NAACL HLT 2015 Author Index
This schedule is interactive, you can click on an author to view that author’s papers. (Unfortunately, the TACL papers that are to be presented at NAACL 2015 are not included in this author index).
A
Omri Abend, University of Edinburgh [369]
369: Lexical Event Ordering with an Edge-Factored Model, by
Somak Aditya, Arizona State University [458]
458: Recognizing Social Constructs from Textual Conversation, by
Apoorv Agarwal, Columbia University [701]
701: Key Female Characters in Film Have More to Talk About Besides Men: Automating the Bechdel Test, by
Eneko Agirre, University of the Basque Country (UPV/EHU) [274, 488]
274: Diamonds in the Rough: Event Extraction from Imperfect Microblog Data, by
488: Random Walks and Neural Network Language Models on Knowledge Bases, by
Malin Ahlberg, University of Gothenburg [647]
647: Paradigm classification in supervised learning of morphology, by
Enrique Alfonseca, Google [317]
317: Idest: Learning a Distributed Representation for Event Patterns, by
Areej Alhothali, University of Waterloo [375]
375: Good News or Bad News: Using Affect Control Theory to Analyze Readers' Reaction Towards News Articles, by
Hannah Alpert-Abrams, University of Texas at Austin [513]
513: Unsupervised Code-Switching for Multilingual Historical Document Transcription, by
Bharat Ram Ambati, ILCC, School of Informatics, University of Edinburgh [136]
136: An Incremental Algorithm for Transition-based CCG Parsing, by
Waleed Ammar, Carnegie Mellon University [205, 534]
205: Constraint-Based Models of Lexical Borrowing, by
534: Unsupervised POS Induction with Word Embeddings, by
Pranav Anand, University of California, Santa Cruz [497]
497: Using Summarization to Discover Argument Facets in Online Idealogical Dialog, by
Daniel Andrade, NEC Research [675]
675: Cross-lingual Text Classification Using Topic-Dependent Word Probabilities, by
Jacob Andreas, UC Berkeley [227]
227: When and why are log-linear models self-normalizing?, by
Shirin Ann Dey, Columbia University [701]
701: Key Female Characters in Film Have More to Talk About Besides Men: Automating the Bechdel Test, by
Emilia Apostolova, BrokerSavant Inc. [167]
167: Digital Leafleting: Extracting Structured Data from Multimedia Online Flyers, by
Raman Arora, Johns Hopkins University [123]
123: Multiview LSA: Representation Learning via Generalized CCA, by
Philip Arthur, Nara Institute of Science and Technology [172]
172: Multi-Target Machine Translation with Multi-Synchronous Context-free Grammars, by
Michael Auli, Facebook [575]
575: A Neural Network Approach to Context-Sensitive Generation of Conversational Responses, by
Michael Auli, Microsoft Research [496]
496: Learning Translation Models from Monolingual Continuous Representations, by
B
Ricardo Baeza-Yates, Yahoo! Labs [223]
223: CASSA: A Context-Aware Synonym Simplification Algorithm, by
Sriramkumar Balasubramanian, [701]
701: Key Female Characters in Film Have More to Talk About Besides Men: Automating the Bechdel Test, by
Timothy Baldwin, The University of Melbourne [145, 293, 558]
145: Exploiting Text and Network Context for Geolocation of Social Media Users, by
293: Accurate Evaluation of Segment-level Machine Translation Metrics, by
558: A Word Embedding Approach to Predicting the Compositionality of Multiword Expressions, by
Tyler Baldwin, IBM Research - Almaden [448]
448: An In-depth Analysis of the Effect of Text Normalization in Social Media, by
Miguel Ballesteros, Universitat Pompeu Fabra [367]
367: Data-driven sentence generation with non-isomorphic trees, by
Paul Baltescu, University of Oxford [697]
697: Pragmatic Neural Language Modelling in Machine Translation, by
Mohit Bansal, Toyota Technological Institute at Chicago [631]
631: Deep Multilingual Correlation for Improved Word Embeddings, by
Chitta Baral, Arizona State University [458]
458: Recognizing Social Constructs from Textual Conversation, by
Marco Baroni, University of Trento [281, 356]
281: So similar and yet incompatible: Toward the automated identification of semantically compatible words, by
356: Combining Language and Vision with a Multimodal Skip-gram Model, by
Loïc Barrault, LIUM, University of Le Mans [262]
262: Continuous Adaptation to User Feedback for Statistical Machine Translation, by
Regina Barzilay, MIT [560, 573]
560: Randomized Greedy Inference for Joint Segmentation, POS Tagging and Dependency Parsing, by
573: High-Order Low-Rank Tensors for Semantic Role Labeling, by
Eric Baumer, Cornell University [351]
351: Testing and Comparing Computational Approaches for Identifying the Language of Framing in Political News, by
Naama Ben-David, University of Toronto [82]
82: Sentence segmentation of aphasic speech, by
Adrian Benton, Johns Hopkins University [664]
664: Entity Linking for Spoken Language, by
Taylor Berg-Kirkpatrick, UC Berkeley [513, 706]
513: Unsupervised Code-Switching for Multilingual Historical Document Transcription, by
706: GPU-Friendly Local Regression for Voice Conversion, by
Jonah Berger, University of Pennsylvania [428]
428: Extracting Human Temporal Orientation from Facebook Language, by
Steven Bethard, University of Alabama at Birmingham [353]
353: Not All Character N-grams Are Created Equal: A Study in Authorship Attribution, by
Pushpak Bhattacharyya, CSE Department, IIT Bombay [197, 532]
197: Unsupervised Most Frequent Sense Detection using Word Embeddings, by
532: Leveraging Small Multilingual Corpora for SMT Using Many Pivot Languages, by
Sudha Bhingardive, CSE Department, IIT Bombay [197]
197: Unsupervised Most Frequent Sense Detection using Word Embeddings, by
Francesca Bianchi, Department of Humanities, University of the Salento [311]
311: Development of the Multilingual Semantic Annotation System, by
Chris Biemann, TU Darmstadt [50]
50: Do Supervised Distributional Methods Really Learn Lexical Inference Relations?, by
Mustafa Bilgic, Illinois Institute of Technology [525]
525: Active Learning with Rationales for Text Classification, by
Alan W Black, Carnegie Mellon University [468]
468: Two/Too Simple Adaptations of Word2Vec for Syntax Problems, by
Kevin Black, Brigham Young University [288]
288: Early Gains Matter: A Case for Preferring Generative over Discriminative Crowdsourcing Models, by
Frédéric Blain, University of Le Mans [262]
262: Continuous Adaptation to User Feedback for Statistical Machine Translation, by
Eduardo Blanco, University of North Texas [531]
531: Inferring Temporally-Anchored Spatial Knowledge from Semantic Roles, by
Phil Blunsom, University of Oxford [697]
697: Pragmatic Neural Language Modelling in Machine Translation, by
Bernd Bohnet, Google [367]
367: Data-driven sentence generation with non-isomorphic trees, by
Fethi Bougares, LIUM- University of Le Mans [262]
262: Continuous Adaptation to User Feedback for Statistical Machine Translation, by
Danny Bouman, University of Maryland [535]
535: Removing the Training Wheels: A Coreference Dataset that Entertains Humans and Challenges Computers, by
Jordan Boyd-Graber, University of Colorado [535, 541]
535: Removing the Training Wheels: A Coreference Dataset that Entertains Humans and Challenges Computers, by
541: Is Your Anchor Going Up or Down? Fast and Accurate Supervised Topic Models, by
Kristy Boyer, North Carolina State University [490]
490: Semantic Grounding in Dialogue for Complex Problem Solving, by
Ted Briscoe, University of Cambridge [169]
169: Towards a standard evaluation method for grammatical error detection and correction, by
Chris Brockett, Microsoft [575]
575: A Neural Network Approach to Context-Sensitive Generation of Conversational Responses, by
Clinton Burkhart, Western Washington University [545]
545: Enhancing Sumerian Lemmatization by Unsupervised Named-Entity Recognition, by
Bill Byrne, University of Cambridge [255, 322]
255: Fast and Accurate Preordering for SMT using Neural Networks, by
322: The Geometry of Statistical Machine Translation, by
C
José G. C. de Souza, University of Trento and Fondazione Bruno Kessler [460]
460: Multitask Learning for Adaptive Quality Estimation of Automatically Transcribed Utterances, by
Chris Callison-Burch, University of Pennsylvania [438]
438: Cost Optimization in Crowdsourcing Translation: Low cost translations made even cheaper, by
José Camacho-Collados, Università La Sapienza, Rome [150]
150: NASARI: a Novel Approach to a Semantically-Aware Representation of Items, by
Claire Cardie, Cornell University [565]
565: Socially-Informed Timeline Generation for Complex Events, by
Taylor Cassidy, Army Research Laboratory [47]
47: Unsupervised Entity Linking with Abstract Meaning Representation, by
Ming-Wei Chang, [617]
617: Inferring Missing Entity Type Instances for Knowledge Base Completion: New Dataset and Methods, by
Eugene Charniak, Brown University [533]
533: A Hybrid Generative/Discriminative Approach To Citation Prediction, by
Wanxiang Che, Harbin Institute of Technology [55]
55: Transition-Based Syntactic Linearization, by
Chen Chen, University of Texas at Dallas [673]
673: Chinese Event Coreference Resolution: An Unsupervised Probabilistic Model Rivaling Supervised Resolvers, by
