64 citations · 375 across the 45 of their papers we have counts for
11 papers · 2 filters
Why is Winoground Hard? Investigating Failures in Visuolinguistic Compositionality
Anuj Diwan, Layne Berry, Eunsol Choi +2
Recent visuolinguistic pre-trained models show promising progress on various end tasks such as image retrieval and video captioning. Yet, they fail miserably on the recently propos…
TyDiP: A Dataset for Politeness Classification in Nine Typologically Diverse Languages
Anirudh Srinivasan, Eunsol Choi
We study politeness phenomena in nine typologically diverse languages. Politeness is an important facet of communication and is sometimes argued to be cultural-specific, yet existi…
Beyond Counting Datasets: A Survey of Multilingual Dataset Construction and Necessary Resources
Xinyan Velocity Yu, Akari Asai, Trina Chatterjee +2
While the NLP community is generally aware of resource disparities among languages, we lack research that quantifies the extent and types of such disparity. Prior surveys estimatin…
Rich Knowledge Sources Bring Complex Knowledge Conflicts: Recalibrating Models to Reflect Conflicting Evidence
Hung-Ting Chen, Michael J. Q. Zhang, Eunsol Choi
Question answering models can use rich knowledge sources -- up to one hundred retrieved passages and parametric knowledge in the large-scale language model (LM). Prior work assumes…
MIA 2022 Shared Task: Evaluating Cross-lingual Open-Retrieval Question Answering for 16 Diverse Languages
Akari Asai, Shayne Longpre, Jungo Kasai +6
We present the results of the Workshop on Multilingual Information Access (MIA) 2022 Shared Task, evaluating cross-lingual open-retrieval question answering (QA) systems in 16 typo…
longhorns at DADC 2022: How many linguists does it take to fool a Question Answering model? A systematic approach to adversarial attacks
Venelin Kovatchev, Trina Chatterjee, Venkata S Govindarajan +9
Developing methods to adversarially challenge NLP systems is a promising avenue for improving both model performance and interpretability. Here, we describe the approach of the tea…
Modeling Exemplification in Long-form Question Answering via Retrieval
Shufan Wang, Fangyuan Xu, Laure Thompson +2
Exemplification is a process by which writers explain or clarify a concept by providing an example. While common in all forms of writing, exemplification is particularly useful in…
Entity Cloze By Date: What LMs Know About Unseen Entities
Yasumasa Onoe, Michael J. Q. Zhang, Eunsol Choi +1
Language models (LMs) are typically trained once on a large-scale corpus and used for years without being updated. However, in a dynamic world, new entities constantly arise. We pr…
Generating Literal and Implied Subquestions to Fact-check Complex Claims
Jifan Chen, Aniruddh Sriram, Eunsol Choi +1
Verifying complex political claims is a challenging task, especially when politicians use various tactics to subtly misrepresent the facts. Automatic fact-checking systems fall sho…
How Do We Answer Complex Questions: Discourse Structure of Long-form Answers
Fangyuan Xu, Junyi Jessy Li, Eunsol Choi
Long-form answers, consisting of multiple sentences, can provide nuanced and comprehensive answers to a broader set of questions. To better understand this complex and understudied…
Simulating Bandit Learning from User Feedback for Extractive Question Answering
Ge Gao, Eunsol Choi, Yoav Artzi
We study learning from user feedback for extractive question answering by simulating feedback using supervised data. We cast the problem as contextual bandit learning, and analyze…