Tushar Khot

According to our database, Tushar Khot authored at least 86 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

OLMo: Accelerating the Science of Language Models.

Dirk Groeneveld, Iz Beltagy, Pete Walsh, Akshita Bhagia, Rodney Kinney, Oyvind Tafjord, Ananya Harsh Jha, Hamish Ivison, Ian Magnusson, Yizhong Wang, Shane Arora, David Atkinson, Russell Authur, Khyathi Raghavi Chandu, Arman Cohan, Jennifer Dumas, Yanai Elazar, Yuling Gu, Jack Hessel, Tushar Khot, William Merrill, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Valentina Pyatkin, Abhilasha Ravichander, Dustin Schwenk, Saurabh Shah, Will Smith, Emma Strubell, Nishant Subramani, Mitchell Wortsman, Pradeep Dasigi, Nathan Lambert, Kyle Richardson, Luke Zettlemoyer, Jesse Dodge, Kyle Lo, Luca Soldaini, Noah A. Smith, Hannaneh Hajishirzi

CoRR, 2024

2023

ADaPT: As-Needed Decomposition and Planning with Language Models.

Archiki Prasad, Alexander Koller, Mareike Hartmann, Peter Clark, Ashish Sabharwal, Mohit Bansal, Tushar Khot

CoRR, 2023

Bias Runs Deep: Implicit Reasoning Biases in Persona-Assigned LLMs.

Shashank Gupta, Vaishnavi Shrivastava, Ameet Deshpande, Ashwin Kalyan, Peter Clark, Ashish Sabharwal, Tushar Khot

CoRR, 2023

SynerGPT: In-Context Learning for Personalized Drug Synergy Prediction and Drug Design.

Carl Edwards, Aakanksha Naik, Tushar Khot, Martin D. Burke, Heng Ji, Tom Hope

CoRR, 2023

How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources.

Yizhong Wang, Hamish Ivison, Pradeep Dasigi, Jack Hessel, Tushar Khot, Khyathi Raghavi Chandu, David Wadden, Kelsey MacMillan, Noah A. Smith, Iz Beltagy, Hannaneh Hajishirzi

CoRR, 2023

Chain-of-Thought Hub: A Continuous Effort to Measure Large Language Models' Reasoning Performance.

Yao Fu, Litu Ou, Mingyu Chen, Yuhao Wan, Hao Peng, Tushar Khot

CoRR, 2023

Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback.

Yao Fu, Hao Peng, Tushar Khot, Mirella Lapata

CoRR, 2023

How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources.

Yizhong Wang, Hamish Ivison, Pradeep Dasigi, Jack Hessel, Tushar Khot, Khyathi Chandu, David Wadden, Kelsey MacMillan, Noah A. Smith, Iz Beltagy, Hannaneh Hajishirzi

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Specializing Smaller Language Models towards Multi-Step Reasoning.

Yao Fu, Hao Peng, Litu Ou, Ashish Sabharwal, Tushar Khot

Proceedings of the International Conference on Machine Learning, 2023

Decomposed Prompting: A Modular Approach for Solving Complex Tasks.

Tushar Khot, Harsh Trivedi, Matthew Finlayson, Yao Fu, Kyle Richardson, Peter Clark, Ashish Sabharwal

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Complexity-Based Prompting for Multi-step Reasoning.

Yao Fu, Hao Peng, Ashish Sabharwal, Peter Clark, Tushar Khot

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions.

Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

The Tail Wagging the Dog: Dataset Construction Biases of Social Bias Benchmarks.

Nikil Roashan Selvam, Sunipa Dev, Daniel Khashabi, Tushar Khot, Kai-Wei Chang

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023

2022

♫ MuSiQue: Multihop Questions via Single-hop Question Composition.

Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal

Trans. Assoc. Comput. Linguistics, 2022

Teaching Broad Reasoning Skills via Decomposition-Guided Contexts.

Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal

CoRR, 2022

Better Retrieval May Not Lead to Better Question Answering.

Zhengzhong Liang, Tushar Khot, Steven Bethard, Mihai Surdeanu, Ashish Sabharwal

CoRR, 2022

Prompt Waywardness: The Curious Case of Discretized Interpretation of Continuous Prompts.

