Welcome, testers! Thank you for helping us test the ACL 2017 conference program page.

For the first time, the program page will allow conference attendees to choose the sessions (or individual paper talks) they want to attend and generate a PDF of their customized schedule!

Instructions & Notes:
  • Click on the title of a session to expand and collapse the session. On a non-mobile browser, you can also click anywhere in the cell containing the session title.
  • Click on a tutorial/paper/poster to select it, click again to unselect it.
  • You can select more than one paper for a time slot.
  • When you hover on a paper for a time slot, it is highlighted in yellow along with the conflicting papers to make the comparison easier. This only works on non-mobile devices where parallel sessions are displayed adjacent to each other.
  • If papers are already selected for a time slot, hovering highlights them in green.
  • Click on the Generate PDF button at the bottom of the page to generate the PDF for your selected talks.
  • Since ACL 2017 doesn't have a program yet, we used the content from the NAACL 2016 conference for the purposes of testing.
  • The page has been tested on MacOS 10.12.3 on the most recent versions of Chrome, Firefox, and Safari browsers. We would like to test on other OSes (Windows, Linux) and other browsers, although older browsers (e.g., Internet Explorer <= v10) will likely not work.
  • The page has also been tested on an iPhone simulator and works as expected. However, it'd be nice to test it on Android (NOTE: only Chrome on Android will work).
  • Note that if you are using Safari, you will need to use Cmd-P to print and File > Save as ... to download the schedule. Chrome and Firefox have buttons for printing and saving as part of their PDF rendering UI.
  • The generated PDF might have some blank rows at the bottom as padding since the PDF generation has been programmed to avoid rows being split across pages.
  • While saving the generated PDF on mobile devices, its name cannot be changed.
  • Please report any issues or problems you run into here. You will need a GitHub account.
Sunday, July 30
Morning Tutorials
9:30 AM – 12:30 PM

[T1] English Resource Semantics
Executive 3AB
[T2] Multilingual Multimodal Language Processing Using Neural Networks
[T3] Question Answering with Knowledge Base, Web and Beyond
Marina 3
12:30 PM – 2:00 PM
Afternoon Tutorials
2:00 PM – 5:00 PM

[T4] Recent Progress in Deep Learning for NLP
[T5] Scalable Statistical Relational Learning for NLP
Marina 3
[T6] Statistical Machine Translation between Related Languages
Executive 3AB
Welcome Reception
6:00 PM – 9:00 PM Grande Foyer & Terrace
Monday, July 31
7:30 AM – 8:45 AM
Kevin Knight, Ani Nenkova, Owen Rambow
9:00 AM – 9:15 AM Grande Ballroom
Invited Talk: "How can NLP help cure cancer?"
Regina Barzilay
9:15 AM – 10:30 AM Grande Ballroom

Cancer inflicts a heavy toll on our society. One out of seven women will be diagnosed with breast cancer during their lifetime, a fraction of them contributing to about 450,000 deaths annually worldwide. Despite billions of dollars invested in cancer research, our understanding of the disease, treatment, and prevention is still limited.

Majority of cancer research today takes place in biology and medicine. Computer science plays a minor supporting role in this process if at all. In this talk, I hope to convince you that NLP as a field has a chance to play a significant role in this battle. Indeed, free-form text remains the primary means by which physicians record their observations and clinical findings. Unfortunately, this rich source of textual information is severely underutilized by predictive models in oncology. Current models rely primarily only on structured data.

In the first part of my talk, I will describe a number of tasks where NLP-based models can make a difference in clinical practice. For example, these include improving models of disease progression, preventing over-treatment, and narrowing down to the cure. This part of the talk draws on active collaborations with oncologists from Massachusetts General Hospital (MGH).

In the second part of the talk, I will push beyond standard tools, introducing new functionalities and avoiding annotation-hungry training paradigms ill-suited for clinical practice. In particular, I will focus on interpretable neural models that provide rationales underlying their predictions, and semi-supervised methods for information extraction.

10:30 AM – 11:00 AM
Machine Translation I
11:00 AM – 12:30 PM Grande Ballroom A

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Chair: David Chiang
11:00-11:20 Achieving Accurate Conclusions in Evaluation of Automatic Machine Translation Metrics. Yvette Graham and Qun Liu
11:20-11:40Flexible Non-Terminals for Dependency Tree-to-Tree Reordering. John Richardson, Fabien Cromieres, Toshiaki Nakazawa and Sadao Kurohashi
11:40-12:00Selecting Syntactic, Non-redundant Segments in Active Learning for Machine Translation. Akiva Miura, Graham Neubig, Michael Paul and Satoshi Nakamura
12:00-12:10Multi-Source Neural Translation. Barret Zoph and Kevin Knight
12:10-12:20Controlling Politeness in Neural Machine Translation via Side Constraints. Rico Sennrich, Barry Haddow and Alexandra Birch
12:20-12:30An Empirical Evaluation of Noise Contrastive Estimation for the Neural Network Joint Model of Translation. Colin Cherry
11:00 AM – 12:30 PM Grande Ballroom B

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Chair: Fei Liu
11:00-11:20 Neural Network-Based Abstract Generation for Opinions and Arguments. Lu Wang and Wang Ling
11:20-11:40 A Low-Rank Approximation Approach to Learning Joint Embeddings of News Stories and Images for Timeline Summarization. William Yang Wang, Yashar Mehdad, Dragomir Radev and Amanda Stent
11:40-12:00 Entity-balanced Gaussian pLSA for Automated Comparison. Danish Contractor, Parag Singla and Mausam
12:00-12:10 Automatic Summarization of Student Course Feedback. Wencan Luo, Fei Liu, Zitao Liu and Diane Litman
12:10-12:20 Abstractive Sentence Summarization with Attentive Recurrent Neural Networks. Sumit Chopra, Michael Auli and Alexander M. Rush
12:20-12:30 Knowledge-Guided Linguistic Rewrites for Inference Rule Verification. Prachi Jain and Mausam
11:00 AM – 12:30 PM Grande Ballroom C

