209 citations · 209 across the 1 of their papers we have counts for
4 papers · 1 filter
Don't Take the Easy Way Out: Ensemble Based Methods for Avoiding Known Dataset Biases
Christopher Clark, Mark Yatskar, Luke Zettlemoyer
State-of-the-art models often make use of superficial patterns in the data that do not generalize well to out-of-domain or adversarial settings. For example, textual entailment mod…
BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions
Christopher Clark, Kenton Lee, Ming-Wei Chang +3
In this paper we study yes/no questions that are naturally occurring --- meaning that they are generated in unprompted and unconstrained settings. We build a reading comprehension…
Deep contextualized word representations
Matthew E. Peters, Mark Neumann, Mohit Iyyer +4
We introduce a new type of deep contextualized word representation that models both (1) complex characteristics of word use (e.g., syntax and semantics), and (2) how these uses var…
Simple and Effective Multi-Paragraph Reading Comprehension
Christopher Clark, Matt Gardner
We consider the problem of adapting neural paragraph-level question answering models to the case where entire documents are given as input. Our proposed solution trains models to p…