2026 Ashish Sabharwal: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	55	4395	4271	2051	1978	202	9522

Overview

Ashish Sabharwal is a researcher affiliated with the Allen Institute for Artificial Intelligence in the United States. Their work spans the field of Computer Science, with a primary focus on Artificial Intelligence. The scientist has contributed extensively in various subfields, including Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Computer Networks and Communications, and Electrical and Electronic Engineering.

The scientist's research topics cover several main areas, reflecting a broad engagement with both fundamental and applied aspects of machine learning and natural language processing. These topics include:

Topic Modeling
Natural Language Processing Techniques
Multimodal Machine Learning Applications
Machine Learning and Algorithms
Software Engineering Research
Explainable Artificial Intelligence (XAI)
Semantic Web and Ontologies

Among recent publications, several papers stand out, illustrating a range of investigations into language models, dataset biases, and multimodal question answering. Some of these recent works are:

"Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models", 2022, arXiv (Cornell University)
"Adversarial Filters of Dataset Biases", 2020, arXiv (Cornell University)
" MuSiQue: Multihop Questions via Single-hop Question Composition", 2022, Transactions of the Association for Computational Linguistics
"Multi-Modal Answer Validation for Knowledge-Based VQA", 2022, Proceedings of the AAAI Conference on Artificial Intelligence
"Decomposed Prompting: A Modular Approach for Solving Complex Tasks", 2022, arXiv (Cornell University)

The scientist frequently publishes in several venues, with a significant number of their works appearing in the following:

arXiv (Cornell University)
Transactions of the Association for Computational Linguistics
Proceedings of the AAAI Conference on Artificial Intelligence
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
AI Magazine

Ashish Sabharwal collaborates regularly with several researchers, as indicated by repeated co-authorship. Notable frequent co-authors include:

Tushar Khot
Kyle Richardson
Peter Clark
Daniel Khashabi
Peter E. Clark

Best Publications

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

Peter Clark;Isaac Cowhey;Oren Etzioni;Tushar Khot

618
Citations
Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering

Todor Mihaylov;Peter Clark;Tushar Khot;Ashish Sabharwal

600
Citations
UNIFIEDQA: Crossing Format Boundaries with a Single QA System

Daniel Khashabi;Sewon Min;Tushar Khot;Ashish Sabharwal

500
Citations
SciTaiL: A Textual Entailment Dataset from Science Question Answering

Tushar Khot;Ashish Sabharwal;Peter Clark

449
Citations
Towards understanding and harnessing the potential of clause learning

Paul Beame;Henry Kautz;Ashish Sabharwal

388
Citations
Decomposed Prompting: A Modular Approach for Solving Complex Tasks

Unknown

231
Citations
Parsing Algebraic Word Problems into Equations

Rik Koncel-Kedziorski;Hannaneh Hajishirzi;Ashish Sabharwal;Oren Etzioni

230
Citations
Complexity-Based Prompting for Multi-Step Reasoning

Unknown

222
Citations
QASC: A dataset for question answering via sentence composition

Tushar Khot;Peter Clark;Michal Guerquin;Peter Jansen

219
Citations
Chapter 2 Satisfiability Solvers

Carla P. Gomes;Henry Kautz;Ashish Sabharwal;Bart Selman

207
Citations
Algorithm selection and scheduling

Serdar Kadioglu;Yuri Malitsky;Ashish Sabharwal;Horst Samulowitz

203
Citations
Adversarial Filters of Dataset Biases

Ronan Le Bras;Swabha Swayamdipta;Chandra Bhagavatula;Rowan Zellers

189
Citations
Model counting: a new strategy for obtaining good bounds

Carla P. Gomes;Ashish Sabharwal;Bart Selman

158
Citations
Combining retrieval, statistics, and inference to answer elementary science questions

Peter Clark;Oren Etzioni;Tushar Khot;Ashish Sabharwal

156
Citations
Probing Natural Language Inference Models through Semantic Fragments.

Kyle Richardson;Hai Hu;Lawrence S. Moss;Ashish Sabharwal

148
Citations
Near-Uniform Sampling of Combinatorial Spaces Using XOR Constraints

Carla P Gomes;Ashish Sabharwal;Bart Selman

127
Citations
Understanding the power of clause learning

Paul Beanie;Henry Kautz;Ashish Sabharwal

125
Citations
Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization

Stefano Ermon;Carla Gomes;Ashish Sabharwal;Bart Selman

123
Citations
From sampling to model counting

Carla P. Gomes;Joerg Hoffmann;Ashish Sabharwal;Bart Selman

121
Citations
MuSiQue: Multi-hop Questions via Single-hop Question Composition

Harsh Trivedi;Niranjan Balasubramanian;Tushar Khot;Ashish Sabharwal

116
Citations
Algorithm portfolios based on cost-sensitive hierarchical clustering

Yuri Malitsky;Ashish Sabharwal;Horst Samulowitz;Meinolf Sellmann

113
Citations
Answering Complex Questions Using Open Information Extraction.

Tushar Khot;Ashish Sabharwal;Peter Clark

111
Citations
UNQOVERing Stereotyping Biases via Underspecified Questions

Tao Li;Daniel Khashabi;Tushar Khot;Ashish Sabharwal

47
Citations

Frequent Co-Authors

Carla P. Gomes Cornell University

Bart Selman Cornell University

Peter Clark Allen Institute for Artificial Intelligence

Stefano Ermon Stanford University

Paul Beame University of Washington

Oren Etzioni University of Washington

Dan Roth University of Pennsylvania

Henry Kautz University of Virginia

Hannaneh Hajishirzi University of Washington

Atri Rudra University at Buffalo, State University of New York

External Links

Google Scholar page

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