Jianfu Chen, Stony Brook University [595]
595: Déjà Image-Captions: A Corpus of Expressive Descriptions in Repetition, by
Yun-Nung Chen, Carnegie Mellon University [229]
229: Jointly Modeling Inter-Slot Relations by Random Walk on Knowledge Graphs for Unsupervised Spoken Language Understanding, by
Colin Cherry, NRC [529, 688]
529: The Unreasonable Effectiveness of Word Representations for Twitter Named Entity Recognition, by
688: Inflection Generation as Discriminative String Transduction, by
David Chiang, University of Notre Dame [122, 222]
122: Multi-Task Word Alignment Triangulation for Low-Resource Languages, by
222: Model Invertibility Regularization: Sequence Alignment With or Without Parallel Data, by
Yejin Choi, University of Washington [595]
595: Déjà Image-Captions: A Corpus of Expressive Descriptions in Repetition, by
Kam-Pui Chow, The University of Hong Kong [90]
90: LCCT: A Semi-supervised Model for Sentiment Classification, by
Jason Chuang, IBM [39]
39: TopicCheck: Interactive Alignment for Assessing Topic Model Stability, by
Philipp Cimiano, Semantic Computing Group, CITEC, Bielefeld University [89]
89: Semantic parsing of speech using grammars learned with weak supervision, by
Peter Clark, Allen Institute for AI [661]
661: Learning Knowledge Graphs for Question Answering through Conversational Dialog, by
Peter Clark, Allen Institute for Artificial Intelligence [446]
446: Spinning Straw into Gold: Using Free Text to Train Monolingual Alignment Models for Non-factoid Question Answering, by
Arman Cohan, Georgetown University [582]
582: Matching Citation Text and Cited Spans in Biomedical Literature: a Search-Oriented Approach, by
Shay B. Cohen, [369]
369: Lexical Event Ordering with an Edge-Factored Model, by
Trevor Cohn, University of Melbourne [145]
145: Exploiting Text and Network Context for Geolocation of Social Media Users, by
Carlos A. Colmenares, Google Inc. [278]
278: HEADS: Headline Generation as Sequence Prediction Using an Abstract Feature-Rich Space, by
Paul Cook, University of New Brunswick [558]
558: A Word Embedding Approach to Predicting the Compositionality of Multiword Expressions, by
Ryan Cotterell, Johns Hopkins University [444, 452]
444: Morphological Word-Embeddings, by
452: Penalized Expectation Propagation for Graphical Models over Strings, by
Fabien Cromieres, Kyoto University [532]
532: Leveraging Small Multilingual Corpora for SMT Using Many Pivot Languages, by
Aron Culotta, Illinois Institute of Technology [524]
524: Inferring latent attributes of Twitter users with label regularization, by
Hoang Cuong, ILLC, University of Amsterdam [404]
404: Latent Domain Word Alignment for Heterogeneous Corpora, by
D
Angela D'Egidio, Department of Humanities, University of the Salento [311]
311: Development of the Multilingual Semantic Annotation System, by
Raj Dabre, Kyoto University [532]
532: Leveraging Small Multilingual Corpora for SMT Using Many Pivot Languages, by
Ido Dagan, Bar-Ilan University [50, 56]
50: Do Supervised Distributional Methods Really Learn Lexical Inference Relations?, by
56: Modeling Word Meaning in Context with Substitute Vectors, by
Falavigna Daniele, Fondazione Bruno Kessler [460]
460: Multitask Learning for Adaptive Quality Estimation of Automatically Transcribed Utterances, by
Kareem Darwish, Qatar Computing Research Institute, Qatar Foundation [560]
560: Randomized Greedy Inference for Joint Segmentation, POS Tagging and Dependency Parsing, by
Hal Daumé III, University of Maryland [590]
590: Dialogue focus tracking for zero pronoun resolution, by
Carmen Dayrell, Department of Sociology, Lancaster University [311]
311: Development of the Multilingual Semantic Annotation System, by
Vera Demberg, Saarland University [670]
670: Improving unsupervised vector-space thematic fit evaluation via role-filler prototype clustering, by
Julia Dembowski, University of Saarland [223]
223: CASSA: A Context-Aware Synonym Simplification Algorithm, by
Li Deng, Microsoft Research [176]
176: Representation Learning Using Multi-Task Deep Neural Networks for Semantic Classification and Information Retrieval, by
Lingjia Deng, University of Pittsburgh [650]
650: MPQA 3.0: An Entity/Event-Level Sentiment Corpus, by
Tejaswini Deoskar, University of Edinburgh [136]
136: An Incremental Algorithm for Transition-based CCG Parsing, by
Aliya Deri, USC Information Sciences Institute [32]
32: How to Make a Frenemy: Multitape FSTs for Portmanteau Generation, by
Haibo Ding, [642]
642: Extracting Information about Medication Use from Veterinary Discussions, by
Jesse Dodge, Carnegie Mellon University [76]
76: Retrofitting Word Vectors to Semantic Lexicons, by
Bill Dolan, Microsoft [575]
575: A Neural Network Approach to Context-Sensitive Generation of Conversational Responses, by
Jeff Donahue, UC Berkeley [539]
539: Translating Videos to Natural Language Using Deep Recurrent Neural Networks, by
Yuanzhe Dong, SDL Language Weaver [418]
418: APRO: All-Pairs Ranking Optimization for MT Tuning, by
Dejing Dou, University of Oregon [217]
217: Chain Based RNN for Relation Classification, by
Gabriel Doyle, Stanford University [666]
666: Shared common ground influences information density in microblog texts, by
Mark Dras, Macquarie University [338]
338: Large-Scale Native Language Identification with Cross-Corpus Evaluation, by
Mark Dredze, Johns Hopkins University [206, 550, 664]
206: Combining Word Embeddings and Feature Embeddings for Fine-grained Relation Extraction, by
550: Predicate Argument Alignment using a Global Coherence Model, by
664: Entity Linking for Spoken Language, by
Markus Dreyer, SDL Language Weaver [418]
418: APRO: All-Pairs Ranking Optimization for MT Tuning, by
Kevin Duh, Nara Institute of Science and Technology [172, 176]
172: Multi-Target Machine Translation with Multi-Synchronous Context-free Grammars, by
176: Representation Learning Using Multi-Task Deep Neural Networks for Semantic Classification and Information Retrieval, by
Emmanuel Dupoux, LSCP - EHESS/ENS/CNRS, Paris [453]
453: Prosodic boundary information helps unsupervised word segmentation, by
Emmanuel Dupoux, École des Hautes Etudes en Sciences Sociales, ENS [196]
196: Sign constraints on feature weights improve a joint model of word segmentation and phonology, by
Greg Durrett, UC Berkeley [689]
689: Disfluency Detection with a Semi-Markov Model and Prosodic Features, by
Chris Dyer, Carnegie Mellon University [76, 205, 379, 468, 534]
76: Retrofitting Word Vectors to Semantic Lexicons, by
205: Constraint-Based Models of Lexical Borrowing, by
379: Ontologically Grounded Multi-sense Representation Learning for Semantic Vector Space Models, by
468: Two/Too Simple Adaptations of Word2Vec for Syntax Problems, by
534: Unsupervised POS Induction with Word Embeddings, by
E
Javid Ebrahimi, University of Oregon [217]
217: Chain Based RNN for Relation Classification, by
Johannes Eichstaedt, University of Pennsylvania [428]
428: Extracting Human Temporal Orientation from Facebook Language, by
Jacob Eisenstein, Georgia Institute of Technology [336, 450]
336: Unsupervised Multi-Domain Adaptation with Feature Embeddings, by
450: “You’re Mr. Lebowski, I’m the Dude”: Inducing Address Term Formality in Signed Social Networks, by
Jason Eisner, Johns Hopkins University [452]
452: Penalized Expectation Propagation for Graphical Models over Strings, by
Elisha Elovic, Cornell University [351]
351: Testing and Comparing Computational Approaches for Identifying the Language of Framing in Political News, by
Allyson Ettinger, University of Maryland [590]
590: Dialogue focus tracking for zero pronoun resolution, by
F
Manaal Faruqui, Carnegie Mellon University [76, 103]
76: Retrofitting Word Vectors to Semantic Lexicons, by
103: Multilingual Open Relation Extraction Using Cross-lingual Projection, by
Mariano Felice, University of Cambridge [169]
169: Towards a standard evaluation method for grammatical error detection and correction, by
Paul Felt, Brigham Young University [288]
288: Early Gains Matter: A Case for Preferring Generative over Discriminative Crowdsourcing Models, by
Vanessa Wei Feng, University of Toronto [36]
36: Encoding World Knowledge in the Evaluation of Local Coherence, by
James Ferguson, [689]
689: Disfluency Detection with a Semi-Markov Model and Prosodic Features, by
Katja Filippova, Google [317]
317: Idest: Learning a Distributed Representation for Event Patterns, by
Jeffrey Flanigan, Carnegie Mellon University [567]
567: Toward Abstractive Summarization Using Semantic Representations, by
Markus Forsberg, University of Gothenburg [647]
647: Paradigm classification in supervised learning of morphology, by
Eric Fosler-Lussier, The Ohio State University [586]
586: Corpus-based discovery of semantic intensity scales, by
Jean E. Fox Tree, University of California, Santa Cruz [497]
497: Using Summarization to Discover Argument Facets in Online Idealogical Dialog, by
Michael Frank, Stanford University [666]
666: Shared common ground influences information density in microblog texts, by
Kathleen C. Fraser, University of Toronto [82]
82: Sentence segmentation of aphasic speech, by
