| 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 | 2848 | 2021 |
| Wilds: A benchmark of in-the-wild distribution shifts PW Koh, S Sagawa, H Marklund, SM Xie, M Zhang, A Balsubramani, ... arXiv preprint arXiv: 2012.07421, 2021 | 1164 | 2021 |
| 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 | 669* | 2022 |
| StarCoder: may the source be with you! R Li, LB Allal, Y Zi, N Muennighoff, D Kocetkov, C Mou, M Marone, C Akiki, ... arXiv preprint arXiv:2305.06161, 2023 | 391* | 2023 |
| Extending the WILDS Benchmark for Unsupervised Adaptation S Sagawa, PW Koh, T Lee, I Gao, SM Xie, K Shen, A Kumar, W Hu, ... arXiv preprint arXiv:2112.05090, 2021 | 94 | 2021 |
| Evaluating Human-Language Model Interaction M Lee, M Srivastava, A Hardy, J Thickstun, E Durmus, A Paranjape, ... arXiv preprint arXiv:2212.09746, 2022 | 59 | 2022 |
| Holistic Evaluation of Text-to-Image Models T Lee, M Yasunaga, C Meng, Y Mai, JS Park, A Gupta, Y Zhang, ... Thirty-seventh Conference on Neural Information Processing Systems Datasets …, 2023 | 22 | 2023 |
| Can small and synthetic benchmarks drive modeling innovation? a retrospective study of question answering modeling approaches NFLTL Robin, JP Liang | 20* | 2021 |
| 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 |
| BioMedLM: A 2.7 B Parameter Language Model Trained On Biomedical Text E Bolton, A Venigalla, M Yasunaga, D Hall, B Xiong, T Lee, R Daneshjou, ... arXiv preprint arXiv:2403.18421, 2024 | 7* | 2024 |
Percy LiangAssociate Professor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
