Annual Meeting of the Association for Computational Linguistics (2016)


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Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

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Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Katrin Erk | Noah A. Smith

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Noise reduction and targeted exploration in imitation learning for Abstract Meaning Representation parsing
James Goodman | Andreas Vlachos | Jason Naradowsky

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Data Recombination for Neural Semantic Parsing
Robin Jia | Percy Liang

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Inferring Logical Forms From Denotations
Panupong Pasupat | Percy Liang

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Language to Logical Form with Neural Attention
Li Dong | Mirella Lapata

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Unsupervised Person Slot Filling based on Graph Mining
Dian Yu | Heng Ji

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A Multi-media Approach to Cross-lingual Entity Knowledge Transfer
Di Lu | Xiaoman Pan | Nima Pourdamghani | Shih-Fu Chang | Heng Ji | Kevin Knight

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Models and Inference for Prefix-Constrained Machine Translation
Joern Wuebker | Spence Green | John DeNero | Saša Hasan | Minh-Thang Luong

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Modeling Coverage for Neural Machine Translation
Zhaopeng Tu | Zhengdong Lu | Yang Liu | Xiaohua Liu | Hang Li

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Improving Neural Machine Translation Models with Monolingual Data
Rico Sennrich | Barry Haddow | Alexandra Birch

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Graph-Based Translation Via Graph Segmentation
Liangyou Li | Andy Way | Qun Liu

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Incremental Acquisition of Verb Hypothesis Space towards Physical World Interaction
Lanbo She | Joyce Chai

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Language Transfer Learning for Supervised Lexical Substitution
Gerold Hintz | Chris Biemann

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Learning the Curriculum with Bayesian Optimization for Task-Specific Word Representation Learning
Yulia Tsvetkov | Manaal Faruqui | Wang Ling | Brian MacWhinney | Chris Dyer

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Pointing the Unknown Words
Caglar Gulcehre | Sungjin Ahn | Ramesh Nallapati | Bowen Zhou | Yoshua Bengio

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Generalized Transition-based Dependency Parsing via Control Parameters
Bernd Bohnet | Ryan McDonald | Emily Pitler | Ji Ma

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A Transition-Based System for Joint Lexical and Syntactic Analysis
Matthieu Constant | Joakim Nivre

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Neural Greedy Constituent Parsing with Dynamic Oracles
Maximin Coavoux | Benoît Crabbé

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Literal and Metaphorical Senses in Compositional Distributional Semantic Models
E.Dario Gutiérrez | Ekaterina Shutova | Tyler Marghetis | Benjamin Bergen

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Idiom Token Classification using Sentential Distributed Semantics
Giancarlo Salton | Robert Ross | John Kelleher

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Adaptive Joint Learning of Compositional and Non-Compositional Phrase Embeddings
Kazuma Hashimoto | Yoshimasa Tsuruoka

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Metaphor Detection with Topic Transition, Emotion and Cognition in Context
Hyeju Jang | Yohan Jo | Qinlan Shen | Michael Miller | Seungwhan Moon | Carolyn Rosé

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Compressing Neural Language Models by Sparse Word Representations
Yunchuan Chen | Lili Mou | Yan Xu | Ge Li | Zhi Jin

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Intrinsic Subspace Evaluation of Word Embedding Representations
Yadollah Yaghoobzadeh | Hinrich Schütze

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On the Role of Seed Lexicons in Learning Bilingual Word Embeddings
Ivan Vulić | Anna Korhonen

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Liberal Event Extraction and Event Schema Induction
Lifu Huang | Taylor Cassidy | Xiaocheng Feng | Heng Ji | Clare R. Voss | Jiawei Han | Avirup Sil

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Jointly Event Extraction and Visualization on Twitter via Probabilistic Modelling
Deyu Zhou | Tianmeng Gao | Yulan He

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Using Sentence-Level LSTM Language Models for Script Inference
Karl Pichotta | Raymond J. Mooney

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Two Discourse Driven Language Models for Semantics
Haoruo Peng | Dan Roth

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Sentiment Domain Adaptation with Multiple Sources
Fangzhao Wu | Yongfeng Huang

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Connotation Frames: A Data-Driven Investigation
Hannah Rashkin | Sameer Singh | Yejin Choi

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Bi-Transferring Deep Neural Networks for Domain Adaptation
Guangyou Zhou | Zhiwen Xie | Jimmy Xiangji Huang | Tingting He

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Document-level Sentiment Inference with Social, Faction, and Discourse Context
Eunsol Choi | Hannah Rashkin | Luke Zettlemoyer | Yejin Choi

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Active Learning for Dependency Parsing with Partial Annotation
Zhenghua Li | Min Zhang | Yue Zhang | Zhanyi Liu | Wenliang Chen | Hua Wu | Haifeng Wang

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Dependency Parsing with Bounded Block Degree and Well-nestedness via Lagrangian Relaxation and Branch-and-Bound
Caio Corro | Joseph Le Roux | Mathieu Lacroix | Antoine Rozenknop | Roberto Wolfler Calvo

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Query Expansion with Locally-Trained Word Embeddings
Fernando Diaz | Bhaskar Mitra | Nick Craswell

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Together we stand: Siamese Networks for Similar Question Retrieval
Arpita Das | Harish Yenala | Manoj Chinnakotla | Manish Shrivastava

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News Citation Recommendation with Implicit and Explicit Semantics
Hao Peng | Jing Liu | Chin-Yew Lin

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Grapheme-to-Phoneme Models for (Almost) Any Language
Aliya Deri | Kevin Knight

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Neural Word Segmentation Learning for Chinese
Deng Cai | Hai Zhao

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Transition-Based Neural Word Segmentation
Meishan Zhang | Yue Zhang | Guohong Fu

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A Parallel-Hierarchical Model for Machine Comprehension on Sparse Data
Adam Trischler | Zheng Ye | Xingdi Yuan | Jing He | Philip Bachman

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Combining Natural Logic and Shallow Reasoning for Question Answering
Gabor Angeli | Neha Nayak | Christopher D. Manning

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Easy Questions First? A Case Study on Curriculum Learning for Question Answering
Mrinmaya Sachan | Eric Xing

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Improved Representation Learning for Question Answer Matching
Ming Tan | Cicero dos Santos | Bing Xiang | Bowen Zhou

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Tables as Semi-structured Knowledge for Question Answering
Sujay Kumar Jauhar | Peter Turney | Eduard Hovy

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Neural Summarization by Extracting Sentences and Words
Jianpeng Cheng | Mirella Lapata

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Neural Networks For Negation Scope Detection
Federico Fancellu | Adam Lopez | Bonnie Webber

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CSE: Conceptual Sentence Embeddings based on Attention Model
Yashen Wang | Heyan Huang | Chong Feng | Qiang Zhou | Jiahui Gu | Xiong Gao

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DocChat: An Information Retrieval Approach for Chatbot Engines Using Unstructured Documents
Zhao Yan | Nan Duan | Junwei Bao | Peng Chen | Ming Zhou | Zhoujun Li | Jianshe Zhou

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Investigating the Sources of Linguistic Alignment in Conversation
Gabriel Doyle | Michael C. Frank

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Entropy Converges Between Dialogue Participants: Explanations from an Information-Theoretic Perspective
Yang Xu | David Reitter

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Finding the Middle Ground - A Model for Planning Satisficing Answers
Sabine Janzen | Wolfgang Maaß | Tobias Kowatsch

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A Sentence Interaction Network for Modeling Dependence between Sentences
Biao Liu | Minlie Huang

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Towards more variation in text generation: Developing and evaluating variation models for choice of referential form
Thiago Castro Ferreira | Emiel Krahmer | Sander Wubben

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How Much is 131 Million Dollars? Putting Numbers in Perspective with Compositional Descriptions
Arun Chaganty | Percy Liang

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Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus
Iulian Vlad Serban | Alberto García-Durán | Caglar Gulcehre | Sungjin Ahn | Sarath Chandar | Aaron Courville | Yoshua Bengio

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Latent Predictor Networks for Code Generation
Wang Ling | Phil Blunsom | Edward Grefenstette | Karl Moritz Hermann | Tomáš Kočiský | Fumin Wang | Andrew Senior

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Easy Things First: Installments Improve Referring Expression Generation for Objects in Photographs
Sina Zarrieß | David Schlangen

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Collective Entity Resolution with Multi-Focal Attention
Amir Globerson | Nevena Lazic | Soumen Chakrabarti | Amarnag Subramanya | Michael Ringgaard | Fernando Pereira

