🧑‍🔬 Varsha Kishore

🏛️ Affiliations

🎓Cornell UniversityIthaca · United States2021–2026 · 4 paperscurrent🔬Allen Institute for Artificial IntelligenceSeattle · United States2026 · 2 paperscurrent🎓University of WashingtonSeattle · United States2026 · 1 papercurrent

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.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research (2025 · 28 citations)
   Open deep research (DR) agents are usually trained with reinforcement learning on short questions whose answers can be checked automatically. That kind of reward does not transfer to open-ended, long-form reports, where quality is loosely defined and checking claims requires current external evidence.
2. AstaBench: Rigorous Benchmarking of AI Agents with a Scientific Research Suite (2025 · 19 citations)
   Evaluating AI agents for scientific work is hard to do fairly. Existing benchmark suites rarely give every agent the same tools and information sources, and they seldom factor in inference cost. They also tie tasks to particular agent frameworks, rarely reflect how people actually use such systems, and include few…

All works

7 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. BERTScore: Evaluating Text Generation with BERT ↗arXiv:1904.09675 · no summary yetTianyi Zhang et al.2019 · 6,066 citations
2. Synthesizing scientific literature with retrieval-augmented language models ↗Nature · no summary yetAkari Asai et al.2026 · 42 citations
3. ReasonIR: Training Retrievers for Reasoning Tasks ↗arXiv (Cornell University) · no summary yetRulin Shao et al.2025 · 41 citations
4. DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep ResearcharXiv:2511.19399Rulin Shao, Akari Asai, Shannon Zejiang Shen, et al.2025 · 28 citations
5. AstaBench: Rigorous Benchmarking of AI Agents with a Scientific Research SuitearXiv:2510.21652Jonathan Bragg, Mike D'Arcy, Nishant Balepur, et al.2025 · 19 citations
6. 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
7. 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 of 17 co-authors with a page, the most papers together first.

• Aakanksha Naik
• Akari Asai
• Bhavana Dalvi
• Bodhisattwa Prasad Majumder
• Dan Bareket
• David Sontag
• Hamish Ivison
• Jena D. Hwang
• Jonathan Bragg
• Mike D'Arcy
• Nishant Balepur
• Peter Jansen

Venues

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

• Nature
• Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

🔗 Cited by

Papers of our library cite their works 3,892 times (of the 149,439 papers whose bibliographies we read); 625 citing papers with a page here →.

Updated 3 November 2026

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