| On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2021 | 2909 | 2021 |
| Emergent abilities of large language models J Wei, Y Tay, R Bommasani, C Raffel, B Zoph, S Borgeaud, D Yogatama, ... arXiv preprint arXiv:2206.07682, 2022 | 1781* | 2022 |
| Bloom: A 176b-parameter open-access multilingual language model T Le Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow, R Castagné, ... | 1146 | 2023 |
| Holistic evaluation of language models P Liang, R Bommasani, T Lee, D Tsipras, D Soylu, M Yasunaga, Y Zhang, ... arXiv preprint arXiv:2211.09110, 2022 | 634 | 2022 |
| Interpreting pretrained contextualized representations via reductions to static embeddings R Bommasani, K Davis, C Cardie Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 166 | 2020 |
| On the opportunities and risks of foundation models (2021) R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2022 | 86* | 2022 |
| Intrinsic evaluation of summarization datasets R Bommasani, C Cardie Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 61 | 2020 |
| Evaluating human-language model interaction M Lee, M Srivastava, A Hardy, J Thickstun, E Durmus, A Paranjape, ... arXiv preprint arXiv:2212.09746, 2022 | 60 | 2022 |
| Data governance in the age of large-scale data-driven language technology Y Jernite, H Nguyen, S Biderman, A Rogers, M Masoud, V Danchev, ... Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022 | 48 | 2022 |
| Picking on the same person: Does algorithmic monoculture lead to outcome homogenization? R Bommasani, KA Creel, A Kumar, D Jurafsky, PS Liang Advances in Neural Information Processing Systems 35, 3663-3678, 2022 | 46 | 2022 |
| On the opportunities and risks of foundation models (arXiv: 2108.07258). arXiv R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... | 42 | 2022 |
| The foundation model transparency index R Bommasani, K Klyman, S Longpre, S Kapoor, N Maslej, B Xiong, ... arXiv preprint arXiv:2310.12941, 2023 | 24* | 2023 |
| Do foundation model providers comply with the eu ai act R Bommasani, K Klyman, D Zhang, P Liang Stanford Center for Research on Foundation Models, Institute for Human …, 2023 | 20 | 2023 |
| The time is now to develop community norms for the release of foundation models P Liang, R Bommasani, K Creel, R Reich Protocol, 2022 | 20* | 2022 |
| Reflections on foundation models R Bommasani, P Liang Stanford Institute for Human-Centered AI, 2021 | 19* | 2021 |
| Ecosystem graphs: The social footprint of foundation models R Bommasani, D Soylu, TI Liao, KA Creel, P Liang arXiv preprint arXiv:2303.15772, 2023 | 12* | 2023 |
| Towards Private Synthetic Text Generation R Bommasani, ZS Wu, A Schofield 2019 NeurIPS Workshop: Machine Learning with Guarantees, 2019 | 12* | 2019 |
| Ai regulation has its own alignment problem: The technical and institutional feasibility of disclosure, registration, licensing, and auditing N Guha, C Lawrence, LA Gailmard, K Rodolfa, F Surani, R Bommasani, ... George Washington Law Review, Forthcoming, 2023 | 10 | 2023 |
| Cheaply estimating inference efficiency metrics for autoregressive transformer models D Narayanan, K Santhanam, P Henderson, R Bommasani, T Lee, ... Advances in Neural Information Processing Systems 36, 2024 | 9* | 2024 |
| Foundation models in healthcare: Opportunities, risks & strategies forward A Thieme, A Nori, M Ghassemi, R Bommasani, TO Andersen, E Luger Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing …, 2023 | 7 | 2023 |
Percy LiangAssociate Professor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
