🧑‍🔬 Rishi Bommasani — all works

33 works · ← Rishi Bommasani

1. On the Opportunities and Risks of Foundation ModelsarXiv:2108.07258Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,160 citations
2. Emergent Abilities of Large Language ModelsarXiv:2206.07682Jason Wei, Yi Tay, Rishi Bommasani, et al.2022 · 2,269 citations
3. BLOOM: A 176B-Parameter Open-Access Multilingual Language Model ↗arXiv:2211.05100 · no summary yetBigScience Workshop et al.2022 · 1,606 citations
4. Holistic Evaluation of Language Models ↗arXiv:2211.09110 · Published in Transactions on Machine Learning Research (TMLR), 2023 · no summary yetPercy Liang et al.2022 · 1,001 citations
5. Interpreting Pretrained Contextualized Representations via Reductions to Static EmbeddingsAnnual Meeting of the Association for Computational Linguistics (ACL)Rishi Bommasani, Kelly Davis, Claire Cardie2020 · 250 citations
6. Evaluating Human-Language Model Interaction ↗arXiv (Cornell University) · no summary yetMina Lee et al.2022 · 110 citations
7. Intrinsic Evaluation of Summarization Datasets ↗Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · no summary yetRishi Bommasani, Claire Cardie2020 · 96 citations
8. Picking on the Same Person: Does Algorithmic Monoculture Lead to Outcome Homogenization? ↗neural information processing systems · no summary yetRishi Bommasani et al.2022 · 78 citations
9. The Foundation Model Transparency Index ↗arXiv:2310.12941 · no summary yetRishi Bommasani et al.2023 · 76 citations
10. Foundation Model Transparency Reports ↗Proceedings of the AAAI/ACM Conference on AI Ethics and Society · no summary yetRishi Bommasani et al.2024 · 53 citations
11. International AI Safety Report ↗arXiv (Cornell University) · no summary yetYoshua Bengio et al.2025 · 41 citations
12. Considerations for governing open foundation models ↗Science · no summary yetRishi Bommasani et al.2024 · 36 citations
13. On the Societal Impact of Open Foundation Models ↗arXiv (Cornell University) · no summary yetSayash Kapoor et al.2024 · 30 citations
14. Advancing science- and evidence-based AI policy ↗Science · no summary yetRishi Bommasani et al.2025 · 25 citations
15. Ecosystem Graphs: The Social Footprint of Foundation Models ↗Research Square · no summary yetRishi Bommasani et al.2023 · 23 citations
16. A Safe Harbor for AI Evaluation and Red Teaming ↗arXiv (Cornell University) · no summary yetShayne Longpre et al.2024 · 22 citations
17. The Foundation Model Transparency Index v1.1: May 2024 ↗arXiv (Cornell University) · no summary yetRishi Bommasani et al.2024 · 14 citations
18. International Scientific Report on the Safety of Advanced AI (Interim Report) ↗arXiv (Cornell University) · no summary yetYoshua Bengio et al.2024 · 13 citations
19. Holistic Agent Leaderboard: The Missing Infrastructure for AI Agent Evaluation ↗arXiv:2510.11977 · no summary yetSayash Kapoor et al.2025 · 11 citations
20. The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources ↗arXiv (Cornell University) · no summary yetShayne Longpre et al.2024 · 11 citations
21. Trustworthy Social Bias Measurement ↗Proceedings of the AAAI/ACM Conference on AI Ethics and Society · no summary yetRishi Bommasani, Percy Liang2022 · 11 citations
22. The 2025 Foundation Model Transparency Index ↗SuperIntelligence - Robotics - Safety & Alignment · no summary yetAlexander Wan et al.2026 · 9 citations
23. AI Regulation Has Its Own Alignment Problem: The Technical and Institutional Feasibility of Disclosure, Registration, Licensing, and Auditing ↗bepress Legal Repository · no summary yetNeel Guha et al.2024 · 8 citations
24. Language model developers should report train-test overlap ↗arXiv (Cornell University) · no summary yetAndy K. Zhang et al.2024 · 8 citations
25. Position: On the Societal Impact of Open Foundation Models ↗ANU Open Research (Australian National University) · no summary yetSayash Kapoor et al.2024 · 6 citations
26. Cheaply Evaluating Inference Efficiency Metrics for Autoregressive Transformer APIs ↗arXiv (Cornell University) · no summary yetDeepak Narayanan et al.2023 · 6 citations
27. Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes ↗arXiv (Cornell University) · no summary yetConnor Toups et al.2023 · 4 citations
28. Cheaply Estimating Inference Efficiency Metrics for Autoregressive Transformer Models ↗neural information processing systems · no summary yetDeepak Narayanan et al.2023 · 3 citations
29. Algorithmic Monocultures in Hiring ↗ACM Conference on Fairness, Accountability, and Transparency (FAccT) · no summary yetRishi Bommasani et al.2026 · 2 citations
30. In-House Evaluation Is Not Enough: Towards Robust Third-Party Flaw Disclosure for General-Purpose AI ↗arXiv (Cornell University) · no summary yetShayne Longpre et al.2025 · 2 citations
31. The California Report on Frontier AI Policy ↗arXiv (Cornell University) · no summary yetRishi Bommasani et al.2025 · 1 citation
32. FLARE-AI: Flaw Reporting for AI ↗arXiv (Cornell University) · no summary yetShayne Longpre et al.2026
33. Economic Evaluations of Language Models ↗arXiv (Cornell University) · no summary yetAlexander Wan et al.2026

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