Tushar Khot

4.8k total citations · 1 hit paper
48 papers, 1.4k citations indexed

About

Tushar Khot is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Tushar Khot has authored 48 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Artificial Intelligence, 13 papers in Computer Vision and Pattern Recognition and 10 papers in Information Systems. Recurrent topics in Tushar Khot's work include Topic Modeling (25 papers), Natural Language Processing Techniques (25 papers) and Bayesian Modeling and Causal Inference (12 papers). Tushar Khot is often cited by papers focused on Topic Modeling (25 papers), Natural Language Processing Techniques (25 papers) and Bayesian Modeling and Causal Inference (12 papers). Tushar Khot collaborates with scholars based in United States, Germany and Belgium. Tushar Khot's co-authors include Ashish Sabharwal, Peter E. Clark, Todor Mihaylov, Niranjan Balasubramanian, Sriraam Natarajan, Harsh Trivedi, Daniel Khashabi, Kristian Kersting, Jude Shavlik and Dan Roth and has published in prestigious journals such as Machine Learning, Lecture notes in computer science and Knowledge and Information Systems.

In The Last Decade

Tushar Khot

46 papers receiving 1.3k citations

Hit Papers

Can a Suit of Armor Conduct Electricity? A New Dataset fo... 2018 2026 2020 2023 2018 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering
    2018 284 citations Todor Mihaylov, Peter E. Clark et al. profile →

Peers

Tushar Khot
Chandra Bhagavatula United States
Patrick Lewis United Kingdom
Adam Fisch United States
Andrew M. Dai United States
Wenhu Chen United States
Tom Kwiatkowski United States
Yeyun Gong China
Yun-Nung Chen Taiwan
Yichun Yin China
Shashi Narayan United Kingdom
Chandra Bhagavatula United States
Tushar Khot
Citations per year, relative to Tushar Khot Tushar Khot (= 1×) peers Chandra Bhagavatula

Countries citing papers authored by Tushar Khot

Since Specialization
Citations

This map shows the geographic impact of Tushar Khot's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tushar Khot with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tushar Khot more than expected).

Fields of papers citing papers by Tushar Khot

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tushar Khot. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tushar Khot. The network helps show where Tushar Khot may publish in the future.

Co-authorship network of co-authors of Tushar Khot

This figure shows the co-authorship network connecting the top 25 collaborators of Tushar Khot. A scholar is included among the top collaborators of Tushar Khot based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tushar Khot. Tushar Khot is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Bogin, Ben, Shashank Gupta, Kyle Richardson, et al.. (2024). SUPER: Evaluating Agents on Setting Up and Executing Tasks from Research Repositories. 12622–12645. 1 indexed citations
2.
Koller, Alexander, Mareike Hartmann, Peter Clark, et al.. (2024). ADaPT: As-Needed Decomposition and Planning with Language Models. 4226–4252. 9 indexed citations
3.
Trivedi, Harsh, Tushar Khot, Mareike Hartmann, et al.. (2024). AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents. 16022–16076.
4.
Trivedi, Harsh, Niranjan Balasubramanian, Tushar Khot, & Ashish Sabharwal. (2023). Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions. 10014–10037. 91 indexed citations
5.
Khashabi, Daniel, Xinxi Lyu, Sewon Min, et al.. (2022). Prompt Waywardness: The Curious Case of Discretized Interpretation of Continuous Prompts. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 3631–3643. 22 indexed citations
6.
Trivedi, Harsh, Niranjan Balasubramanian, Tushar Khot, & Ashish Sabharwal. (2022). Teaching Broad Reasoning Skills for Multi-Step QA by Generating Hard Contexts. 6541–6566. 2 indexed citations
7.
Trivedi, Harsh, Niranjan Balasubramanian, Tushar Khot, & Ashish Sabharwal. (2022). ♫ MuSiQue: Multihop Questions via Single-hop Question Composition. Transactions of the Association for Computational Linguistics. 10. 539–554. 64 indexed citations
8.
Sabharwal, Ashish, et al.. (2021). ReadOnce Transformers: Reusable Representations of Text for Transformers. 7129–7141. 2 indexed citations
9.
Khashabi, Daniel, Tushar Khot, & Ashish Sabharwal. (2020). Natural Perturbation for Robust Question Answering. arXiv (Cornell University). 2 indexed citations
10.
Mihaylov, Todor, Peter E. Clark, Tushar Khot, & Ashish Sabharwal. (2018). Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering. 2381–2391. 284 indexed citations breakdown →
11.
Kang, Dongyeop, Tushar Khot, Ashish Sabharwal, & Eduard Hovy. (2018). AdvEntuRe: Adversarial Training for Textual Entailment with Knowledge-Guided Examples. 31 indexed citations
12.
Khashabi, Daniel, Tushar Khot, Ashish Sabharwal, & Dan Roth. (2017). Learning What is Essential in Questions. 80–89. 20 indexed citations
13.
Khashabi, Daniel, Tushar Khot, Ashish Sabharwal, et al.. (2016). Question answering via integer programming over semi-structured knowledge. arXiv (Cornell University). 1145–1152. 12 indexed citations
14.
Natarajan, Sriraam, et al.. (2016). Markov logic networks for adverse drug event extraction from text. Knowledge and Information Systems. 51(2). 435–457. 9 indexed citations
15.
Yang, Shuo, Tushar Khot, Kristian Kersting, & Sriraam Natarajan. (2016). Learning Continuous-Time Bayesian Networks in Relational Domains: A Non-Parametric Approach. Proceedings of the AAAI Conference on Artificial Intelligence. 30(1). 7 indexed citations
16.
Khot, Tushar, et al.. (2015). Anomaly Detection in Text: The Value of Domain Knowledge.. The Florida AI Research Society. 225–228. 7 indexed citations
17.
Khot, Tushar, et al.. (2015). Extracting Adverse Drug Events from Text Using Human Advice. Lecture notes in computer science. 2015. 195–204. 9 indexed citations
18.
Yang, Shuo, Tushar Khot, Kristian Kersting, et al.. (2014). Learning from Imbalanced Data in Relational Domains: A Soft Margin Approach. 1085–1090. 13 indexed citations
19.
Natarajan, Sriraam, Tushar Khot, Kristian Kersting, Bernd Gutmann, & Jude Shavlik. (2010). Boosting relational dependency networks. Lirias (KU Leuven). 1–8. 6 indexed citations
20.
Zhu, Xiaojin, Andrew B. Goldberg, & Tushar Khot. (2009). Some new directions in graph-based semi-supervised learning. 1504–1507. 16 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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