The 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021)
will take place next week, colocated with CoNLL 2021. We’re excited to share all the work from SAIL that will be presented, and you’ll find links to papers, videos and blogs below. Feel free to reach out to the contact authors directly to learn more about the work that’s happening at Stanford!
List of Accepted Papers
Calibrate your listeners! Robust communication-based training for pragmatic speakers
Authors: Rose E. Wang, Julia White, Jesse Mu, Noah D. Goodman
Contact: rewang@stanford.edu
Links: Paper | Video
Keywords: language generation, pragmatics, communication-based training, calibration, uncertainty
Cross-Domain Data Integration for Named Entity Disambiguation in Biomedical Text
Authors: Maya Varma, Laurel Orr, Sen Wu, Megan Leszczynski, Xiao Ling, Christopher Ré
Contact: mvarma2@stanford.edu
Links: Paper | Video
Keywords: named entity disambiguation, biomedical text, rare entities, data integration
ContractNLI: A Dataset for Document-level Natural Language Inference for Contracts
Authors: Yuta Koreeda, Christopher D. Manning
Contact: koreeda@stanford.edu
Links: Paper | Website
Keywords: natural language inference, contract, law, legal, dataset
Venue: The Findings of EMNLP 2021
The Emergence of the Shape Bias Results from Communicative Efficiency
Authors: Eva Portelance, Michael C. Frank, Dan Jurafsky, Alessandro Sordoni, Romain Laroche
Contact: portelan@stanford.edu
Links: Paper | Website
Keywords: emergent communication, shape bias, multi-agent reinforcement learning, language learning, language acquisition
Conference: CoNLL
LM-Critic: Language Models for Unsupervised Grammatical Error Correction
Authors: Michihiro Yasunaga, Jure Leskovec, Percy Liang.
Contact: myasu@cs.stanford.edu
Links: Paper | Blog Post | Website
Keywords: language model, grammatical error correction, unsupervised translation
Sensitivity as a complexity measure for sequence classification tasks
Authors: Michael Hahn, Dan Jurafsky, Richard Futrell
Contact: mhahn2@stanford.edu
Links: Paper
Keywords: decision boundaries, computational complexity
Distributionally Robust Multilingual Machine Translation
Authors: Chunting Zhou*, Daniel Levy*, Marjan Ghazvininejad, Xian Li, Graham Neubig
Contact: daniel.levy0@gmail.com
Keywords: machine translation, robustness, distribution shift, dro, cross-lingual transfer
Learning from Limited Labels for Long Legal Dialogue
Authors: Jenny Hong, Derek Chong, Christopher D. Manning
Contact: jennyhong@cs.stanford.edu
Keywords: legal nlp, information extraction, weak supervision
Capturing Logical Structure of Visually Structured Documents with Multimodal Transition Parser
Authors: Yuta Koreeda, Christopher D. Manning
Contact: koreeda@stanford.edu
Links: Paper | Website
Keywords: legal, preprocessing
Workshop: Natural Legal Language Processing Workshop
We look forward to seeing you at EMNLP/CoNLL 2021!