Vishakh Padmakumar

983 total citations
13 papers, 180 citations indexed

About

Vishakh Padmakumar is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Ophthalmology. According to data from OpenAlex, Vishakh Padmakumar has authored 13 papers receiving a total of 180 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 2 papers in Ophthalmology. Recurrent topics in Vishakh Padmakumar's work include Topic Modeling (9 papers), Natural Language Processing Techniques (7 papers) and Multimodal Machine Learning Applications (3 papers). Vishakh Padmakumar is often cited by papers focused on Topic Modeling (9 papers), Natural Language Processing Techniques (7 papers) and Multimodal Machine Learning Applications (3 papers). Vishakh Padmakumar collaborates with scholars based in United States, India and United Kingdom. Vishakh Padmakumar's co-authors include He He, Nikita Nangia, Jason Phang, Jana Thompson, Alicia Parrish, Samuel Bowman, Tuhin Chakrabarty, Phu Mon Htut, Jonathan Nagler and Fridolin Linder and has published in prestigious journals such as Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Findings of the Association for Computational Linguistics: ACL 2022 and Creativity and Cognition.

In The Last Decade

Vishakh Padmakumar

10 papers receiving 170 citations

Peers

Vishakh Padmakumar
Hila Gonen United States
Rachel Rudinger United States
Shauli Ravfogel Israel
Paul Röttger United Kingdom
Nikita Nangia United States
Sashank Santhanam United States
Lea Frermann Australia
Amin Ahmad Pakistan
Silviu Paun United Kingdom
Yi R. Fung United States
Hila Gonen United States
Vishakh Padmakumar
Citations per year, relative to Vishakh Padmakumar Vishakh Padmakumar (= 1×) peers Hila Gonen

Countries citing papers authored by Vishakh Padmakumar

Since Specialization
Citations

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

Fields of papers citing papers by Vishakh Padmakumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vishakh Padmakumar

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

All Works

13 of 13 papers shown
1.
Chakrabarty, Tuhin, et al.. (2024). Creativity Support in the Age of Large Language Models: An Empirical Study Involving Professional Writers. Creativity and Cognition. 132–155. 11 indexed citations
2.
Chakrabarty, Tuhin, Vishakh Padmakumar, He He, & Nanyun Peng. (2023). Creative Natural Language Generation. 34–40.
3.
Pang, Richard Yuanzhe, Vishakh Padmakumar, Thibault Sellam, Ankur P. Parikh, & He He. (2023). Reward Gaming in Conditional Text Generation. 4746–4763. 1 indexed citations
4.
Guan, Shuo & Vishakh Padmakumar. (2023). Extract, Select and Rewrite: A Modular Sentence Summarization Method. 41–48.
5.
Parrish, Alicia, Nikita Nangia, Vishakh Padmakumar, et al.. (2022). BBQ: A hand-built bias benchmark for question answering. Findings of the Association for Computational Linguistics: ACL 2022. 2086–2105. 64 indexed citations
6.
Pang, Richard Yuanzhe, Alicia Parrish, Nikita Nangia, et al.. (2022). QuALITY: Question Answering with Long Input Texts, Yes!. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 5336–5358. 21 indexed citations
7.
Chakrabarty, Tuhin, Vishakh Padmakumar, & He He. (2022). Help me write a poem: Instruction Tuning as a Vehicle for Collaborative Poetry Writing. 6848–6863. 18 indexed citations
8.
Patil, Mayur, et al.. (2022). Qualitative and Quantitative Evaluation of Donor Corneal Tissue by Slit Lamp and Specular Microscopy. Cureus. 14(5). e24700–e24700. 5 indexed citations
9.
Padmakumar, Vishakh, Leonard Lausen, Miguel Ballesteros, et al.. (2022). Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 2542–2550. 14 indexed citations
10.
Padmakumar, Vishakh & He He. (2022). Machine-in-the-Loop Rewriting for Creative Image Captioning. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 4 indexed citations
11.
Padmakumar, Vishakh & He He. (2021). Unsupervised Extractive Summarization using Pointwise Mutual Information. 2505–2512. 18 indexed citations
12.
Padmakumar, Vishakh, et al.. (2021). Association of HbA1c levels with diabetic retinopathy. Indian Journal of Clinical and Experimental Ophthalmology. 7(2). 339–345. 1 indexed citations
13.
Linder, Fridolin, Vishakh Padmakumar, Michael C. Liu, et al.. (2020). A Comparison of Methods in Political Science Text Classification: Transfer Learning Language Models for Politics. SSRN Electronic Journal. 23 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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