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Chair: Mari Ostendorf
11:00-11:20 Integer Linear Programming for Discourse Parsing. Jérémy Perret, Stergos Afantenos, Nicholas Asher and Mathieu Morey
11:20-11:40 A Diversity-Promoting Objective Function for Neural Conversation Models. Jiwei Li, Michel Galley, Chris Brockett, Jianfeng Gao and Bill Dolan
11:40-12:00 Multi-domain Neural Network Language Generation for Spoken Dialogue Systems. Tsung-Hsien Wen, Milica Gasic, Nikola Mrkšić, Lina M. Rojas Barahona, Pei-Hao Su, David Vandyke and Steve Young
12:00-12:10 A Long Short-Term Memory Framework for Predicting Humor in Dialogues. Dario Bertero and Pascale Fung
12:10-12:20 Conversational Flow in Oxford-style Debates. Justine Zhang, Ravi Kumar, Sujith Ravi and Cristian Danescu-Niculescu-Mizil
12:20-12:30 Counter-fitting Word Vectors to Linguistic Constraints. Nikola Mrkšić, Diarmuid Ó Séaghdha, Blaise Thomson, Milica Gasic, Lina M. Rojas Barahona, Pei-Hao Su, David Vandyke, Tsung-Hsien Wen and Steve Young
12:30 PM – 2:00 PM
Language and Vision
2:00 PM – 3:30 PM Grande Ballroom A

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Chair: Meg Mitchell
2:00-2:20 Grounded Semantic Role Labeling. Shaohua Yang, Qiaozi Gao, Changsong Liu, Caiming Xiong, Song-Chun Zhu and Joyce Chai
2:20-2:40 Black Holes and White Rabbits: Metaphor Identification with Visual Features. Ekaterina Shutova, Douwe Kiela and Jean Maillard
2:40-3:00 Bridge Correlational Neural Networks for Multilingual Multimodal Representation Learning. Janarthanan Rajendran, Mitesh M Khapra, Sarath Chandar and Balaraman Ravindran
3:00-3:20 Unsupervised Visual Sense Disambiguation for Verbs using Multimodal Embeddings. Spandana Gella, Mirella Lapata and Frank Keller
3:20-3:30 Stating the Obvious: Extracting Visual Common Sense Knowledge. Mark Yatskar, Vicente Ordonez and Ali Farhadi
2:00 PM – 3:30 PM Grande Ballroom B

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Chair: Alexander Rush
2:00-2:20 Efficient Structured Inference for Transition-Based Parsing with Neural Networks and Error States. Ashish Vaswani and Kenji Sagae
2:20-2:40 Recurrent Neural Network Grammars. Chris Dyer, Adhiguna Kuncoro, Miguel Ballesteros and Noah A. Smith
2:40-3:00 Expected F-Measure Training for Shift-Reduce Parsing with Recurrent Neural Networks. Wenduan Xu, Michael Auli and Stephen Clark
3:00-3:20 LSTM CCG Parsing. Mike Lewis, Kenton Lee and Luke Zettlemoyer
3:20-3:30 Supertagging With LSTMs. Ashish Vaswani, Yonatan Bisk, Kenji Sagae and Ryan Musa
Named Entity Recognition
2:00 PM – 3:30 PM Grande Ballroom C

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Chair: Alessandro Moschitti
2:00-2:20 An Empirical Study of Automatic Chinese Word Segmentation for Spoken Language Understanding and Named Entity Recognition. Wencan Luo and Fan Yang
2:20-2:40 Name Tagging for Low-resource Incident Languages based on Expectation-driven Learning. Boliang Zhang, Xiaoman Pan, Tianlu Wang, Ashish Vaswani, Heng Ji, Kevin Knight and Daniel Marcu
2:40-3:00 Neural Architectures for Named Entity Recognition. Guillaume Lample, Miguel Ballesteros, Kazuya Kawakami, Sandeep Subramanian and Chris Dyer
3:00-3:20 Dynamic Feature Induction: The Last Gist to the State-of-the-Art. Jinho D. Choi
3:20-3:30 Drop-out Conditional Random Fields for Twitter with Huge Mined Gazetteer. Eun-Suk Yang, Young-Bum Kim, Ruhi Sarikaya and Yu-Seop Kim
3:30 PM – 4:00 PM
Event Detection
4:00 PM – 5:00 PM Grande Ballroom A

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Chair: Heng Ji
4:00-4:20 Joint Extraction of Events and Entities within a Document Context. Bishan Yang and Tom Mitchell
4:20-4:40 A Hierarchical Distance-dependent Bayesian Model for Event Coreference Resolution. Bishan Yang, Claire Cardie and Peter Frazier
4:40-5:00 Joint Event Extraction via Recurrent Neural Networks. Thien Huu Nguyen, Kyunghyun Cho and Ralph Grishman
Language Models
4:00 PM – 5:00 PM Grande Ballroom B

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Chair: Chris Dyer
4:00-4:20 Top-down Tree Long Short-Term Memory Networks. Xingxing Zhang, Liang Lu, Mirella Lapata
4:20-4:40 Recurrent Memory Networks for Language Modeling. Ke Tran, Arianna Bisazza, Christof Monz
4:40-5:00 A Latent Variable Recurrent Neural Network for Discourse-Driven Language Models. Yangfeng Ji, Gholamreza Haffari, Jacob Eisenstein
Non-literal Language
4:00 PM – 5:00 PM Grande Ballroom C

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Chair: Marie-Catherine de Marneffe
4:00-4:20 Questioning Arbitrariness in Language: a Data-Driven Study of Conventional Iconicity. Ekaterina Abramova and Raquel Fernandez
4:20-4:40 Distinguishing Literal and Non-Literal Usage of German Particle Verbs. Maximilian Köper and Sabine Schulte im Walde
4:40-5:00 Phrasal Substitution of Idiomatic Expressions. Changsheng Liu and Rebecca Hwa
5:00 PM – 5:15 PM
One-Minute Madness
5:15 PM – 6:00 PM Grande Ballroom

Chair: Joel Tetreault

Prior to the poster session, TACL and long-paper poster presenters will be given one minute each to pitch their paper. The poster session will immediately follow these presentations along with a buffet dinner.