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Which Coreference Evaluation Metric Do You Trust? A Proposal for a Link-based Entity Aware Metric
Nafise Sadat Moosavi | Michael Strube

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Improving Coreference Resolution by Learning Entity-Level Distributed Representations
Kevin Clark | Christopher D. Manning

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Effects of Creativity and Cluster Tightness on Short Text Clustering Performance
Catherine Finegan-Dollak | Reed Coke | Rui Zhang | Xiangyi Ye | Dragomir Radev

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Generative Topic Embedding: a Continuous Representation of Documents
Shaohua Li | Tat-Seng Chua | Jun Zhu | Chunyan Miao

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Detecting Common Discussion Topics Across Culture From News Reader Comments
Bei Shi | Wai Lam | Lidong Bing | Yinqing Xu

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A Discriminative Topic Model using Document Network Structure
Weiwei Yang | Jordan Boyd-Graber | Philip Resnik

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AraSenTi: Large-Scale Twitter-Specific Arabic Sentiment Lexicons
Nora Al-Twairesh | Hend Al-Khalifa | Abdulmalik Al-Salman

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Unsupervised Multi-Author Document Decomposition Based on Hidden Markov Model
Khaled Aldebei | Xiangjian He | Wenjing Jia | Jie Yang

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Automatic Text Scoring Using Neural Networks
Dimitrios Alikaniotis | Helen Yannakoudakis | Marek Rei

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Improved Semantic Parsers For If-Then Statements
I. Beltagy | Chris Quirk

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Universal Dependencies for Learner English
Yevgeni Berzak | Jessica Kenney | Carolyn Spadine | Jing Xian Wang | Lucia Lam | Keiko Sophie Mori | Sebastian Garza | Boris Katz

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Extracting token-level signals of syntactic processing from fMRI - with an application to PoS induction
Joachim Bingel | Maria Barrett | Anders Søgaard

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Bidirectional Recurrent Convolutional Neural Network for Relation Classification
Rui Cai | Xiaodong Zhang | Houfeng Wang

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Sentence Rewriting for Semantic Parsing
Bo Chen | Le Sun | Xianpei Han | Bo An

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Chinese Zero Pronoun Resolution with Deep Neural Networks
Chen Chen | Vincent Ng

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Constrained Multi-Task Learning for Automated Essay Scoring
Ronan Cummins | Meng Zhang | Ted Briscoe

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CFO: Conditional Focused Neural Question Answering with Large-scale Knowledge Bases
Zihang Dai | Lei Li | Wei Xu

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Verbs Taking Clausal and Non-Finite Arguments as Signals of Modality – Revisiting the Issue of Meaning Grounded in Syntax
Judith Eckle-Kohler

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Tree-to-Sequence Attentional Neural Machine Translation
Akiko Eriguchi | Kazuma Hashimoto | Yoshimasa Tsuruoka

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Coordination Annotation Extension in the Penn Tree Bank
Jessica Ficler | Yoav Goldberg

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Analyzing Biases in Human Perception of User Age and Gender from Text
Lucie Flekova | Jordan Carpenter | Salvatore Giorgi | Lyle Ungar | Daniel Preoţiuc-Pietro

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Modeling Social Norms Evolution for Personalized Sentiment Classification
Lin Gong | Mohammad Al Boni | Hongning Wang

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Modeling Concept Dependencies in a Scientific Corpus
Jonathan Gordon | Linhong Zhu | Aram Galstyan | Prem Natarajan | Gully Burns

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Normalized Log-Linear Interpolation of Backoff Language Models is Efficient
Kenneth Heafield | Chase Geigle | Sean Massung | Lane Schwartz

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How well do Computers Solve Math Word Problems? Large-Scale Dataset Construction and Evaluation
Danqing Huang | Shuming Shi | Chin-Yew Lin | Jian Yin | Wei-Ying Ma

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Embeddings for Word Sense Disambiguation: An Evaluation Study
Ignacio Iacobacci | Mohammad Taher Pilehvar | Roberto Navigli

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Text Understanding with the Attention Sum Reader Network
Rudolf Kadlec | Martin Schmid | Ondrej Bajgar | Jan Kleindienst

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Investigating LSTMs for Joint Extraction of Opinion Entities and Relations
Arzoo Katiyar | Claire Cardie

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Transition-Based Left-Corner Parsing for Identifying PTB-Style Nonlocal Dependencies
Yoshihide Kato | Shigeki Matsubara

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Siamese CBOW: Optimizing Word Embeddings for Sentence Representations
Tom Kenter | Alexey Borisov | Maarten de Rijke

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Unanimous Prediction for 100% Precision with Application to Learning Semantic Mappings
Fereshte Khani | Martin Rinard | Percy Liang

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Exploring Convolutional and Recurrent Neural Networks in Sequential Labelling for Dialogue Topic Tracking
Seokhwan Kim | Rafael Banchs | Haizhou Li

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Cross-Lingual Lexico-Semantic Transfer in Language Learning
Ekaterina Kochmar | Ekaterina Shutova

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A CALL System for Learning Preposition Usage
John Lee | Donald Sturgeon | Mengqi Luo

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A Persona-Based Neural Conversation Model
Jiwei Li | Michel Galley | Chris Brockett | Georgios Spithourakis | Jianfeng Gao | Bill Dolan

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Discriminative Deep Random Walk for Network Classification
Juzheng Li | Jun Zhu | Bo Zhang

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Normalising Medical Concepts in Social Media Texts by Learning Semantic Representation
Nut Limsopatham | Nigel Collier

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Agreement-based Learning of Parallel Lexicons and Phrases from Non-Parallel Corpora
Chunyang Liu | Yang Liu | Maosong Sun | Huanbo Luan | Heng Yu

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Deep Fusion LSTMs for Text Semantic Matching
Pengfei Liu | Xipeng Qiu | Jifan Chen | Xuanjing Huang

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Understanding Discourse on Work and Job-Related Well-Being in Public Social Media
Tong Liu | Christopher Homan | Cecilia Ovesdotter Alm | Megan Lytle | Ann Marie White | Henry Kautz

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Achieving Open Vocabulary Neural Machine Translation with Hybrid Word-Character Models
Minh-Thang Luong | Christopher D. Manning

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End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
Xuezhe Ma | Eduard Hovy

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Off-topic Response Detection for Spontaneous Spoken English Assessment
Andrey Malinin | Rogier Van Dalen | Kate Knill | Yu Wang | Mark Gales

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Synthesizing Compound Words for Machine Translation
Austin Matthews | Eva Schlinger | Alon Lavie | Chris Dyer

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Harnessing Cognitive Features for Sarcasm Detection
Abhijit Mishra | Diptesh Kanojia | Seema Nagar | Kuntal Dey | Pushpak Bhattacharyya

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End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures
Makoto Miwa | Mohit Bansal

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A short proof that O_2 is an MCFL
Mark-Jan Nederhof

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Context-aware Argumentative Relation Mining
Huy Nguyen | Diane Litman

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Leveraging Inflection Tables for Stemming and Lemmatization.
Garrett Nicolai | Grzegorz Kondrak

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Scaling a Natural Language Generation System
Jonathan Pfeil | Soumya Ray

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ALTO: Active Learning with Topic Overviews for Speeding Label Induction and Document Labeling
Forough Poursabzi-Sangdeh | Jordan Boyd-Graber | Leah Findlater | Kevin Seppi

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Predicting the Rise and Fall of Scientific Topics from Trends in their Rhetorical Framing
Vinodkumar Prabhakaran | William L. Hamilton | Dan McFarland | Dan Jurafsky

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Compositional Sequence Labeling Models for Error Detection in Learner Writing
Marek Rei | Helen Yannakoudakis

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Neural Semantic Role Labeling with Dependency Path Embeddings
Michael Roth | Mirella Lapata

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Prediction of Prospective User Engagement with Intelligent Assistants
Shumpei Sano | Nobuhiro Kaji | Manabu Sassano

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Resolving References to Objects in Photographs using the Words-As-Classifiers Model
David Schlangen | Sina Zarrieß | Casey Kennington

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RBPB: Regularization-Based Pattern Balancing Method for Event Extraction
Lei Sha | Jing Liu | Chin-Yew Lin | Sujian Li | Baobao Chang | Zhifang Sui

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Neural Network-Based Model for Japanese Predicate Argument Structure Analysis
Tomohide Shibata | Daisuke Kawahara | Sadao Kurohashi

