| 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 | 3647 | 2021 |
| Stanford alpaca: An instruction-following llama model R Taori, I Gulrajani, T Zhang, Y Dubois, X Li, C Guestrin, P Liang, ... | 2225* | 2023 |
| Measuring Robustness to Natural Distribution Shifts in Image Classification R Taori, A Dave, V Shankar, N Carlini, B Recht, L Schmidt Advances in Neural Information Processing Systems 33, 2020 | 567 | 2020 |
| Openclip, July 2021 G Ilharco, M Wortsman, R Wightman, C Gordon, N Carlini, R Taori, ... URL https://doi. org/10.5281/zenodo 5143773, 29, 0 | 468* | |
| Alpacaeval: An automatic evaluator of instruction-following models X Li, T Zhang, Y Dubois, R Taori, I Gulrajani, C Guestrin, P Liang, ... | 303 | 2023 |
| Alpacafarm: A simulation framework for methods that learn from human feedback Y Dubois, CX Li, R Taori, T Zhang, I Gulrajani, J Ba, C Guestrin, PS Liang, ... Advances in Neural Information Processing Systems 36, 2024 | 279 | 2024 |
| Accuracy on the line: on the strong correlation between out-of-distribution and in-distribution generalization JP Miller, R Taori, A Raghunathan, S Sagawa, PW Koh, V Shankar, ... International conference on machine learning, 7721-7735, 2021 | 267 | 2021 |
| Targeted adversarial examples for black box audio systems R Taori, A Kamsetty, B Chu, N Vemuri 2019 IEEE security and privacy workshops (SPW), 15-20, 2019 | 213 | 2019 |
| Are we learning yet? a meta review of evaluation failures across machine learning T Liao, R Taori, ID Raji, L Schmidt Thirty-fifth Conference on Neural Information Processing Systems Datasets …, 2021 | 109 | 2021 |
| Is a caption worth a thousand images? a controlled study for representation learning S Santurkar, Y Dubois, R Taori, P Liang, T Hashimoto arXiv preprint arXiv:2207.07635, 2022 | 51* | 2022 |
| 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 | 50 | 2022 |
| Visit-bench: A benchmark for vision-language instruction following inspired by real-world use Y Bitton, H Bansal, J Hessel, R Shao, W Zhu, A Awadalla, J Gardner, ... arXiv preprint arXiv:2308.06595, 2023 | 38 | 2023 |
| Agent ai: Surveying the horizons of multimodal interaction Z Durante, Q Huang, N Wake, R Gong, JS Park, B Sarkar, R Taori, Y Noda, ... arXiv preprint arXiv:2401.03568, 2024 | 30 | 2024 |
| Data feedback loops: Model-driven amplification of dataset biases R Taori, T Hashimoto International Conference on Machine Learning, 33883-33920, 2023 | 25 | 2023 |
| Transposer: Universal texture synthesis using feature maps as transposed convolution filter G Liu, R Taori, TC Wang, Z Yu, S Liu, FA Reda, K Sapra, A Tao, ... arXiv preprint arXiv:2007.07243, 2020 | 22 | 2020 |
| Autoregressive models: What are they good for? M Dalal, AC Li, R Taori arXiv preprint arXiv:1910.07737, 2019 | 13 | 2019 |
| An interactive agent foundation model Z Durante, B Sarkar, R Gong, R Taori, Y Noda, P Tang, E Adeli, ... arXiv preprint arXiv:2402.05929, 2024 | 8 | 2024 |
| Position Paper: Agent AI Towards a Holistic Intelligence Q Huang, N Wake, B Sarkar, Z Durante, R Gong, R Taori, Y Noda, ... arXiv preprint arXiv:2403.00833, 2024 | 5 | 2024 |
| Benchmarking Multi-Domain Active Learning on Image Classification J Li, R Taori, TB Hashimoto arXiv preprint arXiv:2312.00364, 2023 | | 2023 |
Tatsunori HashimotoAssistant Professor, Stanford在 stanford.edu 的电子邮件经过验证