Posters, Demos & Dinner
6:00 PM – 8:00 PM Pavilion

Main Conference
A Recurrent Neural Networks Approach for Estimating the Quality of Machine Translation Output. Hyun Kim and Jong-Hyeok Lee
Agreement on Target-bidirectional Neural Machine Translation. Lemao Liu, Masao Utiyama, Andrew Finch and Eiichiro Sumita
An Unsupervised Model of Orthographic Variation for Historical Document Transcription. Dan Garrette and Hannah Alpert-Abrams
Bidirectional RNN for Medical Event Detection in Electronic Health Records. Abhyuday Jagannatha and Hong Yu
Breaking the Closed World Assumption in Text Classification. Geli Fei and Bing Liu
Building Chinese Affective Resources in Valence-Arousal Dimensions. Liang-Chih Yu, Lung-Hao Lee, Shuai Hao, Jin Wang, Yunchao He, Jun Hu, K. Robert Lai and Xuejie Zhang
Combining Recurrent and Convolutional Neural Networks for Relation Classification. Ngoc Thang Vu, Heike Adel, Pankaj Gupta and Hinrich Schütze
Conversational Markers of Constructive Discussions. Vlad Niculae and Cristian Danescu-Niculescu-Mizil
Cross-lingual Wikification Using Multilingual Embeddings. Chen-Tse Tsai and Dan Roth
Deconstructing Complex Search Tasks: a Bayesian Nonparametric Approach for Extracting Sub-tasks. Rishabh Mehrotra, Prasanta Bhattacharya and Emine Yilmaz
Expectation-Regulated Neural Model for Event Mention Extraction. Ching-Yun Chang, Zhiyang Teng and Yue Zhang
Grammatical error correction using neural machine translation. Zheng Yuan and Ted Briscoe
Improved Neural Network-based Multi-label Classification with Better Initialization Leveraging Label Co-occurrence. Gakuto Kurata, Bing Xiang and Bowen Zhou
Improving event prediction by representing script participants. Simon Ahrendt and Vera Demberg
Individual Variation in the Choice of Referential Form. Thiago Castro Ferreira, Emiel Krahmer and Sander Wubben
Inferring Psycholinguistic Properties of Words. Gustavo Paetzold and Lucia Specia
Intra-Topic Variability Normalization based on Linear Projection for Topic Classification. Quan Liu, Wu Guo, Zhen-Hua Ling, Hui Jiang and Yu Hu
Joint Learning Templates and Slots for Event Schema Induction. Lei Sha, Sujian Li, Baobao Chang, Zhifang Sui and Zhifang Sui
Large-scale Multitask Learning for Machine Translation Quality Estimation. Kashif Shah and Lucia Specia
Learning Distributed Word Representations For Bidirectional LSTM Recurrent Neural Network. Peilu Wang, Yao Qian, Frank Soong, Lei He and Hai Zhao
Leverage Financial News to Predict Stock Price Movements Using Word Embeddings and Deep Neural Networks. Yangtuo Peng and Hui Jiang
Multimodal Semantic Learning from Child-Directed Input. Angeliki Lazaridou, Grzegorz Chrupała, Raquel Fernandez and Marco Baroni
Online Multilingual Topic Models with Multi-Level Hyperpriors. Kriste Krstovski, David Smith and Michael J. Kurtz
Psycholinguistic Features for Deceptive Role Detection in Werewolf. Codruta Girlea, Roxana Girju and Eyal Amir
Recurrent Support Vector Machines For Slot Tagging In Spoken Language Understanding. Yangyang Shi, Kaisheng Yao, Hu Chen, Dong Yu, Yi-Cheng Pan and Mei-Yuh Hwang
STransE: a novel embedding model of entities and relationships in knowledge bases. Dat Quoc Nguyen, Kairit Sirts, Lizhen Qu and Mark Johnson
Sequential Short-Text Classification with Recurrent and Convolutional Neural Networks. Ji Young Lee and Franck Dernoncourt
Shift-Reduce CCG Parsing using Neural Network Models. Bharat Ram Ambati, Tejaswini Deoskar and Mark Steedman
Structured Prediction with Output Embeddings for Semantic Image Annotation. Ariadna Quattoni, Arnau Ramisa, Pranava Swaroop Madhyastha, Edgar Simo-Serra and Francesc Moreno-Noguer
Symmetric Patterns and Coordinations: Fast and Enhanced Representations of Verbs and Adjectives. Roy Schwartz, Roi Reichart and Ari Rappoport
The Sensitivity of Topic Coherence Evaluation to Topic Cardinality. Jey Han Lau and Timothy Baldwin
Transition-Based Syntactic Linearization with Lookahead Features. Ratish Puduppully, Yue Zhang and Manish Shrivastava
Vision and Feature Norms: Improving automatic feature norm learning through cross-modal maps. Luana Bulat, Douwe Kiela and Stephen Clark
Student Research Workshop
An End-to-end Approach to Learning Semantic Frames with Feedforward Neural Network. Yukun Feng, Yipei Xu and Dong Yu
Analogy-based detection of morphological and semantic relations with word embeddings: what works and what doesn't. Anna Gladkova, Aleksandr Drozd and Satoshi Matsuoka
Argument Identification in Chinese Editorials. Marisa Chow
Automatic tagging and retrieval of E-Commerce products based on visual features. Vasu Sharma and Harish Karnick
Combining syntactic patterns and Wikipedia's hierarchy of hyperlinks to extract relations: The case of meronymy extraction. Debela Tesfaye Gemechu, Michael Zock and Solomon Teferra
Data-driven Paraphrasing and Stylistic Harmonization. Gerold Hintz
Detecting 'Smart' Spammers on Social Network: A Topic Model Approach. Linqing Liu, Yao Lu, Ye Luo, Renxian Zhang, Laurent Itti and Jianwei Lu
Developing language technology tools and resources for a resource-poor language: Sindhi. Raveesh Motlani
System Demonstrations
rstWeb - A Browser-based Annotation Interface for Rhetorical Structure Theory and Discourse Relations. Amir Zeldes
Instant Feedback for Increasing the Presence of Solutions in Peer Reviews. Huy Nguyen, Wenting Xiong and Diane Litman
Farasa: A Fast and Furious Segmenter for Arabic. Ahmed Abdelali, Kareem Darwish, Nadir Durrani and Hamdy Mubarak
iAppraise: A Manual Machine Translation Evaluation Environment Supporting Eye-tracking. Ahmed Abdelali, Nadir Durrani and Francisco Guzmán
Linguistica 5: Unsupervised Learning of Linguistic Structure. Jackson Lee and John Goldsmith
TransRead: Designing a Bilingual Reading Experience with Machine Translation Technologies. François Yvon, Yong Xu, Marianna Apidianaki, Clément Pillias and Pierre Cubaud
New Dimensions in Testimony Demonstration. Ron Artstein, Alesia Gainer, Kallirroi Georgila, Anton Leuski, Ari Shapiro and David Traum
ArgRewrite: A Web-based Revision Assistant for Argumentative Writings. Fan Zhang, Rebecca Hwa, Diane Litman and Homa B. Hashemi
Scaling Up Word Clustering. Jon Dehdari, Liling Tan and Josef van Genabith
Task Completion Platform: A self-serve multi-domain goal oriented dialogue platform. Paul Crook, Alex Marin, Vipul Agarwal, Khushboo Aggarwal, Tasos Anastasakos, Ravi Bikkula, Daniel Boies, Asli Celikyilmaz, Senthilkumar Chandramohan, Zhaleh Feizollahi, Roman Holenstein, Minwoo Jeong, Omar Khan, Young-Bum Kim, Elizabeth Krawczyk, Xiaohu Liu, Danko Panic, Vasiliy Radostev, Nikhil Ramesh, Jean-Phillipe Robichaud, Alexandre Rochette, Logan Stromberg and Ruhi Sarikaya
Tuesday, August 1
7:30 AM – 8:45 AM
Semantic Parsing
9:00 AM – 10:30 AM Grande Ballroom A