Lea Frermann, School of Informatics, University of Edinburgh [261]
261: A Bayesian Model for Joint Learning of Categories and their Features, by
Atsushi Fujita, National Institute of Information and Communications Technology [243]
243: Expanding Paraphrase Lexicons by Exploiting Lexical Variants, by
Alona Fyshe, Carnegie Mellon University [411]
411: A Compositional and Interpretable Semantic Space, by
G
Michel Galley, Microsoft [575]
575: A Neural Network Approach to Context-Sensitive Generation of Conversational Responses, by
Jianfeng Gao, Microsoft [575]
575: A Neural Network Approach to Context-Sensitive Generation of Conversational Responses, by
Jianfeng Gao, Microsoft Research, Redmond [176]
176: Representation Learning Using Multi-Task Deep Neural Networks for Semantic Classification and Information Retrieval, by
Mingkun Gao, University of Pennsylvania [438]
438: Cost Optimization in Crowdsourcing Translation: Low cost translations made even cheaper, by
Dan Garrette, University of Texas at Austin [513]
513: Unsupervised Code-Switching for Multilingual Historical Document Transcription, by
Judith Gaspers, Semantic Computing Group, CITEC, Bielefeld University [89]
89: Semantic parsing of speech using grammars learned with weak supervision, by
Geri Gay, Cornell University [351]
351: Testing and Comparing Computational Approaches for Identifying the Language of Framing in Political News, by
Marjan Ghazvininejad, USC [506]
506: How to Memorize a Random 60-Bit String, by
Luis Gilberto Mateos Ortiz, School of Informatics, University of Edinburgh [238]
238: Learning to Interpret and Describe Abstract Scenes, by
Daniel Gildea, University of Rochester [420]
420: Discriminative Unsupervised Alignment of Natural Language Instructions with Corresponding Video Segments, by
Kevin Gimpel, Toyota Technological Institute at Chicago [631]
631: Deep Multilingual Correlation for Improved Word Embeddings, by
Amir Globerson, Hebrew University [451]
451: Template Kernels for Dependency Parsing, by
Nazli Goharian, Georgetown University [582]
582: Matching Citation Text and Cited Spans in Biomedical Literature: a Search-Oriented Approach, by
Josu Goikoetxea, University of the Basque Country [488]
488: Random Walks and Neural Network Language Models on Knowledge Bases, by
Yoav Goldberg, Bar Ilan University [451]
451: Template Kernels for Dependency Parsing, by
Jacob Goldberger, Bar-Ilan University [56]
56: Modeling Word Meaning in Context with Substitute Vectors, by
Philip John Gorinski, University of Edinburgh [254]
254: Movie Script Summarization as Graph-based Scene Extraction, by
Matthew R. Gormley, Johns Hopkins University [206]
206: Combining Word Embeddings and Feature Embeddings for Fine-grained Relation Extraction, by
Stephan Gouws, Stellenbosch University [228]
228: Simple task-specific bilingual word embeddings, by
Naida Graham, University of Toronto [82]
82: Sentence segmentation of aphasic speech, by
Yvette Graham, Trinity College Dublin [293]
293: Accurate Evaluation of Segment-level Machine Translation Metrics, by
Clayton Greenberg, Saarland University [670]
670: Improving unsupervised vector-space thematic fit evaluation via role-filler prototype clustering, by
Justin Grimmer, Stanford University [39]
39: TopicCheck: Interactive Alignment for Assessing Topic Model Stability, by
Ralph Grishman, New York University [674]
674: Personalized Page Rank for Named Entity Disambiguation, by
Marco Guerini, Trento-Rise [267]
267: Echoes of Persuasion: The Effect of Euphony in Persuasive Communication, by
Anupam Guha, University of Maryland [535]
535: Removing the Training Wheels: A Coreference Dataset that Entertains Humans and Challenges Computers, by
Hongyu Guo, NRC [529]
529: The Unreasonable Effectiveness of Word Representations for Twitter Named Entity Recognition, by
Sonal Gupta, Stanford University [83]
83: Distributed Representations of Words to Guide Bootstrapped Entity Classifiers, by
Adrià de Gispert, SDL Research [255]
255: Fast and Accurate Preordering for SMT using Neural Networks, by
H
Nguyen Ha Vo, Arizona State University [458]
458: Recognizing Social Constructs from Textual Conversation, by
Carolin Haas, Heidelberg University [30]
30: Response-based Learning for Machine Translation of Open-domain Database Queries, by
Michael Haas, Univ Heidelberg [421]
421: Subsentential Sentiment on a Shoestring: A Crosslingual Analysis of Compositional Classification, by
Robbie Haertel, Brigham Young University [288]
288: Early Gains Matter: A Case for Preferring Generative over Discriminative Crowdsourcing Models, by
Gholamreza Haffari, [407]
407: Optimizing Multivariate Performance Measures for Learning Relation Extraction Models, by
Hannaneh Hajishirzi, University of Washington [385, 477, 661]
385: Unediting: Detecting Disfluencies Without Careful Transcripts, by
477: Aligning Sentences from Standard Wikipedia to Simple Wikipedia, by
661: Learning Knowledge Graphs for Question Answering through Conversational Dialog, by
Hany Hassan, Microsoft Research [496]
496: Learning Translation Models from Monolingual Continuous Representations, by
Jenny Hastings, Arizona State University [458]
458: Recognizing Social Constructs from Textual Conversation, by
Amir Hazem, Post-Doc [262]
262: Continuous Adaptation to User Feedback for Statistical Machine Translation, by
Xiaodong He, Microsoft Research [176]
176: Representation Learning Using Multi-Task Deep Neural Networks for Semantic Classification and Information Retrieval, by
Yifan He, New York University [674]
674: Personalized Page Rank for Named Entity Disambiguation, by
James Hearne, Western Washington University [545]
545: Enhancing Sumerian Lemmatization by Unsupervised Named-Entity Recognition, by
Jeffrey Heer, University of Washington [39]
39: TopicCheck: Interactive Alignment for Assessing Topic Model Stability, by
Michael Heilman, Civis Analytics [350]
350: Effective Feature Integration for Automated Short Answer Scoring, by
Ulf Hermjakob, USC/ISI [47]
47: Unsupervised Entity Linking with Abstract Meaning Representation, by
Felix Hieber, Heidelberg University [71]
71: Bag-of-Words Forced Decoding for Cross-Lingual Information Retrieval, by
Tsutomu Hirao, NTT Communication Science Labs. [552]
552: A Dynamic Programming Algorithm for Tree Trimming-based Text Summarization, by
Graeme Hirst, University of Toronto [36, 82]
36: Encoding World Knowledge in the Evaluation of Local Coherence, by
82: Sentence segmentation of aphasic speech, by
Ben Hixon, University of Washington [661]
661: Learning Knowledge Graphs for Question Answering through Conversational Dialog, by
Armin Hoenen, Text Technology Lab Goethe University Frankfurt am Main [34]
34: Lachmannian Archetype Reconstruction for Ancient Manuscript Corpora, by
Jesse Hoey, University of Waterloo [375]
375: Good News or Bad News: Using Affect Control Theory to Analyze Readers' Reaction Towards News Articles, by
Christopher Homan, Rochester Institute of Technology [426]
426: #WhyIStayed, #WhyILeft: Microblogging to Make Sense of Domestic Abuse, by
Dirk Hovy, Center for Language Technology, University of Copenhagen [237]
237: Mining for unambiguous instances to adapt part-of-speech taggers to new domains, by
Eduard Hovy, Carnegie Mellon University [76, 379]
76: Retrofitting Word Vectors to Semantic Lexicons, by
379: Ontologically Grounded Multi-sense Representation Learning for Semantic Vector Space Models, by
Jingwen Huang, Harbin Institute of Technology [36]
36: Encoding World Knowledge in the Evaluation of Local Coherence, by
Jonathan Huang, Google [182]
182: What’s Cookin’? Interpreting Cooking Videos using Text, Speech and Vision, by
Liang Huang, City University of New York (CUNY) [420, 427, 508]
420: Discriminative Unsupervised Alignment of Natural Language Instructions with Corresponding Video Segments, by
427: Type-Driven Incremental Semantic Parsing with Polymorphism, by
508: Shift-Reduce Constituency Parsing with Dynamic Programming and POS Tag Lattice, by
Mans Hulden, University of Colorado Boulder [647]
647: Paradigm classification in supervised learning of morphology, by
William Hwang, University of Washington [477]
477: Aligning Sentences from Standard Wikipedia to Simple Wikipedia, by
I
Gonzalo Iglesias, SDL [255]
255: Fast and Accurate Preordering for SMT using Neural Networks, by
Ryu Iida, National Institute of Information and Communications Technology [125]
125: Incrementally Tracking Reference in Human/Human Dialogue Using Linguistic and Extra-Linguistic Information, by
Daniela Inclezan, Miami University [458]
458: Recognizing Social Constructs from Textual Conversation, by
Ander Intxaurrondo, PhD Candidate [274]
274: Diamonds in the Rough: Event Extraction from Imperfect Microblog Data, by
Pierre Isabelle, National Research Council Canada [243]
243: Expanding Paraphrase Lexicons by Exploiting Lexical Variants, by
Mohit Iyyer, University of Maryland, College Park [535]
535: Removing the Training Wheels: A Coreference Dataset that Entertains Humans and Challenges Computers, by
J
Aren Jansen, Johns Hopkins University HLTCOE [178]
