ACL2018优质论文合集

[{"title":"（37个子文件19.52MB）ACL2018优质论文合集","children":[{"title":"ACL2018优质论文合集","children":[{"title":"百度","children":[{"title":"AdaptationsofROUGEandBLEUtoBetterEvaluateMachineReadingComprehensionTask.pdf <span style='color:#111;'>139.61KB</span>","children":null,"spread":false},{"title":"DuReaderaChineseMachineReadingComprehensionDatasetfromReal-worldApplications.pdf <span style='color:#111;'>481.35KB</span>","children":null,"spread":false},{"title":"JointTrainingofCandidateExtractionandAnswerSelectioninReadingComprehension.pdf <span style='color:#111;'>384.39KB</span>","children":null,"spread":false},{"title":"Multi-PassageMachineReadingComprehensionwithCross-PassageAnswerVerification.pdf <span style='color:#111;'>399.03KB</span>","children":null,"spread":false}],"spread":true},{"title":"理解最先进的模型","children":[{"title":"BreakingNLISystemswithSentencesthatRequireSimpleLexicalInferences.pdf <span 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style='color:#111;'>894.63KB</span>","children":null,"spread":false}],"spread":true},{"title":"用多种语言和资源较少的语言评价","children":[{"title":"Arobustself-learningmethodforfullyunsupervisedcross-lingualmappingsofwordembeddings.pdf <span style='color:#111;'>328.17KB</span>","children":null,"spread":false},{"title":"TriangularArchitectureforRareLanguageTranslation.pdf <span style='color:#111;'>514.64KB</span>","children":null,"spread":false},{"title":"OntheLimitationsofUnsupervisedBilingualDictionaryInduction.pdf <span style='color:#111;'>604.37KB</span>","children":null,"spread":false}],"spread":true},{"title":"强基线","children":[{"title":"UnsupervisedRandomWalkSentenceEmbeddingsAStrongbutSimpleBaseline.pdf <span style='color:#111;'>319.82KB</span>","children":null,"spread":false},{"title":"StrongBaselinesforNeuralSemi-supervisedLearningunderDomainShift.pdf <span style='color:#111;'>491.24KB</span>","children":null,"spread":false},{"title":"BaselineNeedsMoreLoveOnSimpleWord-Embedding-BasedModelsandAssociatedPoolingMechanisms.pdf <span style='color:#111;'>886.62KB</span>","children":null,"spread":false}],"spread":true},{"title":"更难的数据集","children":[{"title":"TheNarrativeQAReadingComprehensionChallenge.pdf <span style='color:#111;'>219.96KB</span>","children":null,"spread":false},{"title":"ConstructingDatasetsforMulti-hopReadingComprehensionAcrossDocuments.pdf <span style='color:#111;'>812.71KB</span>","children":null,"spread":false}],"spread":true},{"title":"改进评估方法","children":[{"title":"TheHitchhiker’sGuidetoTestingStatisticalSignificanceinNaturalLanguageProcessing.pdf <span style='color:#111;'>157.98KB</span>","children":null,"spread":false},{"title":"ImprovingText-to-SQLEvaluationMethodology.pdf <span style='color:#111;'>318.07KB</span>","children":null,"spread":false},{"title":"Thepriceofdebiasingautomaticmetricsinnaturallanguageevaluation.pdf <span style='color:#111;'>1.26MB</span>","children":null,"spread":false}],"spread":true},{"title":"探索模型","children":[{"title":"NumeracyforLanguageModelsEvaluatingandImprovingtheirAbilitytoPredictNumbers.pdf <span style='color:#111;'>2.41MB</span>","children":null,"spread":false},{"title":"Deep-speareAJointNeuralModelofPoeticLanguage,MeterandRhyme.pdf <span style='color:#111;'>548.97KB</span>","children":null,"spread":false},{"title":"LSTMsCanLearnSyntax-SensitiveDependenciesWell,ButModelingStructureMakesThemBetter.pdf <span style='color:#111;'>979.15KB</span>","children":null,"spread":false},{"title":"SomeofThemCanbeGuessed!ExploringtheEffectofLinguisticContextinPredictingQuantifiers.pdf <span style='color:#111;'>374.82KB</span>","children":null,"spread":false},{"title":"WhatyoucancramintoasinglevectorProbingsentenceembeddingsforlinguisticproperties.pdf <span style='color:#111;'>439.70KB</span>","children":null,"spread":false},{"title":"DeepRNNsEncodeSoftHierarchicalSyntax.pdf <span style='color:#111;'>932.71KB</span>","children":null,"spread":false},{"title":"LSTMsExploitLinguisticAttributesofData.pdf <span style='color:#111;'>237.77KB</span>","children":null,"spread":false},{"title":"ExploringSemanticPropertiesofSentenceEmbeddings.pdf <span style='color:#111;'>222.31KB</span>","children":null,"spread":false}],"spread":true},{"title":"对抗性实例","children":[{"title":"HotFlipWhite-BoxAdversarialExamplesforTextClassification.pdf <span style='color:#111;'>112.46KB</span>","children":null,"spread":false},{"title":"TowardsRobustNeuralMachineTranslation.pdf <span style='color:#111;'>383.04KB</span>","children":null,"spread":false},{"title":"AdversarialContrastiveEstimation.pdf <span style='color:#111;'>641.32KB</span>","children":null,"spread":false}],"spread":true},{"title":"腾讯","children":[{"title":"TowardsRobustNeuralMachineTranslation.pdf <span style='color:#111;'>383.04KB</span>","children":null,"spread":false},{"title":"TransformationNetworksforTarget-OrientedSentimentClassification.pdf <span style='color:#111;'>445.94KB</span>","children":null,"spread":false},{"title":"hyperdoc2vecDistributedRepresentationsofHypertextDocuments.pdf <span style='color:#111;'>1.71MB</span>","children":null,"spread":false},{"title":"LearningDomain-SensitiveandSentiment-AwareWordEmbeddings.pdf <span style='color:#111;'>182.40KB</span>","children":null,"spread":false},{"title":"AutomaticArticleCommentingtheTaskandDataset.pdf <span style='color:#111;'>2.63MB</span>","children":null,"spread":false}],"spread":true}],"spread":true}],"spread":true}]