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Addressing Limited Data for Textual Entailment Across Domains
Chaitanya Shivade | Preethi Raghavan | Siddharth Patwardhan

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Annotating and Predicting Non-Restrictive Noun Phrase Modifications
Gabriel Stanovsky | Ido Dagan

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Bilingual Segmented Topic Model
Akihiro Tamura | Eiichiro Sumita

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Learning Semantically and Additively Compositional Distributional Representations
Ran Tian | Naoaki Okazaki | Kentaro Inui

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Inner Attention based Recurrent Neural Networks for Answer Selection
Bingning Wang | Kang Liu | Jun Zhao

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Relation Classification via Multi-Level Attention CNNs
Linlin Wang | Zhu Cao | Gerard de Melo | Zhiyuan Liu

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Knowledge Base Completion via Coupled Path Ranking
Quan Wang | Jing Liu | Yuanfei Luo | Bin Wang | Chin-Yew Lin

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Larger-Context Language Modelling with Recurrent Neural Network
Tian Wang | Kyunghyun Cho

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The Creation and Analysis of a Website Privacy Policy Corpus
Shomir Wilson | Florian Schaub | Aswarth Abhilash Dara | Frederick Liu | Sushain Cherivirala | Pedro Giovanni Leon | Mads Schaarup Andersen | Sebastian Zimmeck | Kanthashree Mysore Sathyendra | N. Cameron Russell | Thomas B. Norton | Eduard Hovy | Joel Reidenberg | Norman Sadeh

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Sequence-based Structured Prediction for Semantic Parsing
Chunyang Xiao | Marc Dymetman | Claire Gardent

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Learning Word Meta-Embeddings
Wenpeng Yin | Hinrich Schütze

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Towards Constructing Sports News from Live Text Commentary
Jianmin Zhang | Jin-ge Yao | Xiaojun Wan

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A Continuous Space Rule Selection Model for Syntax-based Statistical Machine Translation
Jingyi Zhang | Masao Utiyama | Eiichro Sumita | Graham Neubig | Satoshi Nakamura

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Probabilistic Graph-based Dependency Parsing with Convolutional Neural Network
Zhisong Zhang | Hai Zhao | Lianhui Qin

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A Search-Based Dynamic Reranking Model for Dependency Parsing
Hao Zhou | Yue Zhang | Shujian Huang | Junsheng Zhou | Xin-Yu Dai | Jiajun Chen

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Cross-Lingual Sentiment Classification with Bilingual Document Representation Learning
Xinjie Zhou | Xiaojun Wan | Jianguo Xiao

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Segment-Level Sequence Modeling using Gated Recursive Semi-Markov Conditional Random Fields
Jingwei Zhuo | Yong Cao | Jun Zhu | Bo Zhang | Zaiqing Nie

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Identifying Causal Relations Using Parallel Wikipedia Articles
Christopher Hidey | Kathy McKeown

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Compositional Learning of Embeddings for Relation Paths in Knowledge Base and Text
Kristina Toutanova | Victoria Lin | Wen-tau Yih | Hoifung Poon | Chris Quirk

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Commonsense Knowledge Base Completion
Xiang Li | Aynaz Taheri | Lifu Tu | Kevin Gimpel

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Simpler Context-Dependent Logical Forms via Model Projections
Reginald Long | Panupong Pasupat | Percy Liang

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A Fast Unified Model for Parsing and Sentence Understanding
Samuel R. Bowman | Jon Gauthier | Abhinav Rastogi | Raghav Gupta | Christopher D. Manning | Christopher Potts

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Investigating Language Universal and Specific Properties in Word Embeddings
Peng Qian | Xipeng Qiu | Xuanjing Huang

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Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change
William L. Hamilton | Jure Leskovec | Dan Jurafsky

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Beyond Plain Spatial Knowledge: Determining Where Entities Are and Are Not Located, and For How Long
Alakananda Vempala | Eduardo Blanco

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LexSemTm: A Semantic Dataset Based on All-words Unsupervised Sense Distribution Learning
Andrew Bennett | Timothy Baldwin | Jey Han Lau | Diana McCarthy | Francis Bond

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The LAMBADA dataset: Word prediction requiring a broad discourse context
Denis Paperno | Germán Kruszewski | Angeliki Lazaridou | Ngoc Quan Pham | Raffaella Bernardi | Sandro Pezzelle | Marco Baroni | Gemma Boleda | Raquel Fernández

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WikiReading: A Novel Large-scale Language Understanding Task over Wikipedia
Daniel Hewlett | Alexandre Lacoste | Llion Jones | Illia Polosukhin | Andrew Fandrianto | Jay Han | Matthew Kelcey | David Berthelot

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Optimizing Spectral Learning for Parsing
Shashi Narayan | Shay B. Cohen

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Stack-propagation: Improved Representation Learning for Syntax
Yuan Zhang | David Weiss

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Inferring Perceived Demographics from User Emotional Tone and User-Environment Emotional Contrast
Svitlana Volkova | Yoram Bachrach

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Prototype Synthesis for Model Laws
Matthew Burgess | Eugenia Giraudy | Eytan Adar

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Which argument is more convincing? Analyzing and predicting convincingness of Web arguments using bidirectional LSTM
Ivan Habernal | Iryna Gurevych

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Discovery of Treatments from Text Corpora
Christian Fong | Justin Grimmer

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Learning Structured Predictors from Bandit Feedback for Interactive NLP
Artem Sokolov | Julia Kreutzer | Christopher Lo | Stefan Riezler

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Deep Reinforcement Learning with a Natural Language Action Space
Ji He | Jianshu Chen | Xiaodong He | Jianfeng Gao | Lihong Li | Li Deng | Mari Ostendorf

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Incorporating Copying Mechanism in Sequence-to-Sequence Learning
Jiatao Gu | Zhengdong Lu | Hang Li | Victor O.K. Li

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Cross-domain Text Classification with Multiple Domains and Disparate Label Sets
Himanshu Sharad Bhatt | Manjira Sinha | Shourya Roy

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Morphological Smoothing and Extrapolation of Word Embeddings
Ryan Cotterell | Hinrich Schütze | Jason Eisner

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Cross-lingual Models of Word Embeddings: An Empirical Comparison
Shyam Upadhyay | Manaal Faruqui | Chris Dyer | Dan Roth

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Take and Took, Gaggle and Goose, Book and Read: Evaluating the Utility of Vector Differences for Lexical Relation Learning
Ekaterina Vylomova | Laura Rimell | Trevor Cohn | Timothy Baldwin

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Minimum Risk Training for Neural Machine Translation
Shiqi Shen | Yong Cheng | Zhongjun He | Wei He | Hua Wu | Maosong Sun | Yang Liu

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A Character-level Decoder without Explicit Segmentation for Neural Machine Translation
Junyoung Chung | Kyunghyun Cho | Yoshua Bengio

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Target-Side Context for Discriminative Models in Statistical Machine Translation
Aleš Tamchyna | Alexander Fraser | Ondřej Bojar | Marcin Junczys-Dowmunt

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Neural Machine Translation of Rare Words with Subword Units
Rico Sennrich | Barry Haddow | Alexandra Birch

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Implicit Discourse Relation Detection via a Deep Architecture with Gated Relevance Network
Jifan Chen | Qi Zhang | Pengfei Liu | Xipeng Qiu | Xuanjing Huang

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Model Architectures for Quotation Detection
Christian Scheible | Roman Klinger | Sebastian Padó

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Speech Act Modeling of Written Asynchronous Conversations with Task-Specific Embeddings and Conditional Structured Models
Shafiq Joty | Enamul Hoque

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Situation entity types: automatic classification of clause-level aspect
Annemarie Friedrich | Alexis Palmer | Manfred Pinkal

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Learning Prototypical Event Structure from Photo Albums
Antoine Bosselut | Jianfu Chen | David Warren | Hannaneh Hajishirzi | Yejin Choi

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Cross-Lingual Image Caption Generation
Takashi Miyazaki | Nobuyuki Shimizu

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Learning Concept Taxonomies from Multi-modal Data
Hao Zhang | Zhiting Hu | Yuntian Deng | Mrinmaya Sachan | Zhicheng Yan | Eric Xing

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Generating Natural Questions About an Image
Nasrin Mostafazadeh | Ishan Misra | Jacob Devlin | Margaret Mitchell | Xiaodong He | Lucy Vanderwende

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Physical Causality of Action Verbs in Grounded Language Understanding
Qiaozi Gao | Malcolm Doering | Shaohua Yang | Joyce Chai