Daniel Khashabi, Xinxi Lyu, Sewon Min, Lianhui Qin, Kyle Richardson, Sean Welleck, Hannaneh Hajishirzi, Tushar Khot, Ashish Sabharwal, Sameer Singh, Yejin Choi

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Teaching Broad Reasoning Skills for Multi-Step QA by Generating Hard Contexts.

Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Hey AI, Can You Solve Complex Tasks by Talking to Agents?

Tushar Khot, Kyle Richardson, Daniel Khashabi, Ashish Sabharwal

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021

Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies.

Mor Geva, Daniel Khashabi, Elad Segal, Tushar Khot, Dan Roth, Jonathan Berant

Trans. Assoc. Comput. Linguistics, 2021

Structure learning for relational logistic regression: an ensemble approach.

Nandini Ramanan, Gautam Kunapuli, Tushar Khot, Bahare Fatemi, Seyed Mehran Kazemi, David Poole, Kristian Kersting, Sriraam Natarajan

Data Min. Knowl. Discov., 2021

PROMPT WAYWARDNESS: The Curious Case of Discretized Interpretation of Continuous Prompts.

Daniel Khashabi, Shane Lyu, Sewon Min, Lianhui Qin, Kyle Richardson, Sameer Singh, Sean Welleck, Hannaneh Hajishirzi, Tushar Khot, Ashish Sabharwal, Yejin Choi

CoRR, 2021

Learning to Solve Complex Tasks by Talking to Agents.

Tushar Khot, Kyle Richardson, Daniel Khashabi, Ashish Sabharwal

CoRR, 2021

MuSiQue: Multi-hop Questions via Single-hop Question Composition.

Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal

CoRR, 2021

Think you have Solved Direct-Answer Question Answering? Try ARC-DA, the Direct-Answer AI2 Reasoning Challenge.

Sumithra Bhakthavatsalam, Daniel Khashabi, Tushar Khot, Bhavana Dalvi Mishra, Kyle Richardson, Ashish Sabharwal, Carissa Schoenick, Oyvind Tafjord, Peter Clark

CoRR, 2021

Temporal Reasoning on Implicit Events from Distant Supervision.

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

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

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

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

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

GooAQ: Open Question Answering with Diverse Answer Types.

Daniel Khashabi, Amos Ng, Tushar Khot, Ashish Sabharwal, Hannaneh Hajishirzi, Chris Callison-Burch

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Ethical-Advice Taker: Do Language Models Understand Natural Language Interventions?

Jieyu Zhao, Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Kai-Wei Chang

Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

ReadOnce Transformers: Reusable Representations of Text for Transformers.

Shih-Ting Lin, Ashish Sabharwal, Tushar Khot

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020

UnQovering Stereotyping Biases via Underspecified Questions.

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

CoRR, 2020

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

Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal

CoRR, 2020

UnifiedQA: Crossing Format Boundaries With a Single QA System.

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

CoRR, 2020

Natural Perturbation for Robust Question Answering.

Daniel Khashabi, Tushar Khot, Ashish Sabharwal

CoRR, 2020

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

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

AI Mag., 2020

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

Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

UNQOVERing Stereotypical Biases via Underspecified Questions.

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

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

UnifiedQA: Crossing Format Boundaries With a Single QA System.

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

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

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

Daniel Khashabi, Tushar Khot, Ashish Sabharwal

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

A Simple Yet Strong Pipeline for HotpotQA.

Dirk Groeneveld, Tushar Khot, Mausam, Ashish Sabharwal

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

IIRC: A Dataset of Incomplete Information Reading Comprehension Questions.

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

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

QASC: A Dataset for Question Answering via Sentence Composition.

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

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

On the Capabilities and Limitations of Reasoning for Natural Language Understanding.

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

CoRR, 2019

Repurposing Entailment for Multi-Hop Question Answering Tasks.

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

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

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

Tushar Khot, Ashish Sabharwal, Peter Clark

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Exploiting Explicit Paths for Multi-hop Reading Comprehension.

Souvik Kundu, Tushar Khot, Ashish Sabharwal, Peter Clark

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018

Exploiting Explicit Paths for Multi-hop Reading Comprehension.