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Chair: Mike Lewis
9:00-9:20 Transforming Dependency Structures to Logical Forms for Semantic Parsing. Siva Reddy, Oscar Täckström, Michael Collins, Tom Kwiatkowski, Dipanjan Das, Mark Steedman and Mirella Lapata
9:20-9:40 Imitation Learning of Agenda-based Semantic Parsers. Jonathan Berant and Percy Liang
9:40-10:00 Probabilistic Models for Learning a Semantic Parser Lexicon. Jayant Krishnamurthy
10:00-10:20 Semantic Parsing of Ambiguous Input through Paraphrasing and Verification. Philip Arthur, Graham Neubig, Sakriani Sakti, Tomoki Toda and Satoshi Nakamura
10:20-10:30 Unsupervised Compound Splitting With Distributional Semantics Rivals Supervised Methods. Martin Riedl and Chris Biemann
Morphology & Phonology
9:00 AM – 10:30 AM Grande Ballroom B

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Chair: Dilek Hakkani-Tur
9:00-9:20 Weighting Finite-State Transductions With Neural Context. Pushpendre Rastogi, Ryan Cotterell and Jason Eisner
9:20-9:40 Morphological Inflection Generation Using Character Sequence to Sequence Learning. Manaal Faruqui, Yulia Tsvetkov, Graham Neubig and Chris Dyer
9:40-10:00 Towards Unsupervised and Language-independent Compound Splitting using Inflectional Morphological Transformations. Patrick Ziering and Lonneke van der Plas
10:00-10:20 Phonological Pun-derstanding. Aaron Jaech, Rik Koncel-Kedziorski and Mari Ostendorf
10:20-10:30 A Joint Model of Orthography and Morphological Segmentation. Ryan Cotterell, Tim Vieira and Hinrich Schütze
9:00 AM – 10:30 AM Grande Ballroom C

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Chair: Jinho Choi
9:00-9:20 Syntactic Parsing of Web Queries with Question Intent. Yuval Pinter, Roi Reichart and Idan Szpektor
9:20-9:40 Visualizing and Understanding Neural Models in NLP. Jiwei Li, Xinlei Chen, Eduard Hovy and Dan Jurafsky
9:40-10:00 Bilingual Word Embeddings from Parallel and Non-parallel Corpora for Cross-Language Text Classification. Aditya Mogadala and Achim Rettinger
10:00-10:20 Joint Learning with Global Inference for Comment Classification in Community Question Answering. Shafiq Joty, Lluís Màrquez and Preslav Nakov
10:20-10:30 Weak Semi-Markov CRFs for Noun Phrase Chunking in Informal Text Aldrian. Obaja Muis and Wei Lu
10:30 AM – 11:00 AM
11:00 AM – 12:30 PM Grande Ballroom A

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Chair: Lu Wang
11:00-11:20 What to talk about and how? Selective Generation using LSTMs with Coarse-to-Fine Alignment. Hongyuan Mei, Mohit Bansal and Matthew Walter
11:20-11:40 Generation from Abstract Meaning Representation using Tree Transducers. Jeffrey Flanigan, Chris Dyer, Noah A. Smith and Jaime Carbonell
11:40-12:00 A Corpus and Semantic Parser for Multilingual Natural Language Querying of OpenStreetMap. Carolin Haas and Stefan Riezler
12:00-12:20 Natural Language Communication with Robots. Yonatan Bisk, Daniel Marcu and Deniz Yuret
12:20-12:30 Inter-document Contextual Language model. Quan Hung Tran, Ingrid Zukerman and Gholamreza Haffari
11:00 AM – 12:30 PM Grande Ballroom B

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Chair: Ellen Riloff
11:00-11:20 Ultradense Word Embeddings by Orthogonal Transformation. Sascha Rothe, Sebastian Ebert and Hinrich Schütze
11:20-11:40 Separating Actor-View from Speaker-View Opinion Expressions using Linguistic Features. Michael Wiegand, Marc Schulder and Josef Ruppenhofer
11:40-12:00 Clustering for Simultaneous Extraction of Aspects and Features from Reviews. Lu Chen, Justin Martineau, Doreen Cheng and Amit Sheth
12:00-12:20 Opinion Holder and Target Extraction on Opinion Compounds -- A Linguistic Approach. Michael Wiegand, Christine Bocionek and Josef Ruppenhofer
12:20-12:30 Capturing Reliable Fine-Grained Sentiment Associations by Crowdsourcing and Best-Worst Scaling. Svetlana Kiritchenko and Saif Mohammad
Knowledge Acquisition
11:00 AM – 12:30 PM Grande Ballroom C