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Optimizing an Approximation of ROUGE - a Problem-Reduction Approach to Extractive Multi-Document Summarization
Maxime Peyrard | Judith Eckle-Kohler

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Phrase Structure Annotation and Parsing for Learner English
Ryo Nagata | Keisuke Sakaguchi

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A Trainable Spaced Repetition Model for Language Learning
Burr Settles | Brendan Meeder

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User Modeling in Language Learning with Macaronic Texts
Adithya Renduchintala | Rebecca Knowles | Philipp Koehn | Jason Eisner

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On the Similarities Between Native, Non-native and Translated Texts
Ella Rabinovich | Sergiu Nisioi | Noam Ordan | Shuly Wintner

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Learning Text Pair Similarity with Context-sensitive Autoencoders
Hadi Amiri | Philip Resnik | Jordan Boyd-Graber | Hal Daumé III

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Linguistic Benchmarks of Online News Article Quality
Ioannis Arapakis | Filipa Peleja | Barla Berkant | Joao Magalhaes

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Alleviating Poor Context with Background Knowledge for Named Entity Disambiguation
Ander Barrena | Aitor Soroa | Eneko Agirre

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Mining Paraphrasal Typed Templates from a Plain Text Corpus
Or Biran | Terra Blevins | Kathleen McKeown

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How to Train Dependency Parsers with Inexact Search for Joint Sentence Boundary Detection and Parsing of Entire Documents
Anders Björkelund | Agnieszka Faleńska | Wolfgang Seeker | Jonas Kuhn

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MUTT: Metric Unit TesTing for Language Generation Tasks
William Boag | Renan Campos | Kate Saenko | Anna Rumshisky

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N-gram language models for massively parallel devices
Nikolay Bogoychev | Adam Lopez

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Cross-Lingual Morphological Tagging for Low-Resource Languages
Jan Buys | Jan A. Botha

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Semi-Supervised Learning for Neural Machine Translation
Yong Cheng | Wei Xu | Zhongjun He | Wei He | Hua Wu | Maosong Sun | Yang Liu

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Strategies for Training Large Vocabulary Neural Language Models
Wenlin Chen | David Grangier | Michael Auli

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Predicting the Compositionality of Nominal Compounds: Giving Word Embeddings a Hard Time
Silvio Cordeiro | Carlos Ramisch | Marco Idiart | Aline Villavicencio

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Learning-Based Single-Document Summarization with Compression and Anaphoricity Constraints
Greg Durrett | Taylor Berg-Kirkpatrick | Dan Klein

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Set-Theoretic Alignment for Comparable Corpora
Thierry Etchegoyhen | Andoni Azpeitia

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Jointly Learning to Embed and Predict with Multiple Languages
Daniel C. Ferreira | André F. T. Martins | Mariana S. C. Almeida

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Supersense Embeddings: A Unified Model for Supersense Interpretation, Prediction, and Utilization
Lucie Flekova | Iryna Gurevych

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Efficient techniques for parsing with tree automata
Jonas Groschwitz | Alexander Koller | Mark Johnson

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A Vector Space for Distributional Semantics for Entailment
James Henderson | Diana Popa

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Hidden Softmax Sequence Model for Dialogue Structure Analysis
Zhiyang He | Xien Liu | Ping Lv | Ji Wu

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Summarizing Source Code using a Neural Attention Model
Srinivasan Iyer | Ioannis Konstas | Alvin Cheung | Luke Zettlemoyer

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Continuous Profile Models in ASL Syntactic Facial Expression Synthesis
Hernisa Kacorri | Matt Huenerfauth

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Evaluating Sentiment Analysis in the Context of Securities Trading
Siavash Kazemian | Shunan Zhao | Gerald Penn

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Edge-Linear First-Order Dependency Parsing with Undirected Minimum Spanning Tree Inference
Effi Levi | Roi Reichart | Ari Rappoport

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Topic Extraction from Microblog Posts Using Conversation Structures
Jing Li | Ming Liao | Wei Gao | Yulan He | Kam-Fai Wong

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Neural Relation Extraction with Selective Attention over Instances
Yankai Lin | Shiqi Shen | Zhiyuan Liu | Huanbo Luan | Maosong Sun

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Leveraging FrameNet to Improve Automatic Event Detection
Shulin Liu | Yubo Chen | Shizhu He | Kang Liu | Jun Zhao

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Learning To Use Formulas To Solve Simple Arithmetic Problems
Arindam Mitra | Chitta Baral

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Unravelling Names of Fictional Characters
Katerina Papantoniou | Stasinos Konstantopoulos

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Most “babies” are “little” and most “problems” are “huge”: Compositional Entailment in Adjective-Nouns
Ellie Pavlick | Chris Callison-Burch

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Modeling Stance in Student Essays
Isaac Persing | Vincent Ng

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A New Psychometric-inspired Evaluation Metric for Chinese Word Segmentation
Peng Qian | Xipeng Qiu | Xuanjing Huang

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Temporal Anchoring of Events for the TimeBank Corpus
Nils Reimers | Nazanin Dehghani | Iryna Gurevych

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Grammatical Error Correction: Machine Translation and Classifiers
Alla Rozovskaya | Dan Roth

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Recurrent neural network models for disease name recognition using domain invariant features
Sunil Sahu | Ashish Anand

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Domain Adaptation for Authorship Attribution: Improved Structural Correspondence Learning
Upendra Sapkota | Thamar Solorio | Manuel Montes | Steven Bethard

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A Corpus-Based Analysis of Canonical Word Order of Japanese Double Object Constructions
Ryohei Sasano | Manabu Okumura

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Knowledge-Based Semantic Embedding for Machine Translation
Chen Shi | Shujie Liu | Shuo Ren | Shi Feng | Mu Li | Ming Zhou | Xu Sun | Houfeng Wang

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One for All: Towards Language Independent Named Entity Linking
Avirup Sil | Radu Florian

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On Approximately Searching for Similar Word Embeddings
Kohei Sugawara | Hayato Kobayashi | Masajiro Iwasaki

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Composing Distributed Representations of Relational Patterns
Sho Takase | Naoaki Okazaki | Kentaro Inui

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The More Antecedents, the Merrier: Resolving Multi-Antecedent Anaphors
Hardik Vala | Andrew Piper | Derek Ruths

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Automatic Labeling of Topic Models Using Text Summaries
Xiaojun Wan | Tianming Wang

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Graph-based Dependency Parsing with Bidirectional LSTM
Wenhui Wang | Baobao Chang

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TransG : A Generative Model for Knowledge Graph Embedding
Han Xiao | Minlie Huang | Xiaoyan Zhu

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Question Answering on Freebase via Relation Extraction and Textual Evidence
Kun Xu | Siva Reddy | Yansong Feng | Songfang Huang | Dongyan Zhao

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Vector-space topic models for detecting Alzheimer’s disease
Maria Yancheva | Frank Rudzicz

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Chinese Couplet Generation with Neural Network Structures
Rui Yan | Cheng-Te Li | Xiaohua Hu | Ming Zhang

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A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task
Danqi Chen | Jason Bolton | Christopher D. Manning

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Learning Language Games through Interaction
Sida I. Wang | Percy Liang | Christopher D. Manning

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Finding Non-Arbitrary Form-Meaning Systematicity Using String-Metric Learning for Kernel Regression
E.Dario Gutiérrez | Roger Levy | Benjamin Bergen

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Improving Hypernymy Detection with an Integrated Path-based and Distributional Method
Vered Shwartz | Yoav Goldberg | Ido Dagan

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Multimodal Pivots for Image Caption Translation
Julian Hitschler | Shigehiko Schamoni | Stefan Riezler

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Harnessing Deep Neural Networks with Logic Rules
Zhiting Hu | Xuezhe Ma | Zhengzhong Liu | Eduard Hovy | Eric Xing

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Case and Cause in Icelandic: Reconstructing Causal Networks of Cascaded Language Changes
Fermín Moscoso del Prado Martín | Christian Brendel

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On-line Active Reward Learning for Policy Optimisation in Spoken Dialogue Systems
Pei-Hao Su | Milica Gašić | Nikola Mrkšić | Lina M. Rojas-Barahona | Stefan Ultes | David Vandyke | Tsung-Hsien Wen | Steve Young

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Globally Normalized Transition-Based Neural Networks
Daniel Andor | Chris Alberti | David Weiss | Aliaksei Severyn | Alessandro Presta | Kuzman Ganchev | Slav Petrov | Michael Collins


