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Rishi Bommasani
Rishi Bommasani
Verified email at stanford.edu - Homepage
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Cited by
Year
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
45632021
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
3017*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, ...
16112023
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
11362022
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
1972020
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
151*2022
Evaluating human-language model interaction
M Lee, M Srivastava, A Hardy, J Thickstun, E Durmus, A Paranjape, ...
arXiv preprint arXiv:2212.09746, 2022
1042022
The foundation model transparency index
R Bommasani, K Klyman, S Longpre, S Kapoor, N Maslej, B Xiong, ...
arXiv preprint arXiv:2310.12941, 2023
85*2023
Intrinsic evaluation of summarization datasets
R Bommasani, C Cardie
Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020
852020
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
812022
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, ...
782022
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
682022
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
592023
Do foundation model providers comply with the draft EU AI Act
R Bommasani, K Klyman, D Zhang, P Liang
Stanford Center for Research on Foundation Models, https://crfm. stanford …, 2023
382023
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
36*2024
Ecosystem graphs: The social footprint of foundation models
R Bommasani, D Soylu, TI Liao, KA Creel, P Liang
arXiv preprint arXiv:2303.15772, 2023
312023
The time is now to develop community norms for the release of foundation models
P Liang, R Bommasani, K Creel, R Reich
Protocol, 2022
29*2022
Reflections on foundation models
R Bommasani, P Liang
Stanford Institute for Human-Centered AI, 2021
25*2021
On the opportunities and risks of foundation models; 10.48550
R Bommasani, DA Hudson
arXiv preprint ARXIV.2108.07258 4, 2021
24*2021
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
232023
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Articles 1–20