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Chair: Ray Mooney
11:00-11:20 Concept Grounding to Multiple Knowledge Bases via Indirect Supervision. Chen-Tse Tsai and Dan Roth
11:20-11:40 Mapping Verbs in Different Languages to Knowledge Base Relations using Web Text as Interlingua. Derry Tanti Wijaya and Tom Mitchell
11:40-12:00 Comparing Convolutional Neural Networks to Traditional Models for Slot Filling. Heike Adel, Benjamin Roth and Hinrich Schütze
12:00-12:20 A Corpus and Cloze Evaluation for Deeper Understanding of Commonsense Stories. Nasrin Mostafazadeh, Nathanael Chambers, Xiaodong He, Devi Parikh, Dhruv Batra, Lucy Vanderwende, Pushmeet Kohli and James Allen
12:20-12:30 Dynamic Entity Representation with Max-pooling Improves Machine Reading. Sosuke Kobayashi, Ran Tian, Naoaki Okazaki and Kentaro Inui
12:30 PM – 1:15 PM
Panel Discussion: How Will Deep Learning Change Computational Linguistics?
1:15 PM – 2:15 PM
Grande Ballroom

Moderator: Jason Eisner
Panelists: Kyunghyun Cho, Chris Dyer, Pascale Fung, Heng Ji
  • What are the big problems in NLP historically, now, and in the future? (What do we need to solve, regardless of the approach for solving it?)
  • What current NLP problems has DL solved, or where has DL made an important contribution towards improving the state of the art?
  • Does DL guide NLP towards new problems? Do we already have examples? Do you want to speculate? (Have a new hammer, looking for un-hammered nails.)
  • Does DL change our methodology profoundly, or is it just another machine learning method? Is there a greater danger of overfitting because of the massive tuning required? Given the computational requirements, are off-the-shelf tools incorporating DL practical?
  • Is the use of off-the-shelf word embeddings the major contribution of DL? Does every task in which in the past we had bag of words features now required to also use word embedding features?
  • Is linguistics obsolete because DL will find better representations on its own? Or should DL be combined with traditional representations of latent linguistic structure? What is the best way to do that - hybrid architectures, hybrid training objectives, hand-designed input representations, or something else?
  • Is DL mostly good for supervised mapping of input to output where very large training sets are available? Or can it also help for semi-supervised learning and unsupervised structure discovery?
  • What are the best approaches to interpretability (explaining why a DL system made a particular decision)? What are the best approaches to understanding the latent representations and figuring out what the system is missing and how to fix that?
  • How much do architectures and parameters need to be task-specific? How much can researchers reuse architectures, and learning algorithms reuse parameters, across tasks?
  • A DL design that looks nice on paper often doesn't work right away. What are best practices for achieving good performance? Do experienced researchers not have this problem because they know more tricks of the trade and have better intuitions about hyperparameters? Or does every paper involve 6 months of fiddling around on a dev set until it works? Is it worth doing automatic tuning of hyperparameters, e.g., Bayesian optimization?
Machine Translation II
2:30 PM – 3:30 PM Grande Ballroom A

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Chair: Colin Cherry
2:30-2:50 Speed-Constrained Tuning for Statistical Machine Translation Using Bayesian Optimization. Daniel Beck, Adrià de Gispert, Gonzalo Iglesias, Aurelien Waite and Bill Byrne
2:50-3:10 Multi-Way, Multilingual Neural Machine Translation with a Shared Attention Mechanism. Orhan Firat, Kyunghyun Cho and Yoshua Bengio
3:10-3:30 Incorporating Structural Alignment Biases into an Attentional Neural Translation Model. Trevor Cohn, Cong Duy Vu Hoang, Ekaterina Vymolova, Kaisheng Yao, Chris Dyer and Gholamreza Haffari
Relation Extraction
2:30 PM – 3:30 PM Grande Ballroom B

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Chair: Byron Wallace
2:30-2:50 Multilingual Relation Extraction using Compositional Universal Schema. Patrick Verga, David Belanger, Emma Strubell, Benjamin Roth and Andrew McCallum
2:50-3:10 Effective Crowd Annotation for Relation Extraction. Angli Liu, Stephen Soderland, Jonathan Bragg, Christopher Lin, Xiao Ling and Daniel Weld
3:10-3:30 A Translation-Based Knowledge Graph Embedding Preserving Logical Property of Relations. Hee-Geun Yoon, Hyun-Je Song, Seong-Bae Park and Se-Young Park
Semantic Similarity
2:30 PM – 3:30 PM Grande Ballroom C

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Chair: Dipanjan Das
2:30-2:50 DAG-Structured Long Short-Term Memory for Semantic Compositionality. Xiaodan Zhu, Parinaz Sobhani and Hongyu Guo
2:50-3:10 Bayesian Supervised Domain Adaptation for Short Text Similarity. Md Arafat Sultan, Jordan Boyd-Graber and Tamara Sumner
3:10-3:30 Pairwise Word Interaction Modeling with Deep Neural Networks for Semantic Similarity Measurement. Hua He and Jimmy Lin
3:30 PM – 4:00 PM
Machine Translation III
4:00 PM – 5:00 PM Grande Ballroom A

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Chair: Marine Carpuat
4:00-4:20 An Attentional Model for Speech Translation Without Transcription. Long Duong, Antonios Anastasopoulos, David Chiang, Steven Bird and Trevor Cohn
4:20-4:40 Information Density and Quality Estimation Features as Translationese Indicators for Human Translation Classification. Raphael Rubino, Ekaterina Lapshinova-Koltunski and Josef van Genabith
4:40-4:50 Interpretese vs. Translationese: The Uniqueness of Human Strategies in Simultaneous Interpretation. He He, Jordan Boyd-Graber and Hal Daumé III
4:50-5:00 LSTM Neural Reordering Feature for Statistical Machine Translation. Yiming Cui, Shijin Wang and Jianfeng Li
Anaphora Resolution
4:00 PM – 5:00 PM Grande Ballroom B