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Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

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Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
Katrin Erk | Noah A. Smith

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Transition-based dependency parsing with topological fields
Daniël de Kok | Erhard Hinrichs

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Scalable Semi-Supervised Query Classification Using Matrix Sketching
Young-Bum Kim | Karl Stratos | Ruhi Sarikaya

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Learning Multiview Embeddings of Twitter Users
Adrian Benton | Raman Arora | Mark Dredze

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Implicit Polarity and Implicit Aspect Recognition in Opinion Mining
Huan-Yuan Chen | Hsin-Hsi Chen

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A Domain Adaptation Regularization for Denoising Autoencoders
Stéphane Clinchant | Gabriela Csurka | Boris Chidlovskii

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Incremental Parsing with Minimal Features Using Bi-Directional LSTM
James Cross | Liang Huang

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Improving Statistical Machine Translation Performance by Oracle-BLEU Model Re-estimation
Praveen Dakwale | Christof Monz

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Sequence-to-Sequence Generation for Spoken Dialogue via Deep Syntax Trees and Strings
Ondřej Dušek | Filip Jurčíček

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On the Linearity of Semantic Change: Investigating Meaning Variation via Dynamic Graph Models
Steffen Eger | Alexander Mehler

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Joint Word Segmentation and Phonetic Category Induction
Micha Elsner | Stephanie Antetomaso | Naomi Feldman

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A Language-Independent Neural Network for Event Detection
Xiaocheng Feng | Lifu Huang | Duyu Tang | Heng Ji | Bing Qin | Ting Liu

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Improved Parsing for Argument-Clusters Coordination
Jessica Ficler | Yoav Goldberg

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Reference Bias in Monolingual Machine Translation Evaluation
Marina Fomicheva | Lucia Specia

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Cross-lingual projection for class-based language models
Beat Gfeller | Vlad Schogol | Keith Hall

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A Fast Approach for Semantic Similar Short Texts Retrieval
Yanhui Gu | Zhenglu Yang | Junsheng Zhou | Weiguang Qu | Jinmao Wei | Xingtian Shi

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Empty element recovery by spinal parser operations
Katsuhiko Hayashi | Masaaki Nagata

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Semantic classifications for detection of verb metaphors
Beata Beigman Klebanov | Chee Wee Leong | E. Dario Gutierrez | Ekaterina Shutova | Michael Flor

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Recognizing Salient Entities in Shopping Queries
Zornitsa Kozareva | Qi Li | Ke Zhai | Weiwei Guo

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Leveraging Lexical Resources for Learning Entity Embeddings in Multi-Relational Data
Teng Long | Ryan Lowe | Jackie Chi Kit Cheung | Doina Precup

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Multiplicative Representations for Unsupervised Semantic Role Induction
Yi Luan | Yangfeng Ji | Hannaneh Hajishirzi | Boyang Li

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Vocabulary Manipulation for Neural Machine Translation
Haitao Mi | Zhiguo Wang | Abe Ittycheriah

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Natural Language Inference by Tree-Based Convolution and Heuristic Matching
Lili Mou | Rui Men | Ge Li | Yan Xu | Lu Zhang | Rui Yan | Zhi Jin

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Improving cross-domain n-gram language modelling with skipgrams
Louis Onrust | Antal van den Bosch | Hugo Van hamme

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Simple PPDB: A Paraphrase Database for Simplification
Ellie Pavlick | Chris Callison-Burch

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Improving Named Entity Recognition for Chinese Social Media with Word Segmentation Representation Learning
Nanyun Peng | Mark Dredze

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How Naked is the Naked Truth? A Multilingual Lexicon of Nominal Compound Compositionality
Carlos Ramisch | Silvio Cordeiro | Leonardo Zilio | Marco Idiart | Aline Villavicencio

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An Open Web Platform for Rule-Based Speech-to-Sign Translation
Manny Rayner | Pierrette Bouillon | Sarah Ebling | Johanna Gerlach | Irene Strasly | Nikos Tsourakis

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Word Alignment without NULL Words
Philip Schulz | Wilker Aziz | Khalil Sima’an

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Unsupervised morph segmentation and statistical language models for vocabulary expansion
Matti Varjokallio | Dietrich Klakow

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Detecting Mild Cognitive Impairment by Exploiting Linguistic Information from Transcripts
Veronika Vincze | Gábor Gosztolya | László Tóth | Ildikó Hoffmann | Gréta Szatlóczki | Zoltán Bánréti | Magdolna Pákáski | János Kálmán

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Multi-Modal Representations for Improved Bilingual Lexicon Learning
Ivan Vulić | Douwe Kiela | Stephen Clark | Marie-Francine Moens

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Is This Post Persuasive? Ranking Argumentative Comments in Online Forum
Zhongyu Wei | Yang Liu | Yi Li

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The Value of Semantic Parse Labeling for Knowledge Base Question Answering
Wen-tau Yih | Matthew Richardson | Chris Meek | Ming-Wei Chang | Jina Suh

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Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classification
Peng Zhou | Wei Shi | Jun Tian | Zhenyu Qi | Bingchen Li | Hongwei Hao | Bo Xu

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The red one!: On learning to refer to things based on discriminative properties
Angeliki Lazaridou | Nghia The Pham | Marco Baroni

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Don’t Count, Predict! An Automatic Approach to Learning Sentiment Lexicons for Short Text
Duy Tin Vo | Yue Zhang

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Dimensional Sentiment Analysis Using a Regional CNN-LSTM Model
Jin Wang | Liang-Chih Yu | K. Robert Lai | Xuejie Zhang

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Deep multi-task learning with low level tasks supervised at lower layers
Anders Søgaard | Yoav Goldberg

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Domain Specific Named Entity Recognition Referring to the Real World by Deep Neural Networks
Suzushi Tomori | Takashi Ninomiya | Shinsuke Mori

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An Entity-Focused Approach to Generating Company Descriptions
Gavin Saldanha | Or Biran | Kathleen McKeown | Alfio Gliozzo

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Annotating Relation Inference in Context via Question Answering
Omer Levy | Ido Dagan

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Automatic Semantic Classification of German Preposition Types: Comparing Hard and Soft Clustering Approaches across Features
Maximilian Köper | Sabine Schulte im Walde

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Natural Language Generation enhances human decision-making with uncertain information
Dimitra Gkatzia | Oliver Lemon | Verena Rieser

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Tweet2Vec: Character-Based Distributed Representations for Social Media
Bhuwan Dhingra | Zhong Zhou | Dylan Fitzpatrick | Michael Muehl | William Cohen

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Phrase-Level Combination of SMT and TM Using Constrained Word Lattice
Liangyou Li | Andy Way | Qun Liu

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A Neural Network based Approach to Automatic Post-Editing
Santanu Pal | Sudip Kumar Naskar | Mihaela Vela | Josef van Genabith

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An Unsupervised Method for Automatic Translation Memory Cleaning
Masoud Jalili Sabet | Matteo Negri | Marco Turchi | Eduard Barbu

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Exponentially Decaying Bag-of-Words Input Features for Feed-Forward Neural Network in Statistical Machine Translation
Jan-Thorsten Peter | Weiyue Wang | Hermann Ney

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Syntactically Guided Neural Machine Translation
Felix Stahlberg | Eva Hasler | Aurelien Waite | Bill Byrne

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Very quaffable and great fun: Applying NLP to wine reviews
Iris Hendrickx | Els Lefever | Ilja Croijmans | Asifa Majid | Antal van den Bosch

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Exploring Stylistic Variation with Age and Income on Twitter
Lucie Flekova | Daniel Preoţiuc-Pietro | Lyle Ungar

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Finding Optimists and Pessimists on Twitter
Xianzhi Ruan | Steven Wilson | Rada Mihalcea

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Transductive Adaptation of Black Box Predictions
Stéphane Clinchant | Boris Chidlovskii | Gabriela Csurka

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Which Tumblr Post Should I Read Next?
Zornitsa Kozareva | Makoto Yamada

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Text Simplification as Tree Labeling
Joachim Bingel | Anders Søgaard

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Bootstrapped Text-level Named Entity Recognition for Literature
Julian Brooke | Adam Hammond | Timothy Baldwin

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The Enemy in Your Own Camp: How Well Can We Detect Statistically-Generated Fake Reviews – An Adversarial Study
Dirk Hovy

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Character-based Neural Machine Translation
Marta R. Costa-jussà | José A. R. Fonollosa

