565 citations · 2.3k across the 68 of their papers we have counts for
10 papers · 1 filter
UnQovering Stereotyping Biases via Underspecified Questions
Tao Li, Tushar Khot, Daniel Khashabi +2
While language embeddings have been shown to have stereotyping biases, how these biases affect downstream question answering (QA) models remains unexplored. We present UNQOVER, a g…
ReadOnce Transformers: Reusable Representations of Text for Transformers
Shih-Ting Lin, Ashish Sabharwal, Tushar Khot
We present ReadOnce Transformers, an approach to convert a transformer-based model into one that can build an information-capturing, task-independent, and compressed representation…
Temporal Reasoning on Implicit Events from Distant Supervision
Ben Zhou, Kyle Richardson, Qiang Ning +3
We propose TRACIE, a novel temporal reasoning dataset that evaluates the degree to which systems understand implicit events -- events that are not mentioned explicitly in natural l…
Text Modular Networks: Learning to Decompose Tasks in the Language of Existing Models
Tushar Khot, Daniel Khashabi, Kyle Richardson +2
We propose a general framework called Text Modular Networks(TMNs) for building interpretable systems that learn to solve complex tasks by decomposing them into simpler ones solvabl…
Belief Propagation Neural Networks
Jonathan Kuck, Shuvam Chakraborty, Hao Tang +4
Learned neural solvers have successfully been used to solve combinatorial optimization and decision problems. More general counting variants of these problems, however, are still l…
Is Multihop QA in DiRe Condition? Measuring and Reducing Disconnected Reasoning
Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot +1
Has there been real progress in multi-hop question-answering? Models often exploit dataset artifacts to produce correct answers, without connecting information across multiple supp…