| 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 | 5372 | 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 | 3194 | 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, ... | 1775 | 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 | 1282 | 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 | 202 | 2020 |
| Evaluating human-language model interaction M Lee, M Srivastava, A Hardy, J Thickstun, E Durmus, A Paranjape, ... arXiv preprint arXiv:2212.09746, 2022 | 124 | 2022 |
| The foundation model transparency index R Bommasani, K Klyman, S Longpre, S Kapoor, N Maslej, B Xiong, ... arXiv preprint arXiv:2310.12941, 2023 | 107 | 2023 |
| 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 | 92 | 2022 |
| Intrinsic evaluation of summarization datasets R Bommasani, C Cardie Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 84 | 2020 |
| 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 | 75 | 2022 |
| Emergent abilities of large language models. arXiv 2022 J Wei, Y Tay, R Bommasani, C Raffel, B Zoph, S Borgeaud, D Yogatama, ... arXiv preprint arXiv:2206.07682, 2023 | 69 | 2023 |
| On the societal impact of open foundation models S Kapoor, R Bommasani, K Klyman, S Longpre, A Ramaswami, P Cihon, ... arXiv preprint arXiv:2403.07918, 2024 | 49* | 2024 |
| Do foundation model providers comply with the draft EU AI act R Bommasani, K Klyman, D Zhang, P Liang available at Stanford CRFM, 2023 | 42 | 2023 |
| Emergent abilities of large language models (2022) J Wei, Y Tay, R Bommasani, C Raffel, B Zoph, S Borgeaud, D Yogatama, ... arXiv preprint arXiv:2206.07682, 0 | 39 | |
| Ecosystem graphs: The social footprint of foundation models R Bommasani, D Soylu, TI Liao, KA Creel, P Liang arXiv preprint arXiv:2303.15772, 2023 | 37* | 2023 |
| A safe harbor for ai evaluation and red teaming S Longpre, S Kapoor, K Klyman, A Ramaswami, R Bommasani, ... arXiv preprint arXiv:2403.04893, 2024 | 36 | 2024 |
| Ai regulation has its own alignment problem: The technical and institutional feasibility of disclosure, registration, licensing, and auditing N Guha, CM Lawrence, LA Gailmard, KT Rodolfa, F Surani, R Bommasani, ... Geo. Wash. L. Rev. 92, 1473, 2024 | 29 | 2024 |
| The time is now to develop community norms for the release of foundation models P Liang, R Bommasani, K Creel, R Reich Protocol, 2022 | 27* | 2022 |
| On the opportunities and risks of foundation models (2022) R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 0 | 27 | |
| Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al. 2021 R Bommasani, DA Hudson, E Adeli, R Altman, S Arora On the opportunities and risks of foundation models. ArXiv preprint, abs …, 2021 | 26 | 2021 |
Percy LiangAssociate Professor of Computer Science, Stanford UniversityПотвърден имейл адрес: cs.stanford.edu