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Learning Monolingual Compositional Representations via Bilingual Supervision
Ahmed Elgohary | Marine Carpuat

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Event Nugget Detection with Forward-Backward Recurrent Neural Networks
Reza Ghaeini | Xiaoli Fern | Liang Huang | Prasad Tadepalli

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IBC-C: A Dataset for Armed Conflict Analysis
Andrej Žukov-Gregorič | Zhiyuan Luo | Bartal Veyhe

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A Latent Concept Topic Model for Robust Topic Inference Using Word Embeddings
Weihua Hu | Jun’ichi Tsujii

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Word Embeddings with Limited Memory
Shaoshi Ling | Yangqiu Song | Dan Roth

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Hawkes Processes for Continuous Time Sequence Classification: an Application to Rumour Stance Classification in Twitter
Michal Lukasik | P. K. Srijith | Duy Vu | Kalina Bontcheva | Arkaitz Zubiaga | Trevor Cohn

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Hunting for Troll Comments in News Community Forums
Todor Mihaylov | Preslav Nakov

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Phrase Table Pruning via Submodular Function Maximization
Masaaki Nishino | Jun Suzuki | Masaaki Nagata

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Multilingual Part-of-Speech Tagging with Bidirectional Long Short-Term Memory Models and Auxiliary Loss
Barbara Plank | Anders Søgaard | Yoav Goldberg

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Matrix Factorization using Window Sampling and Negative Sampling for Improved Word Representations
Alexandre Salle | Aline Villavicencio | Marco Idiart

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One model, two languages: training bilingual parsers with harmonized treebanks
David Vilares | Carlos Gómez-Rodríguez | Miguel A. Alonso

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Using mention accessibility to improve coreference resolution
Kellie Webster | Joel Nothman

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Exploiting Linguistic Features for Sentence Completion
Aubrie Woods

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Convergence of Syntactic Complexity in Conversation
Yang Xu | David Reitter

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User Embedding for Scholarly Microblog Recommendation
Yang Yu | Xiaojun Wan | Xinjie Zhou

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Integrating Distributional Lexical Contrast into Word Embeddings for Antonym-Synonym Distinction
Kim Anh Nguyen | Sabine Schulte im Walde | Ngoc Thang Vu

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Machine Translation Evaluation Meets Community Question Answering
Francisco Guzmán | Lluís Màrquez | Preslav Nakov

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Science Question Answering using Instructional Materials
Mrinmaya Sachan | Kumar Dubey | Eric Xing

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Specifying and Annotating Reduced Argument Span Via QA-SRL
Gabriel Stanovsky | Ido Dagan | Meni Adler

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Improving Argument Overlap for Proposition-Based Summarisation
Yimai Fang | Simone Teufel

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Machine Comprehension using Rich Semantic Representations
Mrinmaya Sachan | Eric Xing

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Cross-Lingual Word Representations via Spectral Graph Embeddings
Takamasa Oshikiri | Kazuki Fukui | Hidetoshi Shimodaira

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Semantics-Driven Recognition of Collocations Using Word Embeddings
Sara Rodríguez-Fernández | Luis Espinosa-Anke | Roberto Carlini | Leo Wanner

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Incorporating Relational Knowledge into Word Representations using Subspace Regularization
Abhishek Kumar | Jun Araki

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Word Embedding Calculus in Meaningful Ultradense Subspaces
Sascha Rothe | Hinrich Schütze

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Is “Universal Syntax” Universally Useful for Learning Distributed Word Representations?
Ivan Vulić | Anna Korhonen

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Claim Synthesis via Predicate Recycling
Yonatan Bilu | Noam Slonim

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Modelling the Interpretation of Discourse Connectives by Bayesian Pragmatics
Frances Yung | Kevin Duh | Taku Komura | Yuji Matsumoto

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Nonparametric Spherical Topic Modeling with Word Embeddings
Kayhan Batmanghelich | Ardavan Saeedi | Karthik Narasimhan | Sam Gershman

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A Novel Measure for Coherence in Statistical Topic Models
Fred Morstatter | Huan Liu

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Coarse-grained Argumentation Features for Scoring Persuasive Essays
Debanjan Ghosh | Aquila Khanam | Yubo Han | Smaranda Muresan

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Single-Model Encoder-Decoder with Explicit Morphological Representation for Reinflection
Katharina Kann | Hinrich Schütze

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Joint part-of-speech and dependency projection from multiple sources
Anders Johannsen | Željko Agić | Anders Søgaard

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Dependency-based Gated Recursive Neural Network for Chinese Word Segmentation
Jingjing Xu | Xu Sun

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Deep Neural Networks for Syntactic Parsing of Morphologically Rich Languages
Joël Legrand | Ronan Collobert

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Weakly Supervised Part-of-speech Tagging Using Eye-tracking Data
Maria Barrett | Joachim Bingel | Frank Keller | Anders Søgaard

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Metrics for Evaluation of Word-level Machine Translation Quality Estimation
Varvara Logacheva | Michal Lukasik | Lucia Specia

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The Social Impact of Natural Language Processing
Dirk Hovy | Shannon L. Spruit

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Using Sequence Similarity Networks to Identify Partial Cognates in Multilingual Wordlists
Johann-Mattis List | Philippe Lopez | Eric Bapteste


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Proceedings of the ACL 2016 Student Research Workshop

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Proceedings of the ACL 2016 Student Research Workshop
He He | Tao Lei | Will Roberts

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Controlled and Balanced Dataset for Japanese Lexical Simplification
Tomonori Kodaira | Tomoyuki Kajiwara | Mamoru Komachi

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Dependency Forest based Word Alignment
Hitoshi Otsuki | Chenhui Chu | Toshiaki Nakazawa | Sadao Kurohashi

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Identifying Potential Adverse Drug Events in Tweets Using Bootstrapped Lexicons
Eric Benzschawel

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Generating Natural Language Descriptions for Semantic Representations of Human Brain Activity
Eri Matsuo | Ichiro Kobayashi | Shinji Nishimoto | Satoshi Nishida | Hideki Asoh

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Improving Twitter Community Detection through Contextual Sentiment Analysis
Alron Jan Lam

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Significance of an Accurate Sandhi-Splitter in Shallow Parsing of Dravidian Languages
Devadath V V | Dipti Misra Sharma

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Improving Topic Model Clustering of Newspaper Comments for Summarisation
Clare Llewellyn | Claire Grover | Jon Oberlander

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Arabizi Identification in Twitter Data
Taha Tobaili

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Robust Co-occurrence Quantification for Lexical Distributional Semantics
Dmitrijs Milajevs | Mehrnoosh Sadrzadeh | Matthew Purver

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Singleton Detection using Word Embeddings and Neural Networks
Hessel Haagsma

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A Dataset for Joint Noun-Noun Compound Bracketing and Interpretation
Murhaf Fares

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An Investigation on The Effectiveness of Employing Topic Modeling Techniques to Provide Topic Awareness For Conversational Agents
Omid Moradiannasab

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Improving Dependency Parsing Using Sentence Clause Charts
Vincent Kríž | Barbora Hladká

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Graph- and surface-level sentence chunking
Ewa Muszyńska

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From Extractive to Abstractive Summarization: A Journey
Parth Mehta

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Putting Sarcasm Detection into Context: The Effects of Class Imbalance and Manual Labelling on Supervised Machine Classification of Twitter Conversations
Gavin Abercrombie | Dirk Hovy

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Unsupervised Authorial Clustering Based on Syntactic Structure
Alon Daks | Aidan Clark

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Suggestion Mining from Opinionated Text
Sapna Negi

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An Efficient Cross-lingual Model for Sentence Classification Using Convolutional Neural Network
Yandi Xia | Zhongyu Wei | Yang Liu

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QA-It: Classifying Non-Referential It for Question Answer Pairs
Timothy Lee | Alex Lutz | Jinho D. Choi

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Building a Corpus for Japanese Wikification with Fine-Grained Entity Classes
Davaajav Jargalsaikhan | Naoaki Okazaki | Koji Matsuda | Kentaro Inui

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A Personalized Markov Clustering and Deep Learning Approach for Arabic Text Categorization
Vasu Jindal


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Proceedings of ACL-2016 System Demonstrations

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Proceedings of ACL-2016 System Demonstrations
Sameer Pradhan | Marianna Apidianaki

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POLYGLOT: Multilingual Semantic Role Labeling with Unified Labels
Alan Akbik | Yunyao Li

