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20182023
most citedBoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions

209 citations · 265 across the 5 of their papers we have counts for

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13 papers · 1 filter

cs.CL2023

NAIL: Lexical Retrieval Indices with Efficient Non-Autoregressive Decoders

Livio Baldini Soares, Daniel Gillick, Jeremy R. Cole +1

Neural document rerankers are extremely effective in terms of accuracy. However, the best models require dedicated hardware for serving, which is costly and often not feasible. To…

cs.CL2023

Evaluating and Modeling Attribution for Cross-Lingual Question Answering

Benjamin Muller, John Wieting, Jonathan H. Clark +6

Trustworthy answer content is abundant in many high-resource languages and is instantly accessible through question answering systems, yet this content can be hard to access for th…

cs.CL2021

Decontextualization: Making Sentences Stand-Alone

Eunsol Choi, Jennimaria Palomaki, Matthew Lamm +3

Models for question answering, dialogue agents, and summarization often interpret the meaning of a sentence in a rich context and use that meaning in a new context. Taking excerpts…

cs.CL2021

NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned

Sewon Min, Jordan Boyd-Graber, Chris Alberti +50

We review the EfficientQA competition from NeurIPS 2020. The competition focused on open-domain question answering (QA), where systems take natural language questions as input and…

cs.CL202017 cited

Empirical Evaluation of Pretraining Strategies for Supervised Entity Linking

Thibault Févry, Nicholas FitzGerald, Livio Baldini Soares +1

In this work, we present an entity linking model which combines a Transformer architecture with large scale pretraining from Wikipedia links. Our model achieves the state-of-the-ar…

cs.CL2020

Entities as Experts: Sparse Memory Access with Entity Supervision

Thibault Févry, Livio Baldini Soares, Nicholas FitzGerald +2

We focus on the problem of capturing declarative knowledge about entities in the learned parameters of a language model. We introduce a new model - Entities as Experts (EAE) - that…