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Aakanksha Naik

Aakanksha Naik has 2 papers in our library, in 2019–2025, most of them on Language models & pretraining, Evaluation & benchmarks, Reasoning; often with Abhilasha Ravichander, Alan Li, Carolyn Penstein Rosé.

2 papers in our library · 2019–2025

OpenAlex · ORCID · Wikidata · h-index 12 · 69 works · 568 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 1,001 times in our library · 6 more in our library without a page yet · ⭐ Paper Stars ranking: #6195

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

🔬Allen Institute for Artificial IntelligenceSeattle · United States2022–2026 · 39 paperscurrent🔬Allen InstituteSeattle · United States2023–2026 · 4 paperscurrent🔬Allen Institute for ImmunologySeattle · United States2026 · 1 papercurrent🎓Carnegie Mellon UniversityPittsburgh · United States2017–2024 · 20 papers🎓University of WashingtonSeattle · United States2024 · 5 papers🏛️National Institutes of HealthBethesda · United States2021–2022 · 3 papers🏥National Institutes of Health Clinical CenterBethesda · United States2021–2022 · 3 papers🎓University of California, BerkeleyBerkeley · United States2024 · 2 papers🎓Yale UniversityNew Haven · United States2024 · 2 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 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 workInformation Systems · 1 work

🧭 Topics 4Research subjects and languages the work is about.Language models & pretraining · 1 workEnglish · 1 workEvaluation & benchmarks · 1 workReasoning · 1 work

 Works by year

2020s

20251 paper

2010s

20191 paper

 Papers

The most cited first (OpenAlex and our library).

  1. EQUATE: A Benchmark Evaluation Framework for Quantitative Reasoning in Natural Language Inference (2019 · 123 citations)
    EQUATE is a benchmark of five test sets for quantitative reasoning in entailment: RTE-Quant (166 pairs from RTE2–4), NewsNLI (968 crowdsourced pairs from news summaries), RedditNLI (250 expert-labelled headline pairs), a synthetic stress test (7,500 pairs) and AwpNLI (722 algebra word problems turned into pairs).
  2. SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific Literature (2025 · 27 citations)
    Researchers increasingly want LLMs that can work directly with scientific papers. That means following detailed instructions over long article text and returning structured, evidence-backed answers. Few training resources target this skill across multiple fields. The authors address the gap with SciRIFF, a…

All works

8 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. OLMo: Accelerating the Science of Language Models ↗Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetDirk Groeneveld et al.2024 · 429 citations
  2. Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research ↗Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetLuca Soldaini et al.2024 · 341 citations
  3. Stress Test Evaluation for Natural Language Inference ↗Proceedings of the 27th International Conference on Computational Linguistics · no summary yetAakanksha Naik et al.2018 · 285 citations
  4. EQUATE: A Benchmark Evaluation Framework for Quantitative Reasoning in Natural Language InferenceAbhilasha Ravichander, Aakanksha Naik, Carolyn Rose, et al.English · 123 citations
  5. SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific LiteratureConference on Empirical Methods in Natural Language Processing (EMNLP)David Wadden, Kejian Shi, Jacob Morrison, et al.2025 · 27 citations
  6. AstaBench: Rigorous Benchmarking of AI Agents with a Scientific Research Suite ↗arXiv:2510.21652 · no summary yetJonathan Bragg et al.2025 · 19 citations
  7. Language Models Don't Know What You Want: Evaluating Personalization in Deep Research Needs Real Users ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetNishant Balepur et al.2026 · 2 citations
  8. DRACULA: Hunting for the Actions Users Want Deep Research Agents to Execute ↗arXiv (Cornell University) · no summary yetNishant Balepur et al.2026 · 1 citation

 Co-authors here

12 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 1,001 times (of the 149,439 papers whose bibliographies we read); 209 citing papers with a page here →.

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