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Online Information Retrieval for Language Learning
Maria Chinkina | Madeeswaran Kannan | Detmar Meurers

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Terminology Extraction with Term Variant Detection
Damien Cram | Béatrice Daille

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DeepLife: An Entity-aware Search, Analytics and Exploration Platform for Health and Life Sciences
Patrick Ernst | Amy Siu | Dragan Milchevski | Johannes Hoffart | Gerhard Weikum

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Visualizing and Curating Knowledge Graphs over Time and Space
Tong Ge | Yafang Wang | Gerard de Melo | Haofeng Li | Baoquan Chen

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A Web-framework for ODIN Annotation
Ryan Georgi | Michael Wayne Goodman | Fei Xia

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Real-Time Discovery and Geospatial Visualization of Mobility and Industry Events from Large-Scale, Heterogeneous Data Streams
Leonhard Hennig | Philippe Thomas | Renlong Ai | Johannes Kirschnick | He Wang | Jakob Pannier | Nora Zimmermann | Sven Schmeier | Feiyu Xu | Jan Ostwald | Hans Uszkoreit

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TranscRater: a Tool for Automatic Speech Recognition Quality Estimation
Shahab Jalalvand | Matteo Negri | Marco Turchi | José G. C. de Souza | Daniele Falavigna | Mohammed R. H. Qwaider

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TMop: a Tool for Unsupervised Translation Memory Cleaning
Masoud Jalili Sabet | Matteo Negri | Marco Turchi | José G. C. de Souza | Marcello Federico

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MMFeat: A Toolkit for Extracting Multi-Modal Features
Douwe Kiela

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JEDI: Joint Entity and Relation Detection using Type Inference
Johannes Kirschnick | Holmer Hemsen | Volker Markl

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OpenDial: A Toolkit for Developing Spoken Dialogue Systems with Probabilistic Rules
Pierre Lison | Casey Kennington

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MUSEEC: A Multilingual Text Summarization Tool
Marina Litvak | Natalia Vanetik | Mark Last | Elena Churkin

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Language Muse: Automated Linguistic Activity Generation for English Language Learners
Nitin Madnani | Jill Burstein | John Sabatini | Kietha Biggers | Slava Andreyev

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ccg2lambda: A Compositional Semantics System
Pascual Martínez-Gómez | Koji Mineshima | Yusuke Miyao | Daisuke Bekki

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MeTA: A Unified Toolkit for Text Retrieval and Analysis
Sean Massung | Chase Geigle | ChengXiang Zhai

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MDSWriter: Annotation Tool for Creating High-Quality Multi-Document Summarization Corpora
Christian M. Meyer | Darina Benikova | Margot Mieskes | Iryna Gurevych

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Jigg: A Framework for an Easy Natural Language Processing Pipeline
Hiroshi Noji | Yusuke Miyao

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An Advanced Press Review System Combining Deep News Analysis and Machine Learning Algorithms
Danuta Ploch | Andreas Lommatzsch | Florian Schultze

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Personalized Exercises for Preposition Learning
John Lee | Mengqi Luo

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My Science Tutor—Learning Science with a Conversational Virtual Tutor
Sameer Pradhan | Ron Cole | Wayne Ward

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pigeo: A Python Geotagging Tool
Afshin Rahimi | Trevor Cohn | Timothy Baldwin

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Creating Interactive Macaronic Interfaces for Language Learning
Adithya Renduchintala | Rebecca Knowles | Philipp Koehn | Jason Eisner

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Roleo: Visualising Thematic Fit Spaces on the Web
Asad Sayeed | Xudong Hong | Vera Demberg

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MediaGist: A Cross-lingual Analyser of Aggregated News and Commentaries
Josef Steinberger

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GoWvis: A Web Application for Graph-of-Words-based Text Visualization and Summarization
Antoine Tixier | Konstantinos Skianis | Michalis Vazirgiannis

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LiMoSINe Pipeline: Multilingual UIMA-based NLP Platform
Olga Uryupina | Barbara Plank | Gianni Barlacchi | Francisco J. Valverde Albacete | Manos Tsagkias | Antonio Uva | Alessandro Moschitti

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new/s/leak – Information Extraction and Visualization for Investigative Data Journalists
Seid Muhie Yimam | Heiner Ulrich | Tatiana von Landesberger | Marcel Rosenbach | Michaela Regneri | Alexander Panchenko | Franziska Lehmann | Uli Fahrer | Chris Biemann | Kathrin Ballweg


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Multimodal Learning and Reasoning
Desmond Elliott | Douwe Kiela | Angeliki Lazaridou

Natural Language Processing has broadened in scope to tackle more and more challenging language understanding and reasoning tasks. The core NLP tasks remain predominantly unimodal, focusing on linguistic input, despite the fact that we, humans, acquire and use language while communicating in perceptually rich environments. Moving towards human-level AI will require the integration and modeling of multiple modalities beyond language. With this tutorial, our aim is to introduce researchers to the areas of NLP that have dealt with multimodal signals. The key advantage of using multimodal signals in NLP tasks is the complementarity of the data in different modalities. For example, we are less likely to nd descriptions of yellow bananas or wooden chairs in text corpora, but these visual attributes can be readily extracted directly from images. Multimodal signals, such as visual, auditory or olfactory data, have proven useful for models of word similarity and relatedness, automatic image and video description, and even predicting the associated smells of words. Finally, multimodality offers a practical opportunity to study and apply multitask learning, a general machine learning paradigm that improves generalization performance of a task by using training signals of other related tasks.All material associated to the tutorial will be available at http://multimodalnlp.github.io/

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NLP Approaches to Computational Argumentation
Noam Slonim | Iryna Gurevych | Chris Reed | Benno Stein

Argumentation and debating represent primary intellectual activities of the human mind. People in all societies argue and debate, not only to convince others of their own opinions but also in order to explore the differences between multiple perspectives and conceptualizations, and to learn from this exploration. The process of reaching a resolution on controversial topics typically does not follow a simple sequence of purely logical steps. Rather it involves a wide variety of complex and interwoven actions. Presumably, pros and cons are identified, considered, and weighed, via cognitive processes that often involve persuasion and emotions, which are inherently harder to formalize from a computational perspective.This wide range of conceptual capabilities and activities, have only in part been studied in fields like CL and NLP, and typically within relatively small sub-communities that overlap the ACL audience. The new field of Computational Argumentation has very recently seen significant expansion within the CL and NLP community as new techniques and datasets start to become available, allowing for the first time investigation of the computational aspects of human argumentation in a holistic manner.The main goal of this tutorial would be to introduce this rapidly evolving field to the CL community. Specifically, we will aim to review recent advances in the field and to outline the challenging research questions - that are most relevant to the ACL audience - that naturally arise when trying to model human argumentation.We will further emphasize the practical value of this line of study, by considering real-world CL and NLP applications that are expected to emerge from this research, and to impact various industries, including legal, finance, healthcare, media, and education, to name just a few examples.The first part of the tutorial will provide introduction to the basics of argumentation and rhetoric. Next, we will cover fundamental analysis tasks in Computational Argumentation, including argumentation mining, revealing argument relations, assessing arguments quality, stance classification, polarity analysis, and more. After the coffee break, we will first review existing resources and recently introduced benchmark data. In the following part we will cover basic synthesis tasks in Computational Argumentation, including the relation to NLG and dialogue systems, and the evolving area of Debate Technologies, defined as technologies developed directly to enhance, support, and engage with human debating. Finally, we will present relevant demos, review potential applications, and discuss the future of this emerging field.

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Computer Aided Translation
Philipp Koehn

Moving beyond post-editing machine translation, a number of recent research efforts have advanced computer aided translation methods that allow for more interactivity, richer information such as confidence scores, and the completed feedback loop of instant adaptation of machine translation models to user translations.This tutorial will explain the main techniques for several aspects of computer aided translation: confidence measures;interactive machine translation (interactive translation prediction);bilingual concordancers;translation option display;paraphrasing (alternative translation suggestions);visualization of word alignment;online adaptation;automatic reviewing;integration of translation memory;eye tracking, logging, and cognitive user models;For each of these, the state of the art and open challenges are presented. The tutorial will also look under the hood of the open source CASMACAT toolkit that is based on MATECAT, and available as a "Home Edition" to be installed on a desktop machine. The target audience of this tutorials are researchers interested in computer aided machine translation and practitioners who want to use or deploy advanced CAT technology.

