Harsh Jhamtani

471 total citations
14 papers, 102 citations indexed

About

Harsh Jhamtani is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Communication. According to data from OpenAlex, Harsh Jhamtani has authored 14 papers receiving a total of 102 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 1 paper in Communication. Recurrent topics in Harsh Jhamtani's work include Topic Modeling (8 papers), Natural Language Processing Techniques (8 papers) and Speech and dialogue systems (4 papers). Harsh Jhamtani is often cited by papers focused on Topic Modeling (8 papers), Natural Language Processing Techniques (8 papers) and Speech and dialogue systems (4 papers). Harsh Jhamtani collaborates with scholars based in United States, India and Switzerland. Harsh Jhamtani's co-authors include Taylor Berg-Kirkpatrick, Varun Gangal, Vaskar Raychoudhury, Eduard Hovy, Graham Neubig, Prakhar Gupta, Jeffrey P. Bigham, Jaime Carbonell, Bodhisattwa Prasad Majumder and Julian McAuley and has published in prestigious journals such as arXiv (Cornell University), Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) and Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.

In The Last Decade

Harsh Jhamtani

13 papers receiving 98 citations

Peers

Harsh Jhamtani
Rishabh Misra United States
Giannis Karamanolakis United States
Varun Gangal United States
Sweta Agrawal United States
Seth Neel United States
Potsawee Manakul United Kingdom
Harsh Jhamtani
Citations per year, relative to Harsh Jhamtani Harsh Jhamtani (= 1×) peers David Madras

Countries citing papers authored by Harsh Jhamtani

Since Specialization
Citations

This map shows the geographic impact of Harsh Jhamtani'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 Harsh Jhamtani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Harsh Jhamtani more than expected).

Fields of papers citing papers by Harsh Jhamtani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Harsh Jhamtani. 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 Harsh Jhamtani. The network helps show where Harsh Jhamtani may publish in the future.

Co-authorship network of co-authors of Harsh Jhamtani

This figure shows the co-authorship network connecting the top 25 collaborators of Harsh Jhamtani. A scholar is included among the top collaborators of Harsh Jhamtani 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 Harsh Jhamtani. Harsh Jhamtani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
Thomas, Ryan M., et al.. (2024). Ontologically Faithful Generation of Non-Player Character Dialogues. 9212–9242. 1 indexed citations
2.
Jhamtani, Harsh, et al.. (2024). Learning to Retrieve Iteratively for In-Context Learning. 7156–7168. 1 indexed citations
3.
Fang, Hao, Harsh Jhamtani, Jayant Krishnamurthy, et al.. (2023). The Whole Truth and Nothing But the Truth: Faithful and Controllable Dialogue Response Generation with Dataflow Transduction and Constrained Decoding. 5682–5700. 1 indexed citations
4.
Gupta, Prakhar, Harsh Jhamtani, & Jeffrey P. Bigham. (2022). Target-Guided Dialogue Response Generation Using Commonsense and Data Augmentation. 1301–1317. 9 indexed citations
5.
Majumder, Bodhisattwa Prasad, Harsh Jhamtani, Taylor Berg-Kirkpatrick, & Julian McAuley. (2022). Achieving Conversational Goals with Unsupervised Post-hoc Knowledge Injection. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2 indexed citations
6.
Jhamtani, Harsh, Varun Gangal, Eduard Hovy, & Taylor Berg-Kirkpatrick. (2021). Investigating Robustness of Dialog Models to Popular Figurative Language Constructs. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 7476–7485. 10 indexed citations
7.
Jhamtani, Harsh, et al.. (2021). Formulating Neural Sentence Ordering as the Asymmetric Traveling Salesman Problem. 128–139. 1 indexed citations
8.
Jhamtani, Harsh, et al.. (2019). A Sociolinguistic Study of Online Echo Chambers on Twitter. 78–83. 4 indexed citations
9.
Jhamtani, Harsh, et al.. (2019). Learning Rhyming Constraints using Structured Adversaries. 6024–6030. 7 indexed citations
10.
Jhamtani, Harsh & Taylor Berg-Kirkpatrick. (2018). Learning to Describe Differences Between Pairs of Similar Images. arXiv (Cornell University). 4024–4034. 7 indexed citations
11.
Jhamtani, Harsh, Varun Gangal, Eduard Hovy, Graham Neubig, & Taylor Berg-Kirkpatrick. (2018). Learning to Generate Move-by-Move Commentary for Chess Games from Large-Scale Social Forum Data. 1661–1671. 16 indexed citations
12.
Jhamtani, Harsh, et al.. (2016). A Supervised Approach for Text Illustration. 217–221. 3 indexed citations
13.
Jhamtani, Harsh, et al.. (2014). Word-level Language Identification in Bi-lingual Code-switched Texts. Pacific Asia Conference on Language, Information, and Computation. 348–357. 18 indexed citations
14.
Jhamtani, Harsh, et al.. (2014). Identifying Purchase Intent from Social Posts. Proceedings of the International AAAI Conference on Web and Social Media. 8(1). 180–186. 22 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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