178: Using Zero-Resource Spoken Term Discovery for Ranked Retrieval, by
Peter Jansen, University of Arizona [446]
446: Spinning Straw into Gold: Using Free Text to Train Monolingual Alignment Models for Non-factoid Question Answering, by
Sujay Kumar Jauhar, Carnegie Mellon University [76, 379]
76: Retrofitting Word Vectors to Semantic Lexicons, by
379: Ontologically Grounded Multi-sense Representation Learning for Semantic Vector Space Models, by
Minwoo Jeong, Microsoft [634]
634: Weakly Supervised Slot Tagging with Partially Labeled Sequences from Web Search Click Logs, by
Heng Ji, Rensselaer Polytechnic Institute [8, 47]
8: Why Read if You Can Scan? Trigger Scoping Strategy for Biographical Fact Extraction, by
47: Unsupervised Entity Linking with Abstract Meaning Representation, by
Yangfeng Ji, Georgia Tech [575]
575: A Neural Network Approach to Context-Sensitive Generation of Conversational Responses, by
Lifeng Jin, The Ohio State University [607]
607: A Comparison of Word Similarity Performance Using Explanatory and Non-explanatory Texts, by
Richard Johansson, University of Gothenburg [459]
459: Embedding a Semantic Network in a Word Space, by
Mark Johnson, Macquarie University [136, 196]
136: An Incremental Algorithm for Transition-based CCG Parsing, by
196: Sign constraints on feature weights improve a joint model of word segmentation and phonology, by
Rie Johnson, RJ Research Consulting [73]
73: Effective Use of Word Order for Text Categorization with Convolutional Neural Networks, by
Nicholas Johnston, Google [182]
182: What’s Cookin’? Interpreting Cooking Videos using Text, Speech and Vision, by
Dan Jurafsky, Stanford University [263]
263: Lexicon-Free Conversational Speech Recognition with Neural Networks, by
David Jurgens, McGill University [651]
651: Reserating the awesometastic: An automatic extension of the WordNet taxonomy for novel terms, by
K
Laura Kallmeyer, University of Duesseldorf [224]
224: LR Parsing for LCFRS, by
Shruti Kamath, [701]
701: Key Female Characters in Film Have More to Talk About Besides Men: Automating the Bechdel Test, by
Henry Kautz, University of Rochester [420]
420: Discriminative Unsupervised Alignment of Natural Language Instructions with Corresponding Video Segments, by
Casey Kennington, Bielefeld University [125]
125: Incrementally Tracking Reference in Human/Human Dialogue Using Linguistic and Extra-Linguistic Information, by
Margaret Kern, University of Pennsylvania [428]
428: Extracting Human Temporal Orientation from Facebook Language, by
Daniel Khashabi, University of Illinois, Urbana-Champaign [648]
648: Solving Hard Coreference Problems, by
Ehsan Khoddam, University of Amsterdam [455]
455: Unsupervised Induction of Semantic Roles within a Reconstruction-Error Minimization Framework, by
Young-Bum Kim, Microsoft [634]
634: Weakly Supervised Slot Tagging with Partially Labeled Sequences from Web Search Click Logs, by
Katrin Kirchhoff, University of Washington [207]
207: Morphological Modeling for Machine Translation of English-Iraqi Arabic Spoken Dialogs, by
Svetlana Kiritchenko, NRC [578]
578: Sentiment after Translation: A Case-Study on Arabic Social Media Posts, by
Dan Klein, UC Berkeley [227, 513, 689, 706]
227: When and why are log-linear models self-normalizing?, by
513: Unsupervised Code-Switching for Multilingual Historical Document Transcription, by
689: Disfluency Detection with a Semi-Markov Model and Prosodic Features, by
706: GPU-Friendly Local Regression for Voice Conversion, by
Kevin Knight, USC Information Sciences Institute [32]
32: How to Make a Frenemy: Multitape FSTs for Portmanteau Generation, by
Kevin Knight, USC/ISI [47, 506]
47: Unsupervised Entity Linking with Abstract Meaning Representation, by
506: How to Memorize a Random 60-Bit String, by
Grzegorz Kondrak, University of Alberta [671, 688, 699]
671: Joint Generation of Transliterations from Multiple Representations, by
688: Inflection Generation as Discriminative String Transduction, by
699: English orthography is not "close to optimal", by
Lingpeng Kong, Carnegie Mellon University [591]
591: Transforming Dependencies into Phrase Structures, by
Michal Kosinski, Cambridge University [428]
428: Extracting Human Temporal Orientation from Facebook Language, by
Zornitsa Kozareva, Yahoo! [669]
669: Everyone Likes Shopping! Multi-class Product Categorization for e-Commerce, by
Sebastian Krause, German Research Center for Artificial Intelligence [317]
317: Idest: Learning a Distributed Representation for Event Patterns, by
Vinodh Krishnan, Georgia Institute of Technology [450]
450: “You’re Mr. Lebowski, I’m the Dude”: Inducing Address Term Formality in Signed Social Networks, by
Germán Kruszewski, University of Trento [281]
281: So similar and yet incompatible: Toward the automated identification of semantically compatible words, by
Shankar Kumar, Google [103]
103: Multilingual Open Relation Extraction Using Cross-lingual Projection, by
Sadao Kurohashi, Kyoto University [532]
532: Leveraging Small Multilingual Corpora for SMT Using Many Pivot Languages, by
Polina Kuznetsova, Stony Brook University [595]
595: Déjà Image-Captions: A Corpus of Expressive Descriptions in Repetition, by
L
Albert M. Lai, The Ohio State University [586]
586: Corpus-based discovery of semantic intensity scales, by
Mirella Lapata, School of Informatics, University of Edinburgh [238, 254, 261]
238: Learning to Interpret and Describe Abstract Scenes, by
254: Movie Script Summarization as Graph-based Scene Extraction, by
261: A Bayesian Model for Joint Learning of Categories and their Features, by
Victor Lavrenko, University of Edinburgh [272]
272: Sampling Techniques for Streaming Cross Document Coreference Resolution, by
Angeliki Lazaridou, University of Trento [356]
356: Combining Language and Vision with a Multimodal Skip-gram Model, by
Phong Le, University of Amsterdam [298]
298: Unsupervised Dependency Parsing: Let's Use Supervised Parsers, by
Joohyung Lee, Arizona State University [458]
458: Recognizing Social Constructs from Textual Conversation, by
Patrick Lehnen, RWTH Aachen University [44]
44: A Comparison of Update Strategies for Large-Scale Maximum Expected BLEU Training, by
Tao Lei, MIT [573]
573: High-Order Low-Rank Tensors for Semantic Role Labeling, by
Lori Levin, Carnegie Mellon University [534]
534: Unsupervised POS Induction with Word Embeddings, by
Tomer Levinboim, University of Notre Dame [122, 222]
122: Multi-Task Word Alignment Triangulation for Low-Resource Languages, by
222: Model Invertibility Regularization: Sequence Alignment With or Without Parallel Data, by
Omer Levy, Bar-Ilan University [50]
50: Do Supervised Distributional Methods Really Learn Lexical Inference Relations?, by
Chen Li, University of Texas at Dallas [589, 611]
589: Using External Resources and Joint Learning for Bigram Weighting in ILP-Based Multi-Document Summarization, by
611: Improving Update Summarization via Supervised ILP and Sentence Reranking, by
Chengtao Li, MIT [560]
560: Randomized Greedy Inference for Joint Segmentation, POS Tagging and Dependency Parsing, by
Sujian Li, Peking University [8]
8: Why Read if You Can Scan? Trigger Scoping Strategy for Biographical Fact Extraction, by
Xiaolong Li, North Carolina State University [490]
490: Semantic Grounding in Dialogue for Complex Problem Solving, by
Yunyao Li, IBM Research - Almaden [448]
448: An In-depth Analysis of the Effect of Text Normalization in Social Media, by
Chin-Yew Lin, Microsoft Research Asia [8]
8: Why Read if You Can Scan? Trigger Scoping Strategy for Biographical Fact Extraction, by
Chu-Cheng Lin, Carnegie Mellon University [534]
534: Unsupervised POS Induction with Word Embeddings, by
Yiye Lin, Beijing Institute of Technology [275]
275: Normalized Word Embedding and Orthogonal Transform for Bilingual Word Translation, by
Wang Ling, CMU-LTI & INESC-ID [468]
468: Two/Too Simple Adaptations of Word2Vec for Syntax Problems, by
Marina Litvak, Shamoon College of Engineering [278]
278: HEADS: Headline Generation as Sequence Prediction Using an Abstract Feature-Rich Space, by
Chao Liu, Tsinghua University [275]
275: Normalized Word Embedding and Orthogonal Transform for Bilingual Word Translation, by
Fei Liu, Carnegie Mellon University [567]
567: Toward Abstractive Summarization Using Semantic Representations, by
Qiguang Liu, University of Rochester [420]
420: Discriminative Unsupervised Alignment of Natural Language Instructions with Corresponding Video Segments, by
Ting Liu, Harbin Institute of Technology [36]
36: Encoding World Knowledge in the Evaluation of Local Coherence, by
Xiaodong Liu, Nara Institute of Science and Technology [176]
176: Representation Learning Using Multi-Task Deep Neural Networks for Semantic Classification and Information Retrieval, by
Yang Liu, University of Texas at Dallas [589, 611]
589: Using External Resources and Joint Learning for Bigram Weighting in ILP-Based Multi-Document Summarization, by
611: Improving Update Summarization via Supervised ILP and Sentence Reranking, by
Yi Liu, IMSL Shenzhen Key Lab [282]
282: Clustering Sentences with Density Peaks for Multi-document Summarization, by
