Tushar Khot

Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI

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QASC: A Dataset for Question Answering via Sentence Composition

Tushar Khot,Peter Clark, Michal Guerquin, Peter Jansen,Ashish Sabharwal

national conference on artificial intelligence, (2020)

Cited by7Bibtex

Temporal Reasoning on Implicit Events from Distant Supervision

Ben Zhou,Kyle Richardson,Qiang Ning,Tushar Khot,Ashish Sabharwal,Dan Roth

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More Bang for Your Buck: Natural Perturbation for Robust Question Answering

Daniel Khashabi,Tushar Khot,Ashish Sabharwal

empirical methods in natural language processing, pp.163-170, (2020)

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IIRC: A Dataset of Incomplete Information Reading Comprehension Questions

James Ferguson,Matt Gardner,Hannaneh Hajishirzi,Tushar Khot,Pradeep Dasigi

empirical methods in natural language processing, pp.1137-1147, (2020)

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Is Multihop QA in DiRe Condition? Measuring and Reducing Disconnected Reasoning

Harsh Trivedi,Niranjan Balasubramanian,Tushar Khot,Ashish Sabharwal

empirical methods in natural language processing, pp.8846-8863, (2020)

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UNQOVERing Stereotyping Biases via Underspecified Questions

Tao Li,Daniel Khashabi,Tushar Khot,Ashish Sabharwal,Vivek Srikumar

EMNLP, pp.3475-3489, (2020)

EIBibtex

Text Modular Networks: Learning to Decompose Tasks in the Language of Existing Models

Tushar Khot,Daniel Khashabi, Kyle Richardson,Peter Clark,Ashish Sabharwal

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Measuring and Reducing Non-Multifact Reasoning in Multi-hop Question Answering

Trivedi Harsh,Balasubramanian Niranjan,Khot Tushar,Sabharwal Ashish

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UnifiedQA: Crossing Format Boundaries With a Single QA System

Khashabi Daniel,Khot Tushar,Sabharwal Ashish,Tafjord Oyvind,Clark Peter,Hajishirzi Hannaneh

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A Simple Yet Strong Pipeline for HotpotQA

Groeneveld Dirk,Khot Tushar,Mausam,Sabharwal Ashish

EMNLP 2020, (2020)

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Natural Perturbation for Robust Question Answering

Khashabi Daniel,Khot Tushar,Sabharwal Ashish

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ReadOnce Transformers: Reusable Representations of Text for Transformers

Shih-Ting Lin,Ashish Sabharwal,Tushar Khot

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On the Capabilities and Limitations of Reasoning for Natural Language Understanding

Daniel Khashabi,Erfan Sadeqi Azer,Tushar Khot,Ashish Sabharwal,Dan Roth

arXiv: Computation and Language, (2019)

Cited by4EIBibtex

From 'F' to 'A' on the N.Y. Regents Science Exams: An Overview of the Aristo Project

Clark Peter,Etzioni Oren,Khot Tushar, Mishra Bhavana Dalvi,Richardson Kyle,Sabharwal Ashish, Schoenick Carissa,Tafjord Oyvind,Tandon Niket,Bhakthavatsalam Sumithra, Groeneveld Dirk, Guerquin Michal

Bibtex

What's Missing: A Knowledge Gap Guided Approach for Multi-hop Question Answering

Khot Tushar,Sabharwal Ashish, Clark Peter

EMNLP/IJCNLP (1), pp.2814-2828, (2019)

Cited by7EIBibtex

Exploiting Explicit Paths for Multi-hop Reading Comprehension

Souvik Kundu,Tushar Khot,Ashish Sabharwal,Peter Clark

arXiv: Computation and Language, (2019): 2737-2747

Cited by6EIBibtex

Entailment-based Question Answering over Multiple Sentences

Harsh Trivedi, Heeyoung Kwon,Tushar Khot,Ashish Sabharwal,Niranjan Balasubramanian

north american chapter of the association for computational linguistics, (2019)

Bibtex

Repurposing Entailment for Multi-Hop Question Answering Tasks

Harsh Trivedi, Heeyoung Kwon,Tushar Khot,Ashish Sabharwal,Niranjan Balasubramanian

arXiv: Computation and Language, (2019)

Cited by4EIBibtex

What’s Missing: A Knowledge Gap Guided Approach for Multi-hop Question Answering

Tushar Khot,Ashish Sabharwal, Peter Clark

international joint conference on natural language processing, (2019)

Cited by3Bibtex

SciTaiL: A Textual Entailment Dataset from Science Question Answering

Tushar Khot,Ashish Sabharwal,Peter Clark

AAAI, (2018)

Cited by93EIBibtex

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