Souvik Kundu, Tushar Khot, Ashish Sabharwal

CoRR, 2018

Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Peter Clark, Isaac Cowhey, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Carissa Schoenick, Oyvind Tafjord

CoRR, 2018

Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering.

Todor Mihaylov, Peter Clark, Tushar Khot, Ashish Sabharwal

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Bridging Knowledge Gaps in Neural Entailment via Symbolic Models.

Dongyeop Kang, Tushar Khot, Ashish Sabharwal, Peter Clark

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

AdvEntuRe: Adversarial Training for Textual Entailment with Knowledge-Guided Examples.

Dongyeop Kang, Tushar Khot, Ashish Sabharwal, Eduard H. Hovy

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

SciTaiL: A Textual Entailment Dataset from Science Question Answering.

Tushar Khot, Ashish Sabharwal, Peter Clark

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Question Answering as Global Reasoning Over Semantic Abstractions.

Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Dan Roth

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Markov logic networks for adverse drug event extraction from text.

Sriraam Natarajan, Vishal Bangera, Tushar Khot, Jose Picado, Anurag Wazalwar, Vítor Santos Costa, David Page, Michael Caldwell

Knowl. Inf. Syst., 2017

Relational Restricted Boltzmann Machines: A Probabilistic Logic Learning Approach.

Navdeep Kaur, Gautam Kunapuli, Tushar Khot, Kristian Kersting, William Cohen, Sriraam Natarajan

Proceedings of the Inductive Logic Programming - 27th International Conference, 2017

Learning What is Essential in Questions.

Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Dan Roth

Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017), 2017

Answering Complex Questions Using Open Information Extraction.

Tushar Khot, Ashish Sabharwal, Peter Clark

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017

2016

Scaling Lifted Probabilistic Inference and Learning Via Graph Databases.

Mayukh Das, Yuqing Wu, Tushar Khot, Kristian Kersting, Sriraam Natarajan

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Inductive Logic Programming Meets Relational Databases: Efficient Learning of Markov Logic Networks.

Marcin Malec, Tushar Khot, James G. Nagy, Erik Blask, Sriraam Natarajan

Proceedings of the Inductive Logic Programming - 26th International Conference, 2016

Question Answering via Integer Programming over Semi-Structured Knowledge.

Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Peter Clark, Oren Etzioni, Dan Roth

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Learning Continuous-Time Bayesian Networks in Relational Domains: A Non-Parametric Approach.

Shuo Yang, Tushar Khot, Kristian Kersting, Sriraam Natarajan

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Combining Retrieval, Statistics, and Inference to Answer Elementary Science Questions.

Peter Clark, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter D. Turney, Daniel Khashabi

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Gradient-based boosting for statistical relational learning: the Markov logic network and missing data cases.

Tushar Khot, Sriraam Natarajan, Kristian Kersting, Jude W. Shavlik

Mach. Learn., 2015

Markov Logic Networks for Natural Language Question Answering.

Tushar Khot, Niranjan Balasubramanian, Eric Gribkoff, Ashish Sabharwal, Peter Clark, Oren Etzioni

CoRR, 2015

Anomaly Detection in Text: The Value of Domain Knowledge.

Raksha Kumaraswamy, Anurag Wazalwar, Tushar Khot, Jude W. Shavlik, Sriraam Natarajan

Proceedings of the Twenty-Eighth International Florida Artificial Intelligence Research Society Conference, 2015

Exploring Markov Logic Networks for Question Answering.

Tushar Khot, Niranjan Balasubramanian, Eric Gribkoff, Ashish Sabharwal, Peter Clark, Oren Etzioni

Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 2015

Extracting Adverse Drug Events from Text Using Human Advice.

Phillip Odom, Vishal Bangera, Tushar Khot, David Page, Sriraam Natarajan

Proceedings of the Artificial Intelligence in Medicine, 2015

Learning Probabilistic Logic Models with Human Advice.

Phillip Odom, Tushar Khot, Sriraam Natarajan

Proceedings of the 2015 AAAI Spring Symposia, 2015

Knowledge-Based Probabilistic Logic Learning.