Yijia Liu, Research Center for Social Computing and Information Retrieval, Harbin Institute of Technology [55]
55: Transition-Based Syntactic Linearization, by
Yudong Liu, Western Washington University [545]
545: Enhancing Sumerian Lemmatization by Unsupervised Named-Entity Recognition, by
Karen Livescu, TTI-Chicago [631]
631: Deep Multilingual Correlation for Improved Word Embeddings, by
Oier Lopez de Lacalle, University of the Basque Country [274]
274: Diamonds in the Rough: Event Extraction from Imperfect Microblog Data, by
Ang Lu, Tsinghua University [631]
631: Deep Multilingual Correlation for Improved Word Embeddings, by
Weiming Lu, zhejiang university [148]
148: Short Text Understanding by Leveraging Knowledge into Topic Model, by
Ziyu Lu, The University of Hong Kong [90]
90: LCCT: A Semi-supervised Model for Sentiment Classification, by
Bogdan Ludusan, LSCP - EHESS/ENS/CNRS, Paris [453]
453: Prosodic boundary information helps unsupervised word segmentation, by
Barry Lumpkin, Arizona State University [458]
458: Recognizing Social Constructs from Textual Conversation, by
Jeffrey Lund, Brigham Young University [541]
541: Is Your Anchor Going Up or Down? Fast and Accurate Supervised Topic Models, by
Jiebo Luo, University of Rochester [420]
420: Discriminative Unsupervised Alignment of Natural Language Instructions with Corresponding Video Segments, by
Liang Luo, Western Washington University [545]
545: Enhancing Sumerian Lemmatization by Unsupervised Named-Entity Recognition, by
M
Andrew Maas, Stanford University [263]
263: Lexicon-Free Conversational Speech Recognition with Neural Networks, by
Nitin Madnani, Educational Testing Service [350]
350: Effective Feature Integration for Automated Short Answer Scoring, by
Ashesh Mahidadia, School of Computer Science and Engineering, UNSW, Sydney [87]
87: Extractive Summarisation Based on Keyword Profile and Language Model, by
Wolfgang Maier, University of Düsseldorf [224]
224: LR Parsing for LCFRS, by
Shervin Malmasi, Macquarie University [338]
338: Large-Scale Native Language Identification with Cross-Corpus Evaluation, by
Jonathan Malmaud, Google [182]
182: What’s Cookin’? Interpreting Cooking Videos using Text, Speech and Vision, by
Christopher D. Manning, Stanford University [83]
83: Distributed Representations of Words to Guide Bootstrapped Entity Classifiers, by
Amin Mantrach, Yahoo Labs [278]
278: HEADS: Headline Generation as Sequence Prediction Using an Abstract Feature-Rich Space, by
Galen Marchetti, Cornell University [565]
565: Socially-Informed Timeline Generation for Complex Events, by
Eric Martin, School of Computer Science and Engineering, UNSW, Sydney [87]
87: Extractive Summarisation Based on Keyword Profile and Language Model, by
Héctor Martínez Alonso, University of Copenhagen [126, 237]
126: Learning to parse with IAA-weighted loss, by
237: Mining for unambiguous instances to adapt part-of-speech taggers to new domains, by
Nitika Mathur, The University of Melbourne [293]
293: Accurate Evaluation of Segment-level Machine Translation Metrics, by
Ryan McDonald, Google [315]
315: A Linear-Time Transition System for Crossing Interval Trees, by
Oren Melamud, Bar Ilan University [56]
56: Modeling Word Meaning in Context with Substitute Vectors, by
Haitao Mi, IBM Watson Research Center [508]
508: Shift-Reduce Constituency Parsing with Dynamic Programming and POS Tag Lattice, by
Simon Mille, Universitat Pompeu Fabra [367]
367: Data-driven sentence generation with non-isomorphic trees, by
Shin-ichi Minato, Hokkaido University [552]
552: A Dynamic Programming Algorithm for Tree Trimming-based Text Summarization, by
Amita Misra, University of California, Santa Cruz [497]
497: Using Summarization to Discover Argument Facets in Online Idealogical Dialog, by
Margaret Mitchell, Microsoft [575]
575: A Neural Network Approach to Context-Sensitive Generation of Conversational Responses, by
Tom M. Mitchell, Carnegie Mellon University [411]
411: A Compositional and Interpretable Semantic Space, by
Makoto Miwa, Toyota Technological Institute [577]
577: Word Embedding-based Antonym Detection using Thesauri and Distributional Information, by
Saif Mohammad, [578]
578: Sentiment after Translation: A Case-Study on Arabic Social Media Posts, by
Ehsan Mohammady Ardehaly, Illinois Institute of Technology [524]
524: Inferring latent attributes of Twitter users with label regularization, by
Manuel Montes, INAOE [353]
353: Not All Character N-grams Are Created Equal: A Study in Authorship Attribution, by
Raymond Mooney, University of Texas at Austin [539]
539: Translating Videos to Natural Language Using Deep Recurrent Neural Networks, by
Alessandro Moschitti, Qatar Computing Research Institute (prof. in Computer Science at University of Trento) [305, 573]
305: On the Automatic Learning of Sentiment Lexicons, by
573: High-Order Low-Rank Tensors for Semantic Role Labeling, by
Sebastian Muehr, RWTH Aachen University [44]
44: A Comparison of Update Strategies for Large-Scale Maximum Expected BLEU Training, by
Yugo Murawaki, Kyushu University [226]
226: Continuous Space Representations of Linguistic Typology and their Application to Phylogenetic Inference, by
Brian Murphy, Queen's University Belfast [411]
411: A Compositional and Interpretable Semantic Space, by
Kevin Murphy, Google [182]
182: What’s Cookin’? Interpreting Cooking Videos using Text, Speech and Vision, by
Lluís Màrquez, Qatar Computing Research Institute [573]
573: High-Order Low-Rank Tensors for Semantic Role Labeling, by
Thomas Müller, CIS, University of Munich [69]
69: Robust Morphological Tagging with Word Representations, by
Marie-Catherine de Marneffe, The Ohio State University [586]
586: Corpus-based discovery of semantic intensity scales, by
N
Masaaki Nagata, +81-774-93-5235 [116]
116: Empty Category Detection With Joint Context-Label Embeddings, by
Masaaki Nagata, NTT Communication Science Laboratories [552]
552: A Dynamic Programming Algorithm for Tree Trimming-based Text Summarization, by
Ajay Nagesh, IIT Bombay [407]
407: Optimizing Multivariate Performance Measures for Learning Relation Extraction Models, by
Iftekhar Naim, University of Rochester [420]
420: Discriminative Unsupervised Alignment of Natural Language Instructions with Corresponding Video Segments, by
Zaw Naung, Arizona State University [458]
458: Recognizing Social Constructs from Textual Conversation, by
Roberto Navigli, Sapienza University of Rome [150]
150: NASARI: a Novel Approach to a Semantically-Aware Representation of Items, by
Arvind Neelakantan, University of Massachusetts, Amherst [617]
617: Inferring Missing Entity Type Instances for Knowledge Base Completion: New Dataset and Methods, by
Matteo Negri, Fondazione Bruno Kessler [460]
460: Multitask Learning for Adaptive Quality Estimation of Automatically Transcribed Utterances, by
Ani Nenkova, University of Pennsylvania [501, 570]
501: Identification and Characterization of Newsworthy Verbs in World News, by
570: Inducing Lexical Style Properties for Paraphrase and Genre Differentiation, by
Graham Neubig, Nara Institute of Science and Technology [172]
172: Multi-Target Machine Translation with Multi-Synchronous Context-free Grammars, by
Hermann Ney, RWTH Aachen University [44]
44: A Comparison of Update Strategies for Large-Scale Maximum Expected BLEU Training, by
Andrew Ng, Stanford University [263]
263: Lexicon-Free Conversational Speech Recognition with Neural Networks, by
Hwee Tou Ng, National University of Singapore [218]
218: Semi-Supervised Word Sense Disambiguation Using Word Embeddings in General and Specific Domains, by
Vincent Ng, University of Texas at Dallas [673]
673: Chinese Event Coreference Resolution: An Unsupervised Probabilistic Model Rivaling Supervised Resolvers, by
Thang Nguyen, University of Maryland [541]
541: Is Your Anchor Going Up or Down? Fast and Accurate Supervised Topic Models, by
Garrett Nicolai, University of Alberta [688, 699]
688: Inflection Generation as Discriminative String Transduction, by
699: English orthography is not "close to optimal", by
Jian-Yun Nie, Université de Montréal [575]
575: A Neural Network Approach to Context-Sensitive Generation of Conversational Responses, by
Luis Nieto Piña, University of Gothenburg [459]
459: Embedding a Semantic Network in a Word Space, by
Masaaki Nishino, NTT Communication Science Laboratories [552]
552: A Dynamic Programming Algorithm for Tree Trimming-based Text Summarization, by
Benjamin Nye, University of Pennsylvania [501]
501: Identification and Characterization of Newsworthy Verbs in World News, by
O
Douglas Oard, University of Maryland [178]
178: Using Zero-Resource Spoken Term Discovery for Ranked Retrieval, by
Franz Och, Human Longevity, Inc. [100]
100: Unsupervised Morphology Induction Using Word Embeddings, by
Manabu Okumura, Tokyo Institute of Technology [77]
77: Context-Dependent Automatic Response Generation Using Statistical Machine Translation Techniques, by
Masataka Ono, Toyota Technological Institute [577]
577: Word Embedding-based Antonym Detection using Thesauri and Distributional Information, by
Miles Osborne, Bloomberg [272]
