations.",
"We",
"create",
"three",
"large-scale",
"benchmark",
"datasets",
"and",
"conduct",
"extensive",
"experiments",
"on",
"them.",
"The",
"experimental",
"results",
"show",
"the",
"superiority",
"of",
"our",
"proposed",
"CAGR",
"by",
"comparing",
"it",
"with",
"state-of-the-art",
"group",
"recommender",
"models."
] |
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[
"Face",
"anti-spoofing",
"(FAS)",
"plays",
"a",
"vital",
"role",
"in",
"face",
"recognition",
"systems.",
"Most",
"state-of-the-art",
"FAS",
"methods",
"1)",
"rely",
"on",
"stacked",
"convolutions",
"and",
"expert-designed",
"network,",
"which",
"is",
"weak",
"in",
"describing",
"detailed",
"fine-grained",
"information",
"and",
"easily",
"being",
"ineffective",
"when",
"the",
"environment",
"varies",
"(e.g.,",
"different",
"illumination),",
"and",
"2)",
"prefer",
"to",
"use",
"long",
"sequence",
"as",
"input",
"to",
"extract",
"dynamic",
"features,",
"making",
"them",
"difficult",
"to",
"deploy",
"into",
"scenarios",
"which",
"need",
"quick",
"response.",
"Here",
"we",
"propose",
"a",
"novel",
"frame",
"level",
"FAS",
"method",
"based",
"on",
"Central",
"Difference",
"Convolution",
"(CDC),",
"which",
"is",
"able",
"to",
"capture",
"intrinsic",
"detailed",
"patterns",
"via",
"aggregating",
"both",
"intensity",
"and",
"gradient",
"information.",
"A",
"network",
"built",
"with",
"CDC,",
"called",
"the",
"Central",
"Difference",
"Convolution",
"al",
"Network",
"(CDCN),",
"is",
"able",
"to",
"provide",
"more",
"robust",
"modeling",
"capacity",
"than",
"its",
"counterpart",
"built",
"with",
"vanilla",
"convolution.",
"Furthermore,",
"over",
"a",
"specifically",
"designed",
"CDC",
"search",
"space,",
"Neural",
"Architecture",
"Search",
"(NAS)",
"is",
"utilized",
"to",
"discover",
"a",
"more",
"powerful",
"network",
"structure",
"(CDCN++),",
"which",
"can",
"be",
"assembled",
"with",
"Multiscale",
"Attention",
"Fusion",
"Module",
"(MAFM)",
"for",
"further",
"boosting",
"performance.",
"Comprehensive",
"experiments",
"are",
"performed",
"on",
"six",
"benchmark",
"datasets",
"to",
"show",
"that",
"1)",
"the",
"proposed",
"method",
"not",
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"achieves",
"superior",
"performance",
"on",
"intra-dataset",
"testing",
"(especially",
"0.20%",
"ACER",
"in",
"Protocol-1",
"of",
"OULU-NPU",
"dataset),",
"2)",
"it",
"also",
"generalizes",
"well",
"on",
"cross-dataset",
"testing",
"(particularly",
"6.50%",
"HTER",
"from",
"CASIA-MFSD",
"to",
"Replay-Attack",
"datasets).",
"The",
"codes",
"are",
"available",
"at",
"\\href{https://github.com/ZitongYu/CDCN}{https://github.com/ZitongYu/CDCN}."