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Chair: Vincent Ng
4:00-4:20 A Novel Approach to Dropped Pronoun Translation. Longyue Wang, Zhaopeng Tu, Xiaojun Zhang, Hang Li, Andy Way and Qun Liu
4:20-4:40 Learning Global Features for Coreference Resolution. Sam Wiseman, Alexander M. Rush and Stuart Shieber
4:40-4:50 Search Space Pruning: A Simple Solution for Better Coreference Resolvers. Nafise Sadat Moosavi and Michael Strube
4:50-5:00 Unsupervised Ranking Model for Entity Coreference Resolution. Xuezhe Ma, Zhengzhong Liu and Eduard Hovy
Word Embeddings I
4:00 PM – 5:00 PM Grande Ballroom C

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Chair: Manaal Faruqui
4:00-4:20 Embedding Lexical Features via Low-Rank Tensors. Mo Yu, Mark Dredze, Raman Arora and Matthew R. Gormley
4:20-4:40 The Role of Context Types and Dimensionality in Learning Word Embeddings. Oren Melamud, David McClosky, Siddharth Patwardhan and Mohit Bansal
4:40-5:00 Improve Chinese Word Embeddings by Exploiting Internal Structure. Jian Xu, Jiawei Liu, Liangang Zhang, Zhengyu Li and Huanhuan Chen
5:00 PM – 5:15 PM
One-Minute Madness
5:15 PM – 6:00 PM Grande Ballroom

Chair: Joel Tetreault

Prior to the poster session, TACL and long-paper poster presenters will be given one minute each to pitch their paper. The poster session will immediately follow these presentations along with a buffet dinner.

Posters, Demos & Dinner
6:00 PM – 8:00 PM Pavilion

Main Conference
Assessing Relative Sentence Complexity using an Incremental CCG Parser. Bharat Ram Ambati, Siva Reddy and Mark Steedman
Automatic Prediction of Linguistic Decline in Writings of Subjects with Degenerative Dementia. Davy Weissenbacher, Travis A. Johnson, Laura Wojtulewicz, Amylou Dueck, Dona Locke, Richard Caselli and Graciela Gonzalez
Automatically Inferring Implicit Properties in Similes. Ashequl Qadir, Ellen Riloff and Marilyn Walker
BIRA: Improved Predictive Exchange Word Clustering. Jon Dehdari, Liling Tan and Josef van Genabith
Bootstrapping Translation Detection and Sentence Extraction from Comparable Corpora. Kriste Krstovski and David Smith
Capturing Semantic Similarity for Entity Linking with Convolutional Neural Networks. Matthew Francis-Landau, Greg Durrett and Dan Klein
Consensus Maximization Fusion of Probabilistic Information Extractors. Miguel Rodriguez, Sean Goldberg and Daisy Zhe Wang
Cross-genre Event Extraction with Knowledge Enrichment. Hao Li and Heng Ji
Deep Lexical Segmentation and Syntactic Parsing in the Easy-First Dependency Framework. Matthieu Constant, Joseph Le Roux and Nadi Tomeh
Discriminative Reranking for Grammatical Error Correction with Statistical Machine Translation. Tomoya Mizumoto and Yuji Matsumoto
Emergent: a novel data-set for stance classification. William Ferreira and Andreas Vlachos
Eyes Don't Lie: Predicting Machine Translation Quality Using Eye Movement. Hassan Sajjad, Francisco Guzmán, Nadir Durrani, Ahmed Abdelali, Houda Bouamor, Irina Temnikova and Stephan Vogel
Fast and Easy Short Answer Grading with High Accuracy. Md Arafat Sultan, Cristobal Salazar and Tamara Sumner
Frustratingly Easy Cross-Lingual Transfer for Transition-Based Dependency Parsing. Ophélie Lacroix, Lauriane Aufrant, Guillaume Wisniewski and François Yvon
Geolocation for Twitter: Timing Matters. Mark Dredze, Miles Osborne and Prabhanjan Kambadur
Incorporating Side Information into Recurrent Neural Network Language Models. Cong Duy Vu Hoang, Trevor Cohn and Gholamreza Haffari
Integrating Morphological Desegmentation into Phrase-based Decoding. Mohammad Salameh, Colin Cherry and Grzegorz Kondrak
Interlocking Phrases in Phrase-based Statistical Machine Translation. Ye Kyaw Thu, Andrew Finch and Eiichiro Sumita
K-Embeddings: Learning Conceptual Embeddings for Words using Context. Thuy Vu and D. Stott Parker
Learning Composition Models for Phrase Embeddings. Mo Yu and Mark Dredze
Learning a POS tagger for AAVE-like language. Anna Jørgensen, Dirk Hovy and Anders Søgaard
Learning to Recognize Ancillary Information for Automatic Paraphrase Identification. Simone Filice and Alessandro Moschitti
MAWPS: A Math Word Problem Repository. Rik Koncel-Kedziorski, Subhro Roy, Aida Amini, Nate Kushman and Hannaneh Hajishirzi
Making Dependency Labeling Simple, Fast and Accurate. Tianxiao Shen, Tao Lei and Regina Barzilay
PIC a Different Word: A Simple Model for Lexical Substitution in Context. Stephen Roller and Katrin Erk
PRIMT: A Pick-Revise Framework for Interactive Machine Translation. Shanbo Cheng, Shujian Huang, Huadong Chen, Xin-Yu Dai and Jiajun Chen
Patterns of Wisdom: Discourse-Level Style in Multi-Sentence Quotations. Kyle Booten and Marti A. Hearst
Right-truncatable Neural Word Embeddings. Jun Suzuki and Masaaki Nagata
Sentiment Composition of Words with Opposing Polarities. Svetlana Kiritchenko and Saif Mohammad
Simple, Fast Noise-Contrastive Estimation for Large RNN Vocabularies. Barret Zoph, Ashish Vaswani, Jonathan May and Kevin Knight
Sparse Bilingual Word Representations for Cross-lingual Lexical Entailment. Yogarshi Vyas and Marine Carpuat
The Instantiation Discourse Relation: A Corpus Analysis of Its Properties and Improved Detection. Junyi Jessy Li and Ani Nenkova
Visual Storytelling. Ting-Hao Huang, Francis Ferraro, Nasrin Mostafazadeh, Ishan Misra, Jacob Devlin, Aishwarya Agrawal, Ross Girshick, Xiaodong He, Pushmeet Kohli, Dhruv Batra, Larry Zitnick, Devi Parikh, Lucy Vanderwende, Michel Galley and Margaret Mitchell
Student Research Workshop
Effects of Communicative Pressures on Novice L2 Learners' Use of Optional Formal Devices. Yoav Binoun, Francesca Delogu, Clayton Greenberg, Mindaugas Mozuraitis and Matthew Crocker
Explicit Argument Identification for Discourse Parsing In Hindi: A Hybrid Pipeline. Rohit Jain and Dipti Sharma
Exploring Fine-Grained Emotion Detection in Tweets. Jasy Suet Yan Liew and Howard Turtle
Extraction of Bilingual Technical Terms for Chinese-Japanese Patent Translation. Wei Yang, Jinghui Yan and Yves Lepage
Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter. Zeerak Waseem and Dirk Hovy
Non-decreasing Sub-modular Function for Comprehensible Summarization. Litton JKurisinkel, Pruthwik Mishra, Vigneshwaran Muralidaran, Vasudeva Varma and Dipti Misra Sharma
Phylogenetic simulations over constraint-based grammar formalisms. Andrew Lamont and Jonathan Washington
Question Answering over Knowledge Base using Weakly Supervised Memory Networks. Sarthak Jain
Using Related Languages to Enhance Statistical Language Models. Anna Currey, Alina Karakanta and Jon Dehdari
System Demonstrations
Illinois Math Solver: Math Reasoning on the Web. Subhro Roy and Dan Roth
LingoTurk: managing crowdsourced tasks for psycholinguistics. Florian Pusse, Asad Sayeed and Vera Demberg
Sentential Paraphrasing as Black-Box Machine Translation. Courtney Napoles, Chris Callison-Burch and Matt Post
A Tag-based English Math Word Problem Solver with Understanding, Reasoning and Explanation. Chao-Chun Liang, Kuang-Yi Hsu, Chien-Tsung Huang, Chung-Min Li, Shen-Yu Miao and Keh-Yih Su
Cross-media Event Extraction and Recommendation. Di Lu, Clare Voss, Fangbo Tao, Xiang Ren, Rachel Guan, Rostyslav Korolov, Tongtao Zhang, Dongang Wang, Hongzhi Li, Taylor Cassidy, Heng Ji, Shih-fu Chang, Jiawei Han, William Wallace, James Hendler, Mei Si and Lance Kaplan
SODA: Service Oriented Domain Adaptation Architecture for Microblog Categorization. Himanshu Sharad Bhatt, Sandipan Dandapat, Peddamuthu Balaji, Shourya Roy, Sharmistha Jat and Deepali Semwal
Lecture Translator - Speech translation framework for simultaneous lecture translation. Markus Müller, Thai Son Nguyen, Jan Niehues, Eunah Cho, Bastian Krüger, Thanh-Le Ha, Kevin Kilgour, Matthias Sperber, Mohammed Mediani, Sebastian Stüker and Alex Waibel
Zara The Supergirl: An Empathetic Personality Recognition System. Pascale Fung, Anik Dey, Farhad Bin Siddique, Ruixi Lin, Yang Yang, Yan Wan and Ho Yin Ricky Chan
Kathaa: A Visual Programming Framework for NLP Applications. Sharada Prasanna Mohanty, Nehal J Wani, Manish Srivastava and Dipti Misra Sharma
"Why Should I Trust You?": Explaining the Predictions of Any Classifier. Marco Ribeiro, Sameer Singh and Carlos Guestrin
Social Event
8:00 PM – 10:00 PM Bayview Lawn