272: Sampling Techniques for Streaming Cross Document Coreference Resolution, by
Mari Ostendorf, University of Washington [385, 477]
385: Unediting: Detecting Disfluencies Without Careful Transcripts, by
477: Aligning Sentences from Standard Wikipedia to Simple Wikipedia, by
Yulia Otmakhova, Seoul National University [592]
592: Do We Really Need Lexical Information? Towards a Top-down Approach to Sentiment Analysis of Product Reviews, by
Cecilia Ovesdotter Alm, Rochester Institute of Technology [426]
426: #WhyIStayed, #WhyILeft: Microblogging to Make Sense of Domestic Abuse, by
P
Jiaul Paik, University of Maryland [178]
178: Using Zero-Resource Spoken Term Discovery for Ranked Retrieval, by
Xiaoman Pan, Rensselaer Polytechnic Institute [47]
47: Unsupervised Entity Linking with Abstract Meaning Representation, by
Ankur P. Parikh, Carnegie Mellon University [557]
557: Grounded Semantic Parsing for Complex Knowledge Extraction, by
Gregory Park, University of Pennsylvania [428]
428: Extracting Human Temporal Orientation from Facebook Language, by
Marius Pasca, Google Inc. [232]
232: Interpreting Compound Noun Phrases Using Web Search Queries, by
Joe Pater, University of Massachusetts, Ahmerst [196]
196: Sign constraints on feature weights improve a joint model of word segmentation and phonology, by
Ellie Pavlick, University of Pennsylvania [570]
570: Inducing Lexical Style Properties for Paraphrase and Genre Differentiation, by
Stephan Peitz, RWTH Aachen University [44]
44: A Comparison of Update Strategies for Large-Scale Maximum Expected BLEU Training, by
Haoruo Peng, University of Illinois, Urbana-Champaign [648]
648: Solving Hard Coreference Problems, by
Maria Pershina, New York University [674]
674: Personalized Page Rank for Named Entity Disambiguation, by
Nghia The Pham, University of Trento [356]
356: Combining Language and Vision with a Multimodal Skip-gram Model, by
Scott Piao, School of Computing and Communications, Lancaster University [311]
311: Development of the Multilingual Semantic Annotation System, by
Daniele Pighin, Google Inc [317]
317: Idest: Learning a Distributed Representation for Event Patterns, by
Mohammad Taher Pilehvar, Sapienza University of Rome [150, 651]
150: NASARI: a Novel Approach to a Semantically-Aware Representation of Items, by
651: Reserating the awesometastic: An automatic extension of the WordNet taxonomy for novel terms, by
Emily Pitler, Google, Inc. [315]
315: A Linear-Time Transition System for Crossing Interval Trees, by
Barbara Plank, University of Copenhagen [126, 237]
126: Learning to parse with IAA-weighted loss, by
237: Mining for unambiguous instances to adapt part-of-speech taggers to new domains, by
Francesca Polletta, University of California, Irvine [351]
351: Testing and Comparing Computational Approaches for Identifying the Language of Framing in Political News, by
Hoifung Poon, Microsoft Research [557]
557: Grounded Semantic Parsing for Complex Knowledge Extraction, by
Payam Pourashraf, DePaul University [167]
167: Digital Leafleting: Extracting Structured Data from Multimedia Online Flyers, by
Sameer Pradhan, cemantix.org [306]
306: A Transition-based Algorithm for AMR Parsing, by
Raymond Ptucha, Rochester Institute of Technology [426]
426: #WhyIStayed, #WhyILeft: Microblogging to Make Sense of Domestic Abuse, by
Q
Bing Qin, Harbin Institute of Technology [36, 55]
36: Encoding World Knowledge in the Evaluation of Local Coherence, by
55: Transition-Based Syntactic Linearization, by
Ying Qin, Cornell University [351]
351: Testing and Comparing Computational Approaches for Identifying the Language of Framing in Political News, by
R
Andrew Rabinovich, Google [182]
182: What’s Cookin’? Interpreting Cooking Videos using Text, Speech and Vision, by
Afshin Rahimi, The University of Melbourne [145]
145: Exploiting Text and Network Context for Geolocation of Social Media Users, by
Taraka Rama, University of Gothenburg [142]
142: Automatic cognate identification with gap-weighted string subsequences., by
Ganesh Ramakrishnan, Department of Computer Science and Engineering, Indian Institute of Technology Bombay [407]
407: Optimizing Multivariate Performance Measures for Learning Relation Extraction Models, by
Sudha Rao, University Of Maryland, College Park [590]
590: Dialogue focus tracking for zero pronoun resolution, by
Pushpendre Rastogi, Johns Hopkins University [123]
123: Multiview LSA: Representation Learning via Generalized CCA, by
Vivek Rathod, Google [182]
182: What’s Cookin’? Interpreting Cooking Videos using Text, Speech and Vision, by
Paul Rayson, School of Computing and Communications, Lancaster University [311]
311: Development of the Multilingual Semantic Annotation System, by
Hanumant Redkar, Research Engineer, CSE Department, IIT Bombay [197]
197: Unsupervised Most Frequent Sense Detection using Word Embeddings, by
Luz Rello, Universitat Pompeu Fabra [223]
223: CASSA: A Context-Aware Synonym Simplification Algorithm, by
Steffen Remus, TU Darmstadt [50]
50: Do Supervised Distributional Methods Really Learn Lexical Inference Relations?, by
Philip Resnik, University of Maryland [590]
590: Dialogue focus tracking for zero pronoun resolution, by
Corentin Ribeyre, Univ. Paris Diderot - INRIA - ALPAGE [540]
540: Because Syntax Does Matter: Improving Predicate-Argument Structures Parsing with Syntactic Features, by
Colleen Richey, SRI International [207]
207: Morphological Modeling for Machine Translation of English-Iraqi Arabic Spoken Dialogs, by
Sebastian Riedel, UCL [476]
476: Injecting Logical Background Knowledge into Embeddings for Relation Extraction, by
Stefan Riezler, Heidelberg University [30, 71]
30: Response-based Learning for Machine Translation of Open-domain Database Queries, by
71: Bag-of-Words Forced Decoding for Cross-Lingual Information Retrieval, by
Ellen Riloff, University of Utah [642]
642: Extracting Information about Medication Use from Veterinary Discussions, by
Eric Ringger, Brigham Young University [288, 541]
288: Early Gains Matter: A Case for Preferring Generative over Discriminative Crowdsourcing Models, by
541: Is Your Anchor Going Up or Down? Fast and Accurate Supervised Topic Models, by
Margaret E. Roberts, University of California, San Diego [39]
39: TopicCheck: Interactive Alignment for Assessing Topic Model Stability, by
Elizabeth Rochon, University of Toronto [82]
82: Sentence segmentation of aphasic speech, by
Tim Rocktäschel, University College London [476]
476: Injecting Logical Background Knowledge into Embeddings for Relation Extraction, by
Marcus Rohrbach, ICSI, UC Berkeley [539]
539: Translating Videos to Natural Language Using Deep Recurrent Neural Networks, by
Dan Roth, University of Illinois [384, 648]
384: Unsupervised Sparse Vector Densification for Short Text Similarity, by
648: Solving Hard Coreference Problems, by
Alexander Rudnicky, Carnegie Mellon University [229]
229: Jointly Modeling Inter-Slot Relations by Random Walk on Knowledge Graphs for Unsupervised Spoken Language Understanding, by
Alexander M. Rush, MIT [591]
591: Transforming Dependencies into Phrase Structures, by
Attapol Rutherford, Brandeis University [605]
605: Improving the Inference of Implicit Discourse Relations via Classifying Explicit Discourse Connectives, by
S
Jeffrey Sack, BrokerSavant Inc. [167]
167: Digital Leafleting: Extracting Structured Data from Multimedia Online Flyers, by
Kunihiko Sadamasa, NEC Research [675]
675: Cross-lingual Text Classification Using Topic-Dependent Word Probabilities, by
Norman Sadeh, Carnegie Mellon University [567]
567: Toward Abstractive Summarization Using Semantic Representations, by
Kate Saenko, UMass Lowell [539]
539: Translating Videos to Natural Language Using Deep Recurrent Neural Networks, by
Keisuke Sakaguchi, Johns Hopkins University [350]
350: Effective Feature Integration for Automated Short Answer Scoring, by
Mohammad Salameh, University of Alberta [578]
578: Sentiment after Translation: A Case-Study on Arabic Social Media Posts, by
Bahar Salehi, The University of Melbourne [558]
558: A Word Embedding Approach to Predicting the Compositionality of Multiword Expressions, by
Rashmi Sankepally, University of Maryland [178]
178: Using Zero-Resource Spoken Term Discovery for Ranked Retrieval, by
Maarten Sap, University of Pennsylvania [428]
428: Extracting Human Temporal Orientation from Facebook Language, by
Upendra Sapkota, University of Alabama at Birmingham [353]
353: Not All Character N-grams Are Created Equal: A Study in Authorship Attribution, by
Ruhi Sarikaya, Microsoft [634]
634: Weakly Supervised Slot Tagging with Partially Labeled Sequences from Web Search Click Logs, by
Yutaka Sasaki, Toyota Technological Institute [577]
577: Word Embedding-based Antonym Detection using Thesauri and Distributional Information, by
Ryohei Sasano, Tokyo Institute of Technology [77]
77: Context-Dependent Automatic Response Generation Using Statistical Machine Translation Techniques, by
Asad Sayeed, Saarland University [670]
670: Improving unsupervised vector-space thematic fit evaluation via role-filler prototype clustering, by
Richard Scherl, Monmouth University [458]
