Shiori Sagawa
Shiori Sagawa
PhD Student, Stanford University
Verified email at
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
Distributionally robust neural networks for group shifts: On the importance of regularization for worst-case generalization
S Sagawa*, PW Koh*, TB Hashimoto, P Liang
International Conference on Learning Representations, 2019
WILDS: A benchmark of in-the-wild distribution shifts
PW Koh*, S Sagawa*, H Marklund, SM Xie, M Zhang, A Balsubramani, ...
International Conference on Machine Learning, 5637-5664, 2021
Just Train Twice: Improving Group Robustness without Training Group Information
EZ Liu, B Haghgoo, AS Chen, A Raghunathan, PW Koh, S Sagawa, ...
International Conference on Machine Learning, 6781-6792, 2021
An investigation of why overparameterization exacerbates spurious correlations
S Sagawa*, A Raghunathan*, PW Koh*, P Liang
International Conference on Machine Learning, 8346-8356, 2020
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
Openflamingo: An open-source framework for training large autoregressive vision-language models
A Awadalla, I Gao, J Gardner, J Hessel, Y Hanafy, W Zhu, K Marathe, ...
arXiv preprint arXiv:2308.01390, 2023
Distributionally robust language modeling
Y Oren*, S Sagawa*, TB Hashimoto*, P Liang
arXiv preprint arXiv:1909.02060, 2019
Extending the WILDS Benchmark for Unsupervised Adaptation
S Sagawa*, PW Koh*, T Lee*, I Gao*, SM Xie, K Shen, A Kumar, W Hu, ...
International Conference on Learning Representations, 2022
The architecture of EGFR’s basal complexes reveals autoinhibition mechanisms in dimers and oligomers
LC Zanetti-Domingues, D Korovesis, SR Needham, CJ Tynan, S Sagawa, ...
Nature communications 9 (1), 4325, 2018
Structural mechanism for Bruton’s tyrosine kinase activation at the cell membrane
Q Wang, Y Pechersky, S Sagawa, AC Pan, DE Shaw
Proceedings of the National Academy of Sciences 116 (19), 9390-9399, 2019
Selective classification can magnify disparities across groups
E Jones, S Sagawa, PW Koh, A Kumar, P Liang
International Conference on Learning Representations, 2020
Multi-resolution weak supervision for sequential data
P Varma, F Sala, S Sagawa, J Fries, D Fu, S Khattar, A Ramamoorthy, ...
Advances in Neural Information Processing Systems 32, 2019
Genotype specification language
EH Wilson*, S Sagawa*, JW Weis*, MG Schubert*, M Bissell, ...
ACS synthetic biology 5 (6), 471-478, 2016
Out-of-Domain Robustness via Targeted Augmentations
I Gao*, S Sagawa*, PW Koh, T Hashimoto, P Liang
International Conference on Machine Learning, 2023
How does a small molecule bind at a cryptic binding site?
Y Shan, VP Mysore, AE Leffler, ET Kim, S Sagawa, DE Shaw
PLoS computational biology 18 (3), e1009817, 2022
Modulating the frequency and bias of stochastic switching to control phenotypic variation
M Hung, E Chang, R Hussein, K Frazier, JE Shin, S Sagawa, HN Lim
Nature Communications 5 (1), 4574, 2014
Paradoxical suppression of small RNA activity at high Hfq concentrations due to random-order binding
S Sagawa*, JE Shin*, R Hussein, HN Lim
Nucleic acids research 43 (17), 8502-8515, 2015
Validating regulatory predictions from diverse bacteria with mutant fitness data
S Sagawa, MN Price, AM Deutschbauer, AP Arkin
PloS one 12 (5), e0178258, 2017
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