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Semantic Representations of Word Senses and Concepts
José Camacho-Collados | Ignacio Iacobacci | Chris Navigli | Roberto Taher Pilehvar

Representing the semantics of linguistic items in a machine ­interpretable form has been a major goal of Natural Language Processing since its earliest days. Among the range of different linguistic items, words have attracted the most research attention. However, word representations have an important limitation: they conflate different meanings of a word into a single vector. Representations of word senses have the potential to overcome this inherent limitation. Indeed, the representation of individual word senses and concepts has recently gained in popularity with several experimental results showing that a considerable performance improvement can be achieved across different NLP applications upon moving from word level to the deeper sense and concept levels. Another interesting point regarding the representation of concepts and word senses is that these models can be seamlessly applied to other linguistic items, such as words, phrases, sentences, etc.This tutorial will first provide a brief overview of the recent literature concerning word representation (both count based and neural network based). It will then describe the advantages of moving from the word level to the deeper level of word senses and concepts, providing an extensive review of state ­of ­the ­art systems. Approaches covered will not only include those which draw upon knowledge resources such as WordNet, Wikipedia, BabelNet or FreeBase as reference, but also the so ­called multi ­prototype approaches which learn sense distinctions by using different clustering techniques. Our tutorial will discuss the advantages and potential limitations of all approaches, showing their most successful applications to date. We will conclude by presenting current open problems and lines of future work.

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Neural Machine Translation
Thang Luong | Kyunghyun Cho | Christopher D. Manning

Neural Machine Translation (NMT) is a simple new architecture for getting machines to learn to translate. Despite being relatively new (Kalchbrenner and Blunsom, 2013; Cho et al., 2014; Sutskever et al., 2014), NMT has already shown promising results, achieving state-of-the-art performances for various language pairs (Luong et al, 2015a; Jean et al, 2015; Luong et al, 2015b; Sennrich et al., 2016; Luong and Manning, 2016). While many of these NMT papers were presented to the ACL community, research and practice of NMT are only at their beginning stage. This tutorial would be a great opportunity for the whole community of machine translation and natural language processing to learn more about a very promising new approach to MT. This tutorial has four parts.In the first part, we start with an overview of MT approaches, including: (a) traditional methods that have been dominant over the past twenty years and (b) recent hybrid models with the use of neural network components. From these, we motivate why an end-to-end approach like neural machine translation is needed. The second part introduces a basic instance of NMT. We start out with a discussion of recurrent neural networks, including the back-propagation-through-time algorithm and stochastic gradient descent optimizers, as these are the foundation on which NMT builds. We then describe in detail the basic sequence-to-sequence architecture of NMT (Cho et al., 2014; Sutskever et al., 2014), the maximum likelihood training approach, and a simple beam-search decoder to produce translations.The third part of our tutorial describes techniques to build state-of-the-art NMT. We start with approaches to extend the vocabulary coverage of NMT (Luong et al., 2015a; Jean et al., 2015; Chitnis and DeNero, 2015). We then introduce the idea of jointly learning both translations and alignments through an attention mechanism (Bahdanau et al., 2015); other variants of attention (Luong et al., 2015b; Tu et al., 2016) are discussed too. We describe a recent trend in NMT, that is to translate at the sub-word level (Chung et al., 2016; Luong and Manning, 2016; Sennrich et al., 2016), so that language variations can be effectively handled. We then give tips on training and testing NMT systems such as batching and ensembling. In the final part of the tutorial, we briefly describe promising approaches, such as (a) how to combine multiple tasks to help translation (Dong et al., 2015; Luong et al., 2016; Firat et al., 2016; Zoph and Knight, 2016) and (b) how to utilize monolingual corpora (Sennrich et al., 2016). Lastly, we conclude with challenges remained to be solved for future NMT.PS: we would also like to acknowledge the very first paper by Forcada and Ñeco (1997) on sequence-to-sequence models for translation!

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Game Theory and Natural Language: Origin, Evolution and Processing
Rocco Tripodi | Marcello Pelillo

The development of game theory in the early 1940's by John von Neumann was a reaction against the then dominant view that problems in economic theory can be formulated using standard methods from optimization theory. Indeed, most real-world economic problems involve conflicting interactions among decision-making agents that cannot be adequately captured by a single (global) objective function. The main idea behind game theory is to shift the emphasis from optimality criteria to equilibrium conditions. Game theory provides a framework to model complex scenarios, with applications in economics and social science but also in different fields of information technology. With the recent development of algorithmic game theory, it has been used to solve problems in computer vision, pattern recognition, machine learning and natural language processing.Game-theoretic frameworks have been used in different ways to study language origin and evolution. Furthermore, the so-called game metaphor has been used by philosophers and linguists to explain how language evolved and how it works. Ludwig Wittgenstein, for example, famously introduced the concept of a language game to explain the conventional nature of language, and put forward the idea of the spontaneous formation of a common language that gradually emerges from the interactions among the speakers within a population.This concept opens the way to the interpretation of language as a complex adaptive system composed of linguistic units and their interactions, which gives rise to the emergence of structural properties. It is the core part of many computational models of language that are based on classical game theory and evolutionary game theory. With the former it is possible to model how speakers form a signaling system in which the ambiguity of the symbols is minimized; with the latter it is possible to model how speakers coordinate their linguistic choices according to the satisfaction that they have about the outcome of a communication act, converging to a common language. In the same vein, many other attempts have been proposed to explain how other characteristics of language follow similar dynamics.Game theory, and in particular evolutionary game theory, thanks to their ability to model interactive situations and to integrate information from multiple sources, have also been used to solve specific problems in natural language processing and information retrieval, such as language generation, word sense disambiguation and document and text clustering.The goal of this tutorial is to offer an introduction to the basic concepts of game theory and to show its main applications in the study of language, from different perspectives. We shall assume no pre-existing knowledge of game theory by the audience, thereby making the tutorial self-contained and understandable by a non-expert.

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Understanding Short Texts
Zhongyuan Wang | Haixun Wang

Billions of short texts are produced every day, in the form of search queries, ad keywords, tags, tweets, messenger conversations, social network posts, etc. Unlike documents, short texts have some unique characteristics which make them difficult to handle. First, short texts, especially search queries, do not always observe the syntax of a written language. This means traditional NLP techniques, such as syntactic parsing, do not always apply to short texts. Second, short texts contain limited context. The majority of search queries contain less than 5 words, and tweets can have no more than 140 characters. Because of the above reasons, short texts give rise to a significant amount of ambiguity, which makes them extremely difficult to handle. On the other hand, many applications, including search engines, ads, automatic question answering, online advertising, recommendation systems, etc., rely on short text understanding. In all these applications, the necessary first step is to transform an input text into a machine-interpretable representation, namely to "understand" the short text. A growing number of approaches leverage external knowledge to address the issue of inadequate contextual information that accompanies the short texts. These approaches can be classified into two categories: Explicit Representation Model (ERM) and Implicit Representation Model (IRM). In this tutorial, we will present a comprehensive overview of short text understanding based on explicit semantics (knowledge graph representation, acquisition, and reasoning) and implicit semantics (embedding and deep learning). Specifically, we will go over various techniques in knowledge acquisition, representation, and inferencing has been proposed for text understanding, and we will describe massive structured and semi-structured data that have been made available in the recent decade that directly or indirectly encode human knowledge, turning the knowledge representation problems into a computational grand challenge with feasible solutions insight.

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MetaNet: Repository, Identification System, and Applications
Miriam R L Petruck | Ellen K Dodge

The ubiquity of metaphor in language (Lakoff and Johnson 1980) has served as impetus for cognitive linguistic approaches to the study of language, mind, and the study of mind (e.g. Thibodeau & Boroditsky 2011). While native speakers use metaphor naturally and easily, the treatment and interpretation of metaphor in computational systems remains challenging because such systems have not succeeded in developing ways to recognize the semantic elements that define metaphor. This tutorial demonstrates MetaNet's frame-based semantic analyses, and their informing of MetaNet's automatic metaphor identification system. Participants will gain a complete understanding of the theoretical basis and the practical workings of MetaNet, and acquire relevant information about the Frame Semantics basis of that knowledge base and the way that FrameNet handles the widespread phenomenon of metaphor in language. The tutorial is geared to researchers and practitioners of language technology, not necessarily experts in metaphor analysis or knowledgeable about either FrameNet or MetaNet, but who are interested in natural language processing tasks that involve automatic metaphor processing, or could benefit from exposure to tools and resources that support frame-based deep semantic, analyses of language, including metaphor as a widespread phenomenon in human language.