458: Recognizing Social Constructs from Textual Conversation, by
David Schlangen, Bielefeld University [125]
125: Incrementally Tracking Reference in Human/Human Dialogue Using Linguistic and Extra-Linguistic Information, by
Nathan Schneider, University of Edinburgh [401]
401: A Corpus and Model Integrating Multiword Expressions and Supersenses, by
Nicolas Schrading, Rochester Institute of Technology [426]
426: #WhyIStayed, #WhyILeft: Microblogging to Make Sense of Domestic Abuse, by
Hinrich Schuetze, CIS, University of Munich [69]
69: Robust Morphological Tagging with Word Representations, by
William Schuler, The Ohio State University [454, 607]
454: Hierarchic syntax improves reading time prediction, by
607: A Comparison of Word Similarity Performance Using Explanatory and Non-explanatory Texts, by
H. Andrew Schwartz, University of Pennsylvania [428]
428: Extracting Human Temporal Orientation from Facebook Language, by
Holger Schwenk, University of Le Mans [262]
262: Continuous Adaptation to User Feedback for Statistical Machine Translation, by
Hinrich Schütze, Center for Information and Language Processing, University of Munich [444]
444: Morphological Word-Embeddings, by
Hinrich Schütze, University of Munich [156, 158]
156: Convolutional Neural Network for Paraphrase Identification, by
158: Discriminative Phrase Embedding for Paraphrase Identification, by
Djamé Seddah, Université Paris Sorbonne (Paris IV) [540]
540: Because Syntax Does Matter: Improving Predicate-Argument Structures Parsing with Syntactic Features, by
Martin Seligman, University of Pennsylvania [428]
428: Extracting Human Temporal Orientation from Facebook Language, by
Kevin Seppi, Brigham Young University [288, 541]
288: Early Gains Matter: A Case for Preferring Generative over Discriminative Crowdsourcing Models, by
541: Is Your Anchor Going Up or Down? Fast and Accurate Supervised Topic Models, by
Aliaksei Severyn, University of Trento [305]
305: On the Automatic Learning of Sentiment Lexicons, by
Manali Sharma, Illinois Institute of Technology [525]
525: Active Learning with Rationales for Text Classification, by
Rebecca Sharp, University of Arizona [446]
446: Spinning Straw into Gold: Using Free Text to Train Monolingual Alignment Models for Non-factoid Question Answering, by
Andrew Shin, Tokyo Institute of Technology [77]
77: Context-Dependent Automatic Response Generation Using Statistical Machine Translation Techniques, by
Hyopil Shin, Seoul National University [592]
592: Do We Really Need Lexical Information? Towards a Top-down Approach to Sentiment Analysis of Product Reviews, by
Chaitanya Shivade, The Ohio State University [586]
586: Corpus-based discovery of semantic intensity scales, by
Luke Shrimpton, University of Edinburgh [272]
272: Sampling Techniques for Streaming Cross Document Coreference Resolution, by
Fabrizio Silvestri, Yahoo Labs [278]
278: HEADS: Headline Generation as Sequence Prediction Using an Abstract Feature-Rich Space, by
Khalil Sima'an, ILLC, University of Amsterdam [404]
404: Latent Domain Word Alignment for Heterogeneous Corpora, by
Dhirendra Singh, CSE Department, IIT Bombay [197]
197: Unsupervised Most Frequent Sense Detection using Word Embeddings, by
Sameer Singh, University of Washington, Seattle [476]
476: Injecting Logical Background Knowledge into Embeddings for Relation Extraction, by
Arne Skjærholt, University of Oslo [126]
126: Learning to parse with IAA-weighted loss, by
Noah A. Smith, Carnegie Mellon University [76, 401, 567, 591]
76: Retrofitting Word Vectors to Semantic Lexicons, by
401: A Corpus and Model Integrating Multiword Expressions and Supersenses, by
567: Toward Abstractive Summarization Using Semantic Representations, by
591: Transforming Dependencies into Phrase Structures, by
Luca Soldaini, Georgetown University [582]
582: Matching Citation Text and Cited Spans in Biomedical Literature: a Search-Oriented Approach, by
Thamar Solorio, UH [353]
353: Not All Character N-grams Are Created Equal: A Study in Authorship Attribution, by
Yangqiu Song, University of Illinois at Urbana-Champaign [384]
384: Unsupervised Sparse Vector Densification for Short Text Similarity, by
Young C. Song, University of Rochester [420]
420: Discriminative Unsupervised Alignment of Natural Language Instructions with Corresponding Video Segments, by
Alessandro Sordoni, Université de Montréal [575]
575: A Neural Network Approach to Context-Sensitive Generation of Conversational Responses, by
Radu Soricut, Google Inc [100]
100: Unsupervised Morphology Induction Using Word Embeddings, by
Aitor Soroa, assistant lecturer [488]
488: Random Walks and Neural Network Language Models on Knowledge Bases, by
Robert Staubs, University of Massachusetts, Ahmerst [196]
196: Sign constraints on feature weights improve a joint model of word segmentation and phonology, by
Mark Steedman, University of Edinburgh [136, 369]
136: An Incremental Algorithm for Transition-based CCG Parsing, by
369: Lexical Event Ordering with an Edge-Factored Model, by
Brandon M. Stewart, Harvard University [39]
39: TopicCheck: Interactive Alignment for Assessing Topic Model Stability, by
David Stillwell, [428]
428: Extracting Human Temporal Orientation from Facebook Language, by
Carlo Strapparava, FBK-irst [267]
267: Echoes of Persuasion: The Effect of Euphony in Persuasive Communication, by
Karl Stratos, Columbia University [634]
634: Weakly Supervised Slot Tagging with Partially Labeled Sequences from Web Search Click Logs, by
Katsuhito Sudoh, NTT Communication Science Laboratories / Kyoto University [116]
116: Empty Category Detection With Joint Context-Label Embeddings, by
Mihai Surdeanu, University of Arizona [274, 446]
274: Diamonds in the Rough: Event Extraction from Imperfect Microblog Data, by
446: Spinning Straw into Gold: Using Free Text to Train Monolingual Alignment Models for Non-factoid Question Answering, by
Dawn M. Sweet, Iowa State University [458]
458: Recognizing Social Constructs from Textual Conversation, by
Gabriel Synnaeve, Ecole Normale Superieure [453]
453: Prosodic boundary information helps unsupervised word segmentation, by
Anders Søgaard, University of Copenhagen [126, 228, 237]
126: Learning to parse with IAA-weighted loss, by
228: Simple task-specific bilingual word embeddings, by
237: Mining for unambiguous instances to adapt part-of-speech taggers to new domains, by
Marten van Schijndel, The Ohio State University [454]
454: Hierarchic syntax improves reading time prediction, by
T
Kaveh Taghipour, National University of Singapore [218]
218: Semi-Supervised Word Sense Disambiguation Using Word Embeddings in General and Specific Domains, by
Hiroya Takamura, Tokyo Institute of Technology [77, 492]
77: Context-Dependent Automatic Response Generation Using Statistical Machine Translation Techniques, by
492: Estimating Numerical Attributes by Bringing Together Fragmentary Clues, by
Partha P. Talukdar, Indian Institute of Science [411]
411: A Compositional and Interpretable Semantic Space, by
Yik-Cheung Tam, SRI International [207]
207: Morphological Modeling for Machine Translation of English-Iraqi Arabic Spoken Dialogs, by
Akihiro Tamura, NEC Research [675]
675: Cross-lingual Text Classification Using Topic-Dependent Word Probabilities, by
Chris Tanner, Brown University [533]
533: A Hybrid Generative/Discriminative Approach To Citation Prediction, by
Hillel Taub-Tabib, The Hebrew University of Jerusalem [451]
451: Template Kernels for Dependency Parsing, by
Sam Thomson, Carnegie Mellon University [567]
567: Toward Abstractive Summarization Using Semantic Representations, by
Dustin Tingley, Harvard University [39]
39: TopicCheck: Interactive Alignment for Assessing Topic Model Stability, by
Ivan Titov, University of Amsterdam [455]
455: Unsupervised Induction of Semantic Roles within a Reconstruction-Error Minimization Framework, by
Takenobu Tokunaga, Tokyo Institute of Technology [125]
125: Incrementally Tracking Reference in Human/Human Dialogue Using Linguistic and Extra-Linguistic Information, by
Kristina Toutanova, Microsoft Research [557]
557: Grounded Semantic Parsing for Complex Knowledge Extraction, by
Isabel Trancoso, INESC-ID [468]
468: Two/Too Simple Adaptations of Word2Vec for Syntax Problems, by
Masaaki Tsuchida, NEC Research [675]
675: Cross-lingual Text Classification Using Topic-Dependent Word Probabilities, by
Jun'ichi Tsujii, Aritificial Intelligence Research Centre at AIST [492]
492: Estimating Numerical Attributes by Bringing Together Fragmentary Clues, by
Yulia Tsvetkov, Carnegie Mellon University [205]
205: Constraint-Based Models of Lexical Borrowing, by
Wenting Tu, The University of Hong Kong [90]
90: LCCT: A Semi-supervised Model for Sentiment Classification, by
Marco Turchi, Fondazione Bruno Kessler [460]
460: Multitask Learning for Adaptive Quality Estimation of Automatically Transcribed Utterances, by
U
Lyle Ungar, University of Pennsylvania [428]
428: Extracting Human Temporal Orientation from Facebook Language, by
V
Rudramurthy V, student [197]
197: Unsupervised Most Frequent Sense Detection using Word Embeddings, by
