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Kinjal Basu

Kinjal Basu has 2 papers in our library, in 2021–2025, most of them on Language models & pretraining, Evaluation & benchmarks, English; often with Ibrahim Abdelaziz, Luis Lastras, Sadhana Kumaravel.

2 papers in our library · 2021–2025

OpenAlex · ORCID · Wikidata · h-index 7 · 34 works · 154 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 58 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #9088

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

🏢IBMArmonk · United States2023–2026 · 17 paperscurrent🎓The University of Texas at DallasRichardson · United States2018–2023 · 12 papersEducation 2018–2022 · Doctorate, Computer Science🏢MicrosoftRedmond · United States2021 · 4 papers🏢LinkedInSunnyvale · United States2021–2022 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

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

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksInformation Systems · 1 work

🧭 Topics 3Research subjects and languages the work is about.English · 1 workEvaluation & benchmarks · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20251 paper20211 paper

 Papers

The most cited first (OpenAlex and our library).

  1. NESTFUL: A Benchmark for Evaluating LLMs on Nested Sequences of API Calls (2025 · 16 citations)
    Benchmarks for LLM tool calling usually treat an API sequence as a set of independent calls. Many real tasks instead need nesting, where one call's result becomes an argument to a later call. NESTFUL (IBM Research) targets this gap with more than 1,800 nested sequences built from MathQA and StarCoder2-Instruct.
  2. Knowledge-driven Natural Language Understanding of English Text and its Applications (2021 · 4 citations)
    The paper argues that systems which answer questions or hold conversations should first turn text into an explicit meaning representation and then reason over it, rather than rely on word correlations.

All works

3 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. Granite Code Models: A Family of Open Foundation Models for Code Intelligence ↗arXiv:2405.04324 · no summary yetMayank Mishra et al.2024 · 54 citations
  2. NESTFUL: A Benchmark for Evaluating LLMs on Nested Sequences of API CallsConference on Empirical Methods in Natural Language Processing (EMNLP)Kinjal Basu, Ibrahim Abdelaziz, Kiran Kate, et al.2025 · 16 citations
  3. Knowledge-driven Natural Language Understanding of English Text and its ApplicationsProceedings of the AAAI Conference on Artificial IntelligenceKinjal Basu, Sarat Varanasi, Farhad Shakerin, et al.2021 · 4 citations

 Co-authors here

4 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 58 times (of the 149,439 papers whose bibliographies we read); 12 citing papers with a page here →.

Updated

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