CoNLL 2017

August 3-4, 2017
Vancouver, Canada

CoNLL is a top-tier conference, yearly organized by SIGNLL (ACL's Special Interest Group on Natural Language Learning). This year, CoNLL will be colocated with ACL 2017 in Vancouver, Canada. The special focus of this edition is on statistical, cognitive and grammatical inference.

CoNLL 2017 Chairs

Shared Tasks

In 2017, CoNLL will have two associated shared tasks.

Accepted Papers

A Joint Model for Semantic Sequences: Frames, Entities, Sentiments
  Haoruo Peng, Snigdha Chaturvedi and Dan Roth
A phoneme clustering algorithm based on the obligatory contour principle
  Mans Hulden
A Probabilistic Generative Grammar for Semantic Parsing
  Abulhair Saparov, Vijay Saraswat and Tom Mitchell
A Simple and Accurate Syntax-Agnostic Neural Model for Dependency-based Semantic Role Labeling
  Diego Marcheggiani, Anton Frolov and Ivan Titov
A Supervised Approach to Extractive Summarisation of Scientific Papers
  Ed Collins, Isabelle Augenstein and Sebastian Riedel
An Artificial Language Evaluation of Distributional Semantic Models
  Fatemeh Torabi Asr and Michael Jones
An Automatic Approach for Document-level Topic Model Evaluation
  Shraey Bhatia, Jey Han Lau and Timothy Baldwin
Attention-based Recurrent Convolutional Neural Network for Automatic Essay Scoring
  Fei Dong, Yue Zhang and Jie Yang
Automatic Selection of Context Configurations for Improved Class-Specific Word Representations
  Ivan Vulić, Roy Schwartz, Ari Rappoport, Roi Reichart and Anna Korhonen
Collaborative Partitioning for Coreference Resolution
  Olga Uryupina and Alessandro Moschitti
Cross-language Learning with Adversarial Neural Networks
  Shafiq Joty, Preslav Nakov and Lluís Màrquez
Embedding Words and Senses Together via Joint Knowledge-Enhanced Training
  Massimiliano Mancini, Jose Camacho-Collados, Ignacio Iacobacci and Roberto Navigli
Encoding of phonology in a recurrent neural model of grounded speech
  Afra Alishahi, Marie Barking and Grzegorz Chrupała
Exploring the Syntactic Abilities of RNNs with Multi-task Learning
  Émile Enguehard, Yoav Goldberg and Tal Linzen
Feature Selection as Causal Inference: Experiments with Text Classification
  Michael J. Paul
German in Flux: Detecting Metaphoric Change via Word Entropy
  Dominik Schlechtweg, Stefanie Eckmann, Enrico Santus, Sabine Schulte im Walde and Daniel Hole
Graph-based Neural Multi-Document Summarization
  Michihiro Yasunaga, Rui Zhang, Kshitijh Meelu, Ayush Pareek, Krishnan Srinivasan and Dragomir Radev
Idea density for predicting Alzheimer's disease from transcribed speech
  Kairit Sirts, Olivier Piguet and Mark Johnson
Joint Prediction of Morphosyntactic Categories for Fine-Grained Arabic Part-of-Speech Tagging Exploiting Tag Dictionary Information
  Go Inoue, Hiroyuki Shindo and Yuji Matsumoto
Knowledge Tracing in Sequential Vocabulary Learning
  Adithya Renduchintala, Philipp Koehn and Jason Eisner
Learning Contextual Embeddings for Structural Semantic Similarity using Categorical Information
  Massimo Nicosia and Alessandro Moschitti
Learning from Relatives: Unified Dialectal Arabic Segmentation
  Younes Samih, Mohamed Eldesouki, Mohammed Attia, Kareem Darwish, Ahmed Abdelali, Hamdy Mubarak and Laura Kallmeyer
Learning local and global contexts using a convolutional recurrent network model for relation classification in biomedical text
  Desh Raj, Sunil Sahu and Ashish Anand
Learning Stock Market Sentiment Lexicon and Sentiment-Oriented Word Vector from StockTwits
  Quanzhi Li and Sameena Shah
Learning What is Essential in Questions
  Daniel Khashabi, Tushar Khot, Ashish Sabharwal and Dan Roth
Learning Word Representations with Regularization from Prior Knowledge
  Yan Song, Chia-Jung Lee and Fei Xia
Leveraging Eventive Information for Better Metaphor Detection and Classification
  I-Hsuan Chen, Yunfei Long, Qin Lu and Chu-Ren Huang
Making Neural QA as Simple as Possible but not Simpler
  Dirk Weissenborn, Georg Wiese and Laura Seiffe
Modeling Context Words as Regions: An Ordinal Regression Approach to Word Embedding
  Shoaib Jameel and Steven Schockaert
Multilingual Semantic Parsing And Code-Switching
  Long Duong, Hadi Afshar, Dominique Estival, Glen Pink, Philip Cohen and Mark Johnson
Named Entity Disambiguation for Noisy Text
  Yotam Eshel, Noam Cohen, Kira Radinsky, Shaul Markovitch, Ikuya Yamada and Omer Levy
Natural Language Generation for Spoken Dialogue System using RNN Encoder-Decoder Networks
  Van-Khanh Tran and Le-Minh Nguyen
Neural Domain Adaptation for Biomedical Question Answering
  Georg Wiese, Dirk Weissenborn and Mariana Neves
Neural Sequence-to-sequence Learning of Internal Word Structure
  Tatyana Ruzsics and Tanja Samardzic
Neural Structural Correspondence Learning for Domain Adaptation
  Yftah Ziser and Roi Reichart
Optimizing Differentiable Relaxations of Coreference Evaluation Metrics
  Phong Le and Ivan Titov
Parsing for Grammatical Relations via Graph Merging
  Weiwei Sun, Yantao Du and Xiaojun Wan
Robust Coreference Resolution and Entity Linking on Dialogues: Character Identification on TV Show Transcripts
  Henry Y. Chen, Ethan Zhou and Jinho D. Choi
Tell Me Why: Using Question Answering as Distant Supervision for Answer Justification
  Rebecca Sharp, Mihai Surdeanu, Peter Jansen, Marco A. Valenzuela-Escárcega, Peter Clark and Michael Hammond
The Covert Helps Parse the Overt
  Xun Zhang, Weiwei Sun and Xiaojun Wan
The Effect of Different Writing Tasks on Linguistic Style: A Case Study of the ROC Story Cloze Task
  Roy Schwartz, Maarten Sap, Ioannis Konstas, Leila Zilles, Yejin Choi and Noah A. Smith
Top-Rank Enhanced Listwise Optimization for Statistical Machine Translation
  Huadong Chen, Shujian Huang, David Chiang, Xin-Yu Dai and Jiajun Chen
Zero-Shot Relation Extraction via Reading Comprehension
  Omer Levy, Minjoon Seo, Eunsol Choi and Luke Zettlemoyer

Registration

In order to attend or present at CoNLL 2017, you must register for "Workshops (2-day)" here.