| 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 | 2692 | 2021 |
| Ask me anything: A simple strategy for prompting language models S Arora, A Narayan, MF Chen, L Orr, N Guha, K Bhatia, I Chami, C Re The Eleventh International Conference on Learning Representations, 2022 | 124 | 2022 |
| Decodingtrust: A comprehensive assessment of trustworthiness in gpt models B Wang, W Chen, H Pei, C Xie, M Kang, C Zhang, C Xu, Z Xiong, R Dutta, ... arXiv preprint arXiv:2306.11698, 2023 | 106 | 2023 |
| Can foundation models wrangle your data? A Narayan, I Chami, L Orr, S Arora, C Ré arXiv preprint arXiv:2205.09911, 2022 | 90 | 2022 |
| Contextual embeddings: When are they worth it? S Arora, A May, J Zhang, C Ré arXiv preprint arXiv:2005.09117, 2020 | 69 | 2020 |
| A temperature-mapping molecular sensor for polyurethane-based elastomers BP Mason, M Whittaker, J Hemmer, S Arora, A Harper, S Alnemrat, ... Applied Physics Letters 108 (4), 2016 | 64* | 2016 |
| Bootleg: Chasing the tail with self-supervised named entity disambiguation L Orr, M Leszczynski, S Arora, S Wu, N Guha, X Ling, C Re arXiv preprint arXiv:2010.10363, 2020 | 49 | 2020 |
| Language models enable simple systems for generating structured views of heterogeneous data lakes S Arora, B Yang, S Eyuboglu, A Narayan, A Hojel, I Trummer, C Ré arXiv preprint arXiv:2304.09433, 2023 | 20 | 2023 |
| Optimizing declarative graph queries at large scale Q Zhang, A Acharya, H Chen, S Arora, A Chen, V Liu, BT Loo Proceedings of the 2019 International Conference on Management of Data, 1411 …, 2019 | 20 | 2019 |
| Control of multiple microrobots with multiscale magnetic field superposition E Steager, D Wong, J Wang, S Arora, V Kumar International Conference on Manipulation, Automation and Robotics at Small …, 2017 | 13 | 2017 |
| Monarch mixer: A simple sub-quadratic gemm-based architecture D Fu, S Arora, J Grogan, I Johnson, ES Eyuboglu, A Thomas, B Spector, ... Advances in Neural Information Processing Systems 36, 2024 | 11 | 2024 |
| Zoology: Measuring and improving recall in efficient language models S Arora, S Eyuboglu, A Timalsina, I Johnson, M Poli, J Zou, A Rudra, C Ré arXiv preprint arXiv:2312.04927, 2023 | 9 | 2023 |
| Reasoning over public and private data in retrieval-based systems S Arora, P Lewis, A Fan, J Kahn, C Ré Transactions of the Association for Computational Linguistics 11, 902-921, 2022 | 9* | 2022 |
| Metadata shaping: A simple approach for knowledge-enhanced language models S Arora, S Wu, E Liu, C Ré Findings of the Association for Computational Linguistics: ACL 2022, 1733-1745, 2022 | 7 | 2022 |
| RELIC: Investigating Large Language Model Responses using Self-Consistency F Cheng, V Zouhar, S Arora, M Sachan, H Strobelt, M El-Assady arXiv preprint arXiv:2311.16842, 2023 | 2 | 2023 |
| Can Foundation Models Help Us Achieve Perfect Secrecy? S Arora, C Ré arXiv preprint arXiv:2205.13722, 2022 | 2 | 2022 |
| Benchmarking and Building Long-Context Retrieval Models with LoCo and M2-BERT J Saad-Falcon, DY Fu, S Arora, N Guha, C Ré arXiv preprint arXiv:2402.07440, 2024 | 1 | 2024 |
| Optimistic Verifiable Training by Controlling Hardware Nondeterminism M Srivastava, S Arora, D Boneh arXiv preprint arXiv:2403.09603, 2024 | | 2024 |
| Simple linear attention language models balance the recall-throughput tradeoff S Arora, S Eyuboglu, M Zhang, A Timalsina, S Alberti, D Zinsley, J Zou, ... arXiv preprint arXiv:2402.18668, 2024 | | 2024 |
| Resources and Evaluations for Multi-Distribution Dense Information Retrieval S Chatterjee, O Khattab, S Arora arXiv preprint arXiv:2306.12601, 2023 | | 2023 |
Christopher RéComputer Science, Stanford University在 cs.stanford.edu 的电子邮件经过验证