] |
[
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[
"Age",
"estimation",
"is",
"a",
"classic",
"learning",
"problem",
"in",
"computer",
"vision.",
"Many",
"largerand",
"deeper",
"CNNs",
"have",
"been",
"proposed",
"with",
"promising",
"performance,",
"such",
"as",
"AlexNet,VggNet,",
"GoogLeNet",
"and",
"ResNet.",
"However,",
"these",
"models",
"are",
"not",
"practical",
"for",
"theembedded/mobile",
"devices.",
"Recently,",
"MobileNets",
"and",
"ShuffleNets",
"have",
"beenproposed",
"to",
"reduce",
"the",
"number",
"of",
"parameters,",
"yielding",
"lightweight",
"models.However,",
"their",
"representation",
"has",
"been",
"weakened",
"because",
"of",
"the",
"adoption",
"ofdepth-wise",
"separable",
"convolution.",
"In",
"this",
"work,",
"we",
"investigate",
"the",
"limits",
"ofcompact",
"model",
"for",
"small-scale",
"image",
"and",
"propose",
"an",
"extremely",
"Compact",
"yetefficient",
"Cascade",
"Context-based",
"Age",
"Estimation",
"model(C3AE).",
"This",
"modelpossesses",
"only",
"09-Jan",
"and",
"1/2000",
"parameters",
"compared",
"with",
"MobileNets/ShuffleNetsand",
"VggNet,",
"while",
"achieves",
"competitive",
"performance.",
"In",
"particular,",
"we",
"re-defineage",
"estimation",
"problem",
"by",
"two-points",
"representation,",
"which",
"is",
"implemented",
"by",
"acascade",
"model.",
"Moreover,",
"to",
"fully",
"utilize",
"the",
"facial",
"context",
"information,multi-branch",
"CNN",
"network",
"is",
"proposed",
"to",
"aggregate",
"multi-scale",
"context.Experiments",
"are",
"carried",
"out",
"on",
"three",
"age",
"estimation",
"datasets.",
"Thestate-of-the-art",
"performance",
"on",
"compact",
"model",
"has",
"been",
"achieved",
"with",
"arelatively",
"large",
"margin."
] |
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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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[
"Named",
"Entity",
"Recognition",
"(NER",
")",
"for",
"Myanmar",
"Language",
"is",
"essential",
"to",
"Myanmarnatural",
"language",
"processing",
"research",
"work.",
"In",
"this",
"work,",
"NER",
"for",
"Myanmarlanguage",
"is",
"treated",
"as",
"a",
"sequence",
"tagging",
"problem",
"and",
"the",
"effectiveness",
"of",
"deepneural",
"networks",
"on",
"NER",
"for",
"Myanmar",
"language",
"has",
"been",
"investigated.",
"Experimentsare",
"performed",
"by",
"applying",
"deep",
"neural",
"network",
"architectures",
"on",
"syllable",
"levelMyanmar",
"contexts.",
"Very",
"first",
"manually",
"annotated",
"NER",
"corpus",
"for",
"Myanmar",
"languageis",
"also",
"constructed",
"and",
"proposed.",
"In",
"developing",
"our",
"in-house",
"NER",
"corpus,sentences",
"from",
"online",
"news",
"website",
"and",
"also",
"sentences",
"supported",
"fromALT-Parallel-Corpus",
"are",
"also",
"used.",
"This",
"ALT",
"corpus",
"is",
"one",
"part",
"of",
"the",
"AsianLanguage",
"Treebank",
"(ALT)",
"project",
"under",
"ASEAN",
"IVO.",
"This",
"paper",
"contributes",
"thefirst",
"evaluation",
"of",
"neural",
"network",
"models",
"on",
"NER",
"task",
"for",
"Myanmar",
"language.",
"Theexperimental",
"results",
"show",
"that",
"those",
"neural",
"sequence",
"models",
"can",
"producepromising",
"results",
"compared",
"to",
"the",
"baseline",
"CRF",
"model.",
"Among",
"those",
"neuralarchitectures,",
"bidirectional",
"LSTM",
"network",
"added",
"CRF",
"layer",
"above",
"gives",
"thehighest",
"F-score",
"value.",
"This",
"work",
"also",
"aims",
"to",
"discover",
"the",
"effectiveness",
"ofneural",
"network",
"approaches",
"to",
"Myanmar",
"textual",
"processing",
"as",
"well",
"as",
"to",
"promotefurther",
"researches",
"on",
"this",
"understudied",
"language."
] |
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6,
6,
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6,
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6,
6,
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6,
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6,
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6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
7,
6,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
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6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6
] |
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