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Kaustubh Dhole

Kaustubh Dhole has 2 papers in our library, in 2021–2023, most of them on Text generation, Evaluation & benchmarks; often with Sebastian Gehrmann, Antoine Bosselut, Anuoluwapo Aremu.

2 papers in our library · 2021–2023

OpenAlex · ORCID · h-index 13 · 62 works · 1,213 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 1,780 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #4485

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Emory UniversityAtlanta · United States2022–2026 · 42 paperscurrent🎓Birla Institute of Technology and Science, PilaniPilāni · India2014–2015 · 5 papers🎓Tata Institute of Fundamental ResearchMumbai · India2016–2021 · 4 papers🎓Birla Institute of Technology and Science, Pilani - Goa CampusSancoale · India2014 · 4 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 2Research subjects and languages the work is about.Evaluation & benchmarks · 1 workText generation · 1 work

 Works by year

2020s

20231 paper20211 paper

 Papers

The most cited first (OpenAlex and our library).

  1. The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics (2021 · 369 citations)
    The authors start from the observation that progress in natural language generation (NLG) is hard to measure.
  2. NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation (2023 · 86 citations)
    Data augmentation is used both to stress-test NLP models and to make their training data more diverse. Most existing perturbation tools offer a narrow, largely English set of edits that are rarely matched to a specific task. NL-Augmenter addresses this with an open, community-built Python library. It grew out of the…

All works

4 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. The GEM Benchmark: Natural Language Generation, its Evaluation and MetricsWorkshop on Generation, Evaluation and Metrics (GEM)Sebastian Gehrmann, Tosin Adewumi, Karmanya Aggarwal, et al.2021 · 369 citations
  2. NusaCrowd: Open Source Initiative for Indonesian NLP Resources ↗Findings of the Association for Computational Linguistics: ACL 2023 · no summary yetSamuel Cahyawijaya et al.2023 · 95 citations
  3. NL-Augmenter: A Framework for Task-Sensitive Natural Language AugmentationNorthern European Journal of Language TechnologyKaustubh Dhole, Varun Gangal, Sebastian Gehrmann, et al.2023 · 86 citations
  4. Syn-QG: Syntactic and Shallow Semantic Rules for Question Generation ↗Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · no summary yetKaustubh Dhole, Christopher D. Manning2020 · 73 citations

 Co-authors here

12 of 14 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 1,780 times (of the 149,439 papers whose bibliographies we read); 478 citing papers with a page here →.

Updated

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