Rohan Taori
Rohan Taori
CS PhD @ Stanford
Verified email at - Homepage
Cited by
Cited by
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
Stanford alpaca: An instruction-following llama model
R Taori, I Gulrajani, T Zhang, Y Dubois, X Li, C Guestrin, P Liang, ...
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
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
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
Openclip, July 2021
G Ilharco, M Wortsman, R Wightman, C Gordon, N Carlini, R Taori, ...
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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
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
Alpacafarm: A simulation framework for methods that learn from human feedback
Y Dubois, X Li, R Taori, T Zhang, I Gulrajani, J Ba, C Guestrin, P Liang, ...
arXiv preprint arXiv:2305.14387, 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
Alpacaeval: An automatic evaluator of instruction-following models
X Li, T Zhang, Y Dubois, R Taori, I Gulrajani, C Guestrin, P Liang, ...
Data feedback loops: Model-driven amplification of dataset biases
R Taori, T Hashimoto
International Conference on Machine Learning, 33883-33920, 2023
Autoregressive models: What are they good for?
M Dalal, AC Li, R Taori
arXiv preprint arXiv:1910.07737, 2019
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
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