Phillip Odom, Tushar Khot, Reid B. Porter, Sriraam Natarajan

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Boosted Statistical Relational Learners - From Benchmarks to Data-Driven Medicine

Sriraam Natarajan, Kristian Kersting, Tushar Khot, Jude W. Shavlik

Springer Briefs in Computer Science, Springer, ISBN: 978-3-319-13644-8, 2014

Relational learning helps in three-way classification of Alzheimer patients from structural magnetic resonance images of the brain.

Sriraam Natarajan, Baidya Nath Saha, Saket Joshi, Adam Edwards, Tushar Khot, Elizabeth M. Davenport, Kristian Kersting, Christopher T. Whitlow, Joseph A. Maldjian

Int. J. Mach. Learn. Cybern., 2014

Statistical Relational Learning for Handwriting Recognition.

Arti Shivram, Tushar Khot, Sriraam Natarajan, Venu Govindaraju

Proceedings of the Inductive Logic Programming - 24th International Conference, 2014

Effectively Creating Weakly Labeled Training Examples via Approximate Domain Knowledge.

Sriraam Natarajan, Jose Picado, Tushar Khot, Kristian Kersting, Christopher Ré, Jude W. Shavlik

Proceedings of the Inductive Logic Programming - 24th International Conference, 2014

Learning from Imbalanced Data in Relational Domains: A Soft Margin Approach.

Shuo Yang, Tushar Khot, Kristian Kersting, Gautam Kunapuli, Kris Hauser, Sriraam Natarajan

Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

Classification from One Class of Examples for Relational Domains.

Tushar Khot, Sriraam Natarajan, Jude W. Shavlik

Proceedings of the Statistical Relational Artificial Intelligence, 2014

Relational One-Class Classification: A Non-Parametric Approach.

Tushar Khot, Sriraam Natarajan, Jude W. Shavlik

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013

Bootstrapping Knowledge Base Acceleration.

Tushar Khot, Ce Zhang, Jude W. Shavlik, Sriraam Natarajan, Christopher Ré

Proceedings of The Twenty-Second Text REtrieval Conference, 2013

Accelerating Imitation Learning in Relational Domains via Transfer by Initialization.

Sriraam Natarajan, Phillip Odom, Saket Joshi, Tushar Khot, Kristian Kersting, Prasad Tadepalli

Proceedings of the Inductive Logic Programming - 23rd International Conference, 2013

Using Commonsense Knowledge to Automatically Create (Noisy) Training Examples from Text.

Sriraam Natarajan, Jose Picado, Tushar Khot, Kristian Kersting, Christopher Ré, Jude W. Shavlik

Proceedings of the Statistical Relational Artificial Intelligence, 2013

2012

Gradient-based boosting for statistical relational learning: The relational dependency network case.

Sriraam Natarajan, Tushar Khot, Kristian Kersting, Bernd Gutmann, Jude W. Shavlik

Mach. Learn., 2012

Accelarating Imitation Learning in Relational Domains via Transfer by Initialization.

Sriraam Natarajan, Phillip Odom, Saket Joshi, Tushar Khot, Kristian Kersting, Prasad Tadepalli

Proceedings of the 2nd International Workshop on Statistical Relational AI (StaRAI-12), 2012

Learning Relational Structure for Temporal Relation Extraction.

Tushar Khot, Siddharth Srivastava, Sriraam Natarajan, Jude W. Shavlik

Proceedings of the 2nd International Workshop on Statistical Relational AI (StaRAI-12), 2012

A Machine Learning Pipeline for Three-Way Classification of Alzheimer Patients from Structural Magnetic Resonance Images of the Brain.

Sriraam Natarajan, Saket Joshi, Baidya Nath Saha, Adam Edwards, Tushar Khot, Elizabeth Moody, Kristian Kersting, Christopher T. Whitlow, Joseph A. Maldjian

Proceedings of the 11th International Conference on Machine Learning and Applications, 2012

2011

Learning Markov Logic Networks via Functional Gradient Boosting.

Tushar Khot, Sriraam Natarajan, Kristian Kersting, Jude W. Shavlik

Proceedings of the 11th IEEE International Conference on Data Mining, 2011

2010

Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models.

Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

2009

Some new directions in graph-based semi-supervised learning.

Xiaojin Zhu, Andrew B. Goldberg, Tushar Khot

Proceedings of the 2009 IEEE International Conference on Multimedia and Expo, 2009