D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 35 Citations 5,019 117 World Ranking 5904 National Ranking 2867

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Programming language
  • Algorithm

His main research concerns Question answering, Artificial intelligence, Algorithm, Natural language processing and Theoretical computer science. The Question answering study combines topics in areas such as Inference, Markov chain, Knowledge base and Set. His research investigates the connection with Artificial intelligence and areas like Machine learning which intersect with concerns in Classifier and Integer.

His work on Boolean satisfiability problem as part of his general Algorithm study is frequently connected to Maximum satisfiability problem, thereby bridging the divide between different branches of science. Ashish Sabharwal combines subjects such as Textual entailment and Task with his study of Natural language processing. His work carried out in the field of Theoretical computer science brings together such families of science as Hash function and Resolution.

His most cited work include:

  • Towards understanding and harnessing the potential of clause learning (245 citations)
  • SciTaiL: A Textual Entailment Dataset from Science Question Answering. (237 citations)
  • Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge (197 citations)

What are the main themes of his work throughout his whole career to date?

Ashish Sabharwal focuses on Artificial intelligence, Theoretical computer science, Algorithm, Question answering and Mathematical optimization. His Artificial intelligence study combines topics from a wide range of disciplines, such as Machine learning, Task and Natural language processing. The various areas that he examines in his Natural language processing study include Annotation, Logical consequence, Textual entailment, Knowledge base and Benchmark.

Markov chain is closely connected to Inference in his research, which is encompassed under the umbrella topic of Theoretical computer science. His Algorithm research focuses on Local consistency and how it connects with Time complexity. His Question answering research integrates issues from Language model, Sentence and Key.

He most often published in these fields:

  • Artificial intelligence (28.42%)
  • Theoretical computer science (22.63%)
  • Algorithm (21.58%)

What were the highlights of his more recent work (between 2018-2021)?

  • Question answering (18.42%)
  • Artificial intelligence (28.42%)
  • Natural language processing (12.63%)

In recent papers he was focusing on the following fields of study:

Ashish Sabharwal mostly deals with Question answering, Artificial intelligence, Natural language processing, Theoretical computer science and Language model. His studies in Question answering integrate themes in fields like Sentence and Key. The Sentence study which covers Context that intersects with Sampling, Tracking, Particle filter and Algorithm.

Ashish Sabharwal interconnects Machine learning, Task and Combinatorial optimization in the investigation of issues within Artificial intelligence. His study in Natural language processing is interdisciplinary in nature, drawing from both Annotation and Benchmark. His Theoretical computer science study frequently involves adjacent topics like Conjunction.

Between 2018 and 2021, his most popular works were:

  • UNIFIEDQA: Crossing Format Boundaries with a Single QA System (50 citations)
  • QASC: A Dataset for Question Answering via Sentence Composition. (48 citations)
  • Question Answering as Global Reasoning Over Semantic Abstractions. (47 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Programming language
  • Algorithm

Ashish Sabharwal mainly investigates Artificial intelligence, Task, Natural language processing, Question answering and Benchmark. He has researched Task in several fields, including Adversarial system, Overfitting, Reduction and Spurious relationship, Machine learning. His Natural language processing research includes themes of Dependency, Range and Coreference.

His multidisciplinary approach integrates Question answering and Structure in his work. His Benchmark research is multidisciplinary, incorporating elements of Natural language inference, Word and Variation. Within one scientific family, Ashish Sabharwal focuses on topics pertaining to Variety under Language model, and may sometimes address concerns connected to State and Information retrieval.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Towards understanding and harnessing the potential of clause learning

Paul Beame;Henry Kautz;Ashish Sabharwal.
Journal of Artificial Intelligence Research (2004)

348 Citations

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

Peter Clark;Isaac Cowhey;Oren Etzioni;Tushar Khot.
arXiv: Artificial Intelligence (2018)

293 Citations

SciTaiL: A Textual Entailment Dataset from Science Question Answering.

Tushar Khot;Ashish Sabharwal;Peter Clark.
national conference on artificial intelligence (2018)

237 Citations

Chapter 2 Satisfiability Solvers

Carla P. Gomes;Henry Kautz;Ashish Sabharwal;Bart Selman.
Foundations of Artificial Intelligence (2008)

186 Citations

Algorithm selection and scheduling

Serdar Kadioglu;Yuri Malitsky;Ashish Sabharwal;Horst Samulowitz.
principles and practice of constraint programming (2011)

185 Citations

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

Todor Mihaylov;Peter Clark;Tushar Khot;Ashish Sabharwal.
empirical methods in natural language processing (2018)

166 Citations

UNIFIEDQA: Crossing Format Boundaries with a Single QA System

Daniel Khashabi;Sewon Min;Tushar Khot;Ashish Sabharwal.
empirical methods in natural language processing (2020)

149 Citations

Model counting: a new strategy for obtaining good bounds

Carla P. Gomes;Ashish Sabharwal;Bart Selman.
national conference on artificial intelligence (2006)

146 Citations

Understanding the power of clause learning

Paul Beanie;Henry Kautz;Ashish Sabharwal.
international joint conference on artificial intelligence (2003)

124 Citations

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

Peter Clark;Oren Etzioni;Tushar Khot;Ashish Sabharwal.
national conference on artificial intelligence (2016)

123 Citations

If you think any of the details on this page are incorrect, let us know.

Contact us

Best Scientists Citing Ashish Sabharwal

Holger H. Hoos

Holger H. Hoos

Leiden University

Publications: 40

Chitta Baral

Chitta Baral

Arizona State University

Publications: 37

Xiang Ren

Xiang Ren

University of Southern California

Publications: 35

Carla P. Gomes

Carla P. Gomes

Cornell University

Publications: 35

Stefan Szeider

Stefan Szeider

TU Wien

Publications: 29

Frank Hutter

Frank Hutter

University of Freiburg

Publications: 28

Peter Clark

Peter Clark

Allen Institute for Artificial Intelligence

Publications: 27

Stefano Ermon

Stefano Ermon

Stanford University

Publications: 26

Moshe Y. Vardi

Moshe Y. Vardi

Rice University

Publications: 26

Yejin Choi

Yejin Choi

Allen Institute for Artificial Intelligence

Publications: 25

Hannaneh Hajishirzi

Hannaneh Hajishirzi

University of Washington

Publications: 24

Jonathan Berant

Jonathan Berant

Tel Aviv University

Publications: 24

Joao Marques-Silva

Joao Marques-Silva

Centre national de la recherche scientifique, CNRS

Publications: 23

Bart Selman

Bart Selman

Cornell University

Publications: 23

Dan Roth

Dan Roth

University of Pennsylvania

Publications: 22

Samuel R. Bowman

Samuel R. Bowman

New York University

Publications: 20

Something went wrong. Please try again later.