Benjamin Van Durme, Johns Hopkins University [123, 550]
123: Multiview LSA: Representation Learning via Generalized CCA, by
550: Predicate Argument Alignment using a Global Coherence Model, by
Ashish Vaswani, University of Southern California Information Sciences Institute [222]
222: Model Invertibility Regularization: Sequence Alignment With or Without Parallel Data, by
Alakananda Vempala, University of North Texas [531]
531: Inferring Temporally-Anchored Spatial Knowledge from Semantic Roles, by
Subhashini Venugopalan, The University of Texas at Austin [539]
539: Translating Videos to Natural Language Using Deep Recurrent Neural Networks, by
Yannick Versley, University of Heidelberg [421]
421: Subsentential Sentiment on a Shoestring: A Crosslingual Analysis of Compositional Classification, by
Eric Villemonte de la Clergerie, INRIA [540]
540: Because Syntax Does Matter: Improving Predicate-Argument Structures Parsing with Syntactic Features, by
Duy Vu, University of Lugano [145]
145: Exploiting Text and Network Context for Geolocation of Social Media Users, by
W
Aurelien Waite, University of Cambridge [322]
322: The Geometry of Statistical Machine Translation, by
Marilyn Walker, University of California, Santa Cruz [497]
497: Using Summarization to Discover Argument Facets in Online Idealogical Dialog, by
Chuan Wang, Brandeis University [306]
306: A Transition-based Algorithm for AMR Parsing, by
Dong Wang, Tsinghua University [275]
275: Normalized Word Embedding and Orthogonal Transform for Bilingual Word Translation, by
Lu Wang, Cornell University [565]
565: Socially-Informed Timeline Generation for Complex Events, by
Weiran Wang, Toyota Technological Institute at Chicago [631]
631: Deep Multilingual Correlation for Improved Word Embeddings, by
Wen Wang, SRI International [207]
207: Morphological Modeling for Machine Translation of English-Iraqi Arabic Spoken Dialogs, by
Wenmin Wang, Peking University [282]
282: Clustering Sentences with Density Peaks for Multi-document Summarization, by
William Yang Wang, Carnegie Mellon University [229, 296]
229: Jointly Modeling Inter-Slot Relations by Random Walk on Knowledge Graphs for Unsupervised Spoken Language Understanding, by
296: I Can Has Cheezburger? A Nonparanormal Approach to Combining Textual and Visual Information for Predicting and Generating Popular Meme Descriptions, by
Xun Wang, NTT Communication Science Laboratories [116]
116: Empty Category Detection With Joint Context-Label Embeddings, by
Ye-Yi Wang, Microsoft [176]
176: Representation Learning Using Multi-Task Deep Neural Networks for Semantic Classification and Information Retrieval, by
Leo Wanner, ICREA and Pompeu Fabra University [367]
367: Data-driven sentence generation with non-isomorphic trees, by
David Warren, Stony Brook University [595]
595: Déjà Image-Captions: A Corpus of Expressive Descriptions in Repetition, by
Leila Wehbe, Carnegie Mellon University [411]
411: A Compositional and Interpretable Semantic Space, by
Baogang Wei, zhejiang university [148]
148: Short Text Understanding by Leveraging Knowledge into Topic Model, by
Evan Weingarten, University of Pennsylvania [428]
428: Extracting Human Temporal Orientation from Facebook Language, by
Rebecca Weiss, Stanford University [39]
39: TopicCheck: Interactive Alignment for Assessing Topic Model Stability, by
Miaomiao Wen, Carnegie Mellon University [296]
296: I Can Has Cheezburger? A Nonparanormal Approach to Combining Textual and Visual Information for Predicting and Generating Popular Meme Descriptions, by
Jerome White, New York University [178]
178: Using Zero-Resource Spoken Term Discovery for Ranked Retrieval, by
Janyce Wiebe, University of Pittsburgh [650]
650: MPQA 3.0: An Entity/Event-Level Sentiment Corpus, by
Travis Wolfe, Johns Hopkins University [550]
550: Predicate Argument Alignment using a Global Coherence Model, by
Clemens Wolff, School of Informatics, University of Edinburgh [238]
238: Learning to Interpret and Describe Abstract Scenes, by
Britta Wrede, Applied Informatics, CITEC, Bielefeld University [89]
89: Semantic parsing of speech using grammars learned with weak supervision, by
Wei Wu, University of Washington [477]
477: Aligning Sentences from Standard Wikipedia to Simple Wikipedia, by
Joern Wuebker, RWTH Aachen University [44]
44: A Comparison of Update Strategies for Large-Scale Maximum Expected BLEU Training, by
X
Yunqing Xia, Tsinghua University [282]
282: Clustering Sentences with Density Peaks for Multi-document Summarization, by
Pengtao Xie, Carnegie Mellon University [521]
521: Incorporating Word Correlation Knowledge into Topic Modeling, by
Ziang Xie, Stanford University [263]
263: Lexicon-Free Conversational Speech Recognition with Neural Networks, by
Chao Xing, Tsinghua University [275]
275: Normalized Word Embedding and Orthogonal Transform for Bilingual Word Translation, by
Eric Xing, Carnegie Mellon University [521]
521: Incorporating Word Correlation Knowledge into Topic Modeling, by
Han Xu, School of Computer Science and Engineering, UNSW, Sydney [87]
87: Extractive Summarisation Based on Keyword Profile and Language Model, by
Huijuan Xu, UMass Lowell [539]
539: Translating Videos to Natural Language Using Deep Recurrent Neural Networks, by
Wei Xu, University of Pennsylvania [438]
438: Cost Optimization in Crowdsourcing Translation: Low cost translations made even cheaper, by
Nianwen Xue, Brandeis University [306, 605]
306: A Transition-based Algorithm for AMR Parsing, by
605: Improving the Inference of Implicit Discourse Relations via Classifying Explicit Discourse Connectives, by
Y
Dezhi Yang, zhejiang university [148]
148: Short Text Understanding by Leveraging Knowledge into Topic Model, by
Diyi Yang, Carnegie Mellon University [521]
521: Incorporating Word Correlation Knowledge into Topic Modeling, by
Min Yang, The University of Hong Kong [90]
90: LCCT: A Semi-supervised Model for Sentiment Classification, by
Shansong Yang, zhejiang university [148]
148: Short Text Understanding by Leveraging Knowledge into Topic Model, by
Yi Yang, Georgia Institute of Technology [336]
336: Unsupervised Multi-Domain Adaptation with Feature Embeddings, by
Lei Yao, University of Alberta [671]
671: Joint Generation of Transliterations from Multiple Representations, by
Liang Yao, zhejiang university [148]
148: Short Text Understanding by Leveraging Knowledge into Topic Model, by
Norihito Yasuda, ERATO Minato Discrete Structure Manipulation System Project [552]
552: A Dynamic Programming Algorithm for Tree Trimming-based Text Summarization, by
Jieping Ye, Arizona State University [458]
458: Recognizing Social Constructs from Textual Conversation, by
Wenpeng Yin, University of Munich [90, 156, 158]
90: LCCT: A Semi-supervised Model for Sentiment Classification, by
156: Convolutional Neural Network for Paraphrase Identification, by
158: Discriminative Phrase Embedding for Paraphrase Identification, by
Dian Yu, Rensselaer Polytechnic Institute [8]
8: Why Read if You Can Scan? Trigger Scoping Strategy for Biographical Fact Extraction, by
Mo Yu, Harbin Institute of Technology [206]
206: Combining Word Embeddings and Feature Embeddings for Fine-grained Relation Extraction, by
Z
Hamed Zamani, University of Tehran [460]
460: Multitask Learning for Adaptive Quality Estimation of Automatically Transcribed Utterances, by
Victoria Zayats, University of Washington [385]
385: Unediting: Detecting Disfluencies Without Careful Transcripts, by
Muyu Zhang, Harbin Institute of Technology [36]
36: Encoding World Knowledge in the Evaluation of Local Coherence, by
Tong Zhang, Rutgers University [73]
73: Effective Use of Word Order for Text Categorization with Convolutional Neural Networks, by
Yang Zhang, Shenzhen Graduate School,Peking University [282]
282: Clustering Sentences with Density Peaks for Multi-document Summarization, by
Yuan Zhang, MIT [560, 573]
560: Randomized Greedy Inference for Joint Segmentation, POS Tagging and Dependency Parsing, by
573: High-Order Low-Rank Tensors for Semantic Role Labeling, by
Yue Zhang, Singapore University of Technology and Design [55]
55: Transition-Based Syntactic Linearization, by
Kai Zhao, Graduate Center, CUNY [427, 496]
427: Type-Driven Incremental Semantic Parsing with Polymorphism, by
496: Learning Translation Models from Monolingual Continuous Representations, by
Lin Zhao, Bosch North America Research Center [589]
589: Using External Resources and Joint Learning for Bigram Weighting in ILP-Based Multi-Document Summarization, by
Lin Zhao, Research and Technology Center, Robert Bosch LLC [611]
611: Improving Update Summarization via Supervised ILP and Sentence Reranking, by
Jiehan Zheng, Duke University [701]
701: Key Female Characters in Film Have More to Talk About Besides Men: Automating the Bechdel Test, by
Di Zhuang, Illinois Institute of Technology [525]
525: Active Learning with Rationales for Text Classification, by
Willem Zuidema, University of Amsterdam [298]
298: Unsupervised Dependency Parsing: Let's Use Supervised Parsers, by
Ö
Gözde Özbal, FBK-irst [267]
267: Echoes of Persuasion: The Effect of Euphony in Persuasive Communication, by