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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 Hits 1 – 20 of 50 1 The Utility and Interplay of Gazetteers and Entity Segmentation for Named Entity Recognition in English ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Agarwal, Oshin; Nenkova, Ani. - : Underline Science Inc., 2021 BASE Show details 2 Interpretability Analysis for Named Entity Recognition to Understand System Predictions and How They Can Improve ... NAACL 2021 2021; Agarwal, Oshin; Nenkova, Ani. - : Underline Science Inc., 2021 BASE Show details 3 The Utility and Interplay of Gazetteers and Entity Segmentation for Named Entity Recognition in English ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Agarwal, Oshin; Nenkova, Ani. - : Underline Science Inc., 2021 BASE Show details 4 Interpretability Analysis for Named Entity Recognition to Understand System Predictions and How They Can Improve ... Agarwal, Oshin; Yang, Yinfei; Wallace, Byron C.; Nenkova, Ani. - : arXiv, 2020 Abstract: Named Entity Recognition systems achieve remarkable performance on domains such as English news. It is natural to ask: What are these models actually learning to achieve this? Are they merely memorizing the names themselves? Or are they capable of interpreting the text and inferring the correct entity type from the linguistic context? We examine these questions by contrasting the performance of several variants of LSTM-CRF architectures for named entity recognition, with some provided only representations of the context as features. We also perform similar experiments for BERT. We find that context representations do contribute to system performance, but that the main factor driving high performance is learning the name tokens themselves. We enlist human annotators to evaluate the feasibility of inferring entity types from the context alone and find that, while people are not able to infer the entity type either for the majority of the errors made by the context-only system, there is some room for ... : Computational Linguistics Journal ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.2004.04564 https://arxiv.org/abs/2004.04564 BASE Hide details 5 Named Person Coreference in English News ... Agarwal, Oshin; Subramanian, Sanjay; Nenkova, Ani. - : arXiv, 2018 BASE Show details 6 Combining Lexical and Syntactic Features for Detecting Content-dense Texts in News ... Yang, Yinfei; Nenkova, Ani. - : arXiv, 2017 BASE Show details 7 Separating Actor-View from Speaker-View Opinion Expressions using Linguistic Features Wiegand, Michael [Verfasser]; Schulder, Marc [Verfasser]; Ruppenhofer, Josef [Verfasser]. - Mannheim : Institut für Deutsche Sprache, Bibliothek, 2016 DNB Subject Category Language Show details 8 Opinion Holder and Target Extraction on Opinion Compounds – A Linguistic Approach Wiegand, Michael [Verfasser]; Bocionek, Christine [Verfasser]; Ruppenhofer, Josef [Verfasser]. - Mannheim : Institut für Deutsche Sprache, Bibliothek, 2016 DNB Subject Category Language Show details 9 Verbose, Laconic or Just Right: A Simple Computational Model of Content Appropriateness under Length Constraints Louis, Annie P; Nenkova, Ani. - : Association for Computational Linguistics, 2014 BASE Show details 10 Prosodic cues for emotion: analysis with discrete characterization of intonation Cao, Houwei; Beňuš, Štefan; Gur, Ruben C.... In: Speech Prosody (2014) BASE Show details 11 Acoustic and Lexical Representations for Affect Prediction in Spontaneous Conversations Cao, Houwei; Savran, Arman; Verma, Ragini. - 2014 BASE Show details 12 Action Unit Models of Facial Expression of Emotion in the Presence of Speech Shah, Miraj; Cooper, David G.; Cao, Houwei. - 2013 BASE Show details 13 Combining Video, Audio and Lexical Indicators of Affect in Spontaneous Conversation via Particle Filtering Savran, Arman; Cao, Houwei; Shah, Miraj. - 2012 BASE Show details 14 Acoustic and Prosodic Correlates of Social Behavior Gravano, Agustín; Levitan, Rivka; Willson, Laura. - : Proceedings of Interspeech 2011, 2011 BASE Show details 15 Information Status Distinctions and Referring Expressions: An Empirical Study of References to People in News Summaries Siddharthan, Advaith; Nenkova, Ani; McKeown, Kathleen. - 2011 BASE Show details 16 Acoustic and Prosodic Correlates of Social Behavior ... Gravano, Agustín; Levitan, Rivka; Willson, Laura. - : Columbia University, 2011 BASE Show details 17 General Versus Specific Sentences: Automatic Identification and Application to Analysis of News Summaries Louis, Annie; Nenkova, Ani In: Technical Reports (CIS) (2011) BASE Show details 18 Information Status Distinctions and Referring Expressions: An Empirical Study of References to People in News Summaries Siddharthan, Advaith; Nenkova, Ani; McKeown, Kathleen In: Departmental Papers (CIS) (2011) BASE Show details 19 Class-level spectral features for emotion recognition Verma, Ragini; Bitouk, Dmitri; Nenkova, Ani In: Speech communication. - Amsterdam [u.a.] : Elsevier 52 (2010) 7, 613-625 BLLDB OLC Linguistik Show details 20 Automatic evaluation of linguistic quality in multi-document summarization Pitler, Emily; Louis, Annie; Nenkova, Ani In: Association for Computational Linguistics. Proceedings of the conference. - Stroudsburg, Penn. : ACL 48 (2010) 1, 544-554 BLLDB Show details Page: 1 2 3

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