The 58th annual meeting of the Association for Computational Linguistics is being hosted virtually this week. We’re excited to share all the work from SAIL that’s being 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
Beyond User Self-Reported Likert Scale Ratings: A Comparison Model for Automatic Dialog Evaluation
Authors: Weixin Liang, James Zou, Zhou Yu
Contact: wxliang@stanford.edu
Keywords: dialog, automatic dialog evaluation, user experience
Contextual Embeddings: When Are They Worth It?
Authors: Simran Arora, Avner May, Jian Zhang, Christopher Ré
Contact: simarora@stanford.edu
Links: Paper | Video
Keywords: contextual embeddings, pretraining, benefits of context
Enabling Language Models to Fill in the Blanks
Authors: Chris Donahue, Mina Lee, Percy Liang
Contact: cdonahue@cs.stanford.edu
Links: Paper | Blog Post | Video
Keywords: natural language generation, infilling, fill in the blanks, language models
ExpBERT: Representation Engineering with Natural Language Explanations
Authors: Shikhar Murty, Pang Wei Koh, Percy Liang
Contact: smurty@cs.stanford.edu
Links: Paper | Video
Keywords: language explanations, bert, relation extraction, language supervision
Finding Universal Grammatical Relations in Multilingual BERT
Authors: Ethan A. Chi, John Hewitt, Christopher D. Manning
Contact: ethanchi@cs.stanford.edu
Links: Paper | Blog Post
Keywords: analysis, syntax, multilinguality
Is Your Classifier Actually Biased? Measuring Fairness under Uncertainty with Bernstein Bounds
Authors: Kawin Ethayarajh
Contact: kawin@stanford.edu
Links: Paper
Keywords: fairness, bias, equal opportunity, ethics, uncertainty
Low-Dimensional Hyperbolic Knowledge Graph Embeddings
Authors: Ines Chami, Adva Wolf, Da-Cheng Juan, Frederic Sala, Sujith Ravi, Christopher Ré
Contact: chami@stanford.edu
Links: Paper | Video
Keywords: knowledge graphs, hyperbolic embeddings, link prediction
Optimizing the Factual Correctness of a Summary: A Study of Summarizing Radiology Reports
Authors: Yuhao Zhang, Derek Merck, Emily Bao Tsai, Christopher D. Manning, Curtis P. Langlotz
Contact: yuhao.zhang@stanford.edu
Links: Paper
Keywords: nlp, text summarization, reinforcement learning, medicine, radiology report
Orthogonal Relation Transforms with Graph Context Modeling for Knowledge Graph Embedding
Authors: Yun Tang, Jing Huang, Guangtao Wang, Xiaodong He and Bowen Zhou
Contact: jhuang18@stanford.edu
Links: Paper | Video
Keywords: orthogonal transforms, knowledge graph embedding
Pretraining with Contrastive Sentence Objectives Improves Discourse Performance of Language Models
Authors: Dan Iter , Kelvin Guu , Larry Lansing, Dan Jurafsky
Contact: daniter@stanford.edu
Links: Paper
Keywords: discourse coherence, language model pretraining
Robust Encodings: A Framework for Combating Adversarial Typos
Authors: Erik Jones, Robin Jia, Aditi Raghunathan, Percy Liang
Contact: erjones@stanford.edu
Links: Paper
Keywords: nlp, robustness, adversarial robustness, typos, safe ml
SenseBERT: Driving Some Sense into BERT
Authors: Yoav Levine, Barak Lenz, Or Dagan, Ori Ram, Dan Padnos, Or Sharir, Shai Shalev-Schwarz, Amnon Shashua, Yoav Shoham
Contact: shoham@cs.stanford.edu
Links: Paper | Blog Post
Keywords: language models, semantics
Shaping Visual Representations with Language for Few-shot Classification
Authors: Jesse Mu, Percy Liang, Noah Goodman
Contact: muj@stanford.edu
Links: Paper
Keywords: grounding, language supervision, vision, few-shot learning, meta-learning, transfer
Stanza: A Python Natural Language Processing Toolkit for Many Human Languages
Authors: Peng Qi, Yuhao Zhang, Yuhui Zhang, Jason Bolton, Christopher D. Manning
Contact: pengqi@cs.stanford.edu
Links: Paper
Keywords: natural language processing, multilingual, data-driven, neural networks
Theoretical Limitations of Self-Attention in Neural Sequence Models
Authors: Michael Hahn
Contact: mhahn2@stanford.edu
Links: Paper
Keywords: theory, transformers, formal languages
Zero-Shot Transfer Learning with Synthesized Data for Multi-Domain Dialogue State Tracking
Authors: Giovanni Campagna, Agata Foryciarz, Mehrad Moradshahi, and Monica S. Lam
Contact: gcampagn@stanford.edu
Links: Paper
Keywords: dialogue state tracking, multiwoz, zero-shot, data programming, pretraining
We look forward to seeing you at ACL 2020!