Included in registration

Enjoy a fun evening under the stars!

Bring your Flower Power to our SoCal Beach Party! After the main dinner and Poster Session, join us on the Bayview Lawn adjacent to the Pavilion for desserts, coffee, tea, and drinks (cash bar). A Beach Boys style band will entertain you when you are not busy in the VW Bus Photo Booth, talking amongst your friends and colleagues, or playing with the beach balls.

Learn more about the social event here.

Wednesday, August 2
7:30 AM – 8:45 AM
Invited Talk: Evaluating Natural Language Generation Systems
Ehud Reiter
9:00 AM – 10:15 AM Grande Ballroom

Natural Language Generation (NLG) systems have different characteristics than other NLP systems, which effects how they are evaluated. In particular, it can be difficult to meaningfully evaluate NLG texts by comparing them against gold-standard reference texts, because (A) there are usually many possible texts which are acceptable to users and (B) some NLG systems produce texts which are better (as judged by human users) than human-written corpus texts. Partially because of these reasons, the NLG community places much more emphasis on human-based evaluations than most areas of NLP.

I will discuss the various ways in which NLG systems are evaluated, focusing on human-based evaluations. These typically either measure the success of generated texts at achieving a goal (eg, measuring how many people change their behaviour after reading behaviour-change texts produced by an NLG system); or ask human subjects to rate various aspects of generated texts (such as readability, accuracy, and appropriateness), often on Likert scales. I will use examples from evaluations I have carried out, and highlight some of the lessons I have learnt, including the importance of reporting negative results, the difference between laboratory and real-world evaluations, and the need to look at worse-case as well as average-case performance. I hope my talk will be interesting and relevant to anyone who is interested in the evaluation of NLP systems.

10:15 AM – 10:45 AM
Question Answering
10:45 AM – 12:15 PM Grande Ballroom A

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Chair: Ed Hovy
10:45-11:05 A Joint Model for Answer Sentence Ranking and Answer Extraction. Md Arafat Sultan, Vittorio Castelli and Radu Florian
11:05-11:25 Convolutional Neural Networks vs. Convolution Kernels: Feature Engineering for Answer Sentence Reranking. Kateryna Tymoshenko, Daniele Bonadiman and Alessandro Moschitti
11:25-11:45 Semi-supervised Question Retrieval with Gated Convolutions. Tao Lei, Hrishikesh Joshi, Regina Barzilay, Tommi Jaakkola, Kateryna Tymoshenko, Alessandro Moschitti and Lluís Màrquez
11:45-12:05 Parsing Algebraic Word Problems into Equations. Rik Koncel-Kedziorski, Hannaneh Hajishirzi, Ashish Sabharwal, Oren Etzioni and Siena Dumas Ang
12:05-12:15 This is how we do it: Answer Reranking for Open-domain How Questions with Paragraph Vectors and Minimal Feature Engineering. Dasha Bogdanova and Jennifer Foster
Multilingual Processing
10:45 AM – 12:15 PM Grande Ballroom B

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Chair: Mohit Bansal
10:45-11:05 Multilingual Language Processing From Bytes. Daniel Gillick, Cliff Brunk, Oriol Vinyals and Amarnag Subramanya
11:05-11:25 Ten Pairs to Tag -- Multilingual POS Tagging via Coarse Mapping between Embeddings. Yuan Zhang, David Gaddy, Regina Barzilay and Tommi Jaakkola
11:25-11:45 Part-of-Speech Tagging for Historical English. Yi Yang and Jacob Eisenstein
11:45-12:05 Statistical Modeling of Creole Genesis. Yugo Murawaki
12:05-12:15 Shallow Parsing Pipeline - Hindi-English Code-Mixed Social Media Text. Arnav Sharma, Sakshi Gupta, Raveesh Motlani, Piyush Bansal, Manish Shrivastava, Radhika Mamidi and Dipti Sharma
Word Embeddings II
10:45 AM – 12:15 PM Grande Ballroom C

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Chair: Hinrich Schütze
10:45-11:05 Bilingual Learning of Multi-sense Embeddings with Discrete Autoencoders. Simon Suster, Ivan Titov and Gertjan van Noord
11:05-11:25 Polyglot Neural Language Models: A Case Study in Cross-Lingual Phonetic Representation Learning. Yulia Tsvetkov, Sunayana Sitaram, Manaal Faruqui, Guillaume Lample, Patrick Littell, David R. Mortensen, Alan W Black, Lori Levin and Chris Dyer
11:25-11:45 Learning Distributed Representations of Sentences from Unlabelled Data. Felix Hill, Kyunghyun Cho and Anna Korhonen
11:45-12:05 Learning to Understand Phrases by Embedding the Dictionary. Felix Hill, Kyunghyun Cho, Anna Korhonen and Yoshua Bengio
12:05-12:15 Retrofitting Sense-Specific Word Vectors Using Parallel Text. Allyson Ettinger, Philip Resnik and Marine Carpuat
12:15 PM – 1:00 PM
NAACL Business Meeting
All attendees are encouraged to participate in the business meeting.
1:00 PM – 2:00 PM
Grande Ballroom A
Argumentation & Discourse Relations
2:15 PM – 3:45 PM Grande Ballroom A

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Chair: Cristian Danescu-Niculescu-Mizil
2:15-2:35 End-to-End Argumentation Mining in Student Essays. Isaac Persing and Vincent Ng
2:35-2:55 Cross-Domain Mining of Argumentative Text through Distant Supervision. Khalid Al Khatib, Henning Wachsmuth, Matthias Hagen, Jonas Köhler and Benno Stein
2:55-3:15 A Study of the Impact of Persuasive Argumentation in Political Debates. Amparo Elizabeth Cano Basave and Yulan Hu
3:15-3:35 Lexical Coherence Graph Modeling Using Word Embeddings. Mohsen Mesgar and Michael Strube
3:35-3:45 Using Context to Predict the Purpose of Argumentative Writing Revisions. Fan Zhang and Diane Litman
Misc. Semantics
2:15 PM – 3:45 PM Grande Ballroom B

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Chair: Steven Bethard
2:15-2:35 Automatic Generation and Scoring of Positive Interpretations from Negated Statements. Eduardo Blanco and Zahra Sarabi
2:35-2:55 Learning Natural Language Inference with LSTM. Shuohang Wang and Jing Jiang
2:55-3:15 Activity Modeling in Email. Ashequl Qadir, Michael Gamon, Patrick Pantel and Ahmed Awadallah
3:15-3:35 Clustering Paraphrases by Word Sense. Anne Cocos and Chris Callison-Burch
3:35-3:45 Unsupervised Learning of Prototypical Fillers for Implicit Semantic Role Labeling. Niko Schenk and Christian Chiarcos
Text Categorization
2:15 PM – 3:45 PM Grande Ballroom C

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Chair: Jacob Eisenstein
2:15-2:35 Hierarchical Attention Networks for Document Classification. Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alex Smola and Eduard Hovy
2:35-2:55 Dependency Based Embeddings for Sentence Classification Tasks. Alexandros Komninos and Suresh Manandhar
2:55-3:15 Deep LSTM based Feature Mapping for Query Classification. Yangyang Shi, Kaisheng Yao, Le Tian and Daxin Jiang
3:15-3:35 Dependency Sensitive Convolutional Neural Networks for Modeling Sentences and Documents. Rui Zhang, Honglak Lee and Dragomir Radev
3:35-3:45 MGNC-CNN: A Simple Approach to Exploiting Multiple Word Embeddings for Sentence Classification. Ye Zhang, Stephen Roller and Byron C. Wallace
3:45 PM – 4:15 PM
Best Papers Presentation
4:15 PM – 5:45 PM Grande Ballroom

Chair: Owen Rambow

Best Short Paper
4:15-4:35 Improving sentence compression by learning to predict gaze. Sigrid Klerke, Yoav Goldberg and Anders Søgaard
Best Long Papers
4:35-5:05 Feuding Families and Former Friends; Unsupervised Learning for Dynamic Fictional Relationships. Mohit Iyyer, Anupam Guha, Snigdha Chaturvedi, Jordan Boyd-Graber and Hal Daumé III
5:05-5:35 Learning to Compose Neural Networks for Question Answering. Jacob Andreas, Marcus Rohrbach, Trevor Darrell and Dan Klein
Closing Remarks
5:35 PM – 5:45 PM Grande Ballroom
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