| Discovery of directional and nondirectional pioneer transcription factors by modeling DNase profile magnitude and shape RI Sherwood, T Hashimoto, CW O'donnell, S Lewis, AA Barkal, ... Nature biotechnology 32 (2), 171-178, 2014 | 424 | 2014 |
| Distributionally robust neural networks for group shifts: On the importance of regularization for worst-case generalization S Sagawa, PW Koh, TB Hashimoto, P Liang arXiv preprint arXiv:1911.08731, 2019 | 386 | 2019 |
| Fairness without demographics in repeated loss minimization T Hashimoto, M Srivastava, H Namkoong, P Liang International Conference on Machine Learning, 1929-1938, 2018 | 291 | 2018 |
| Generating sentences by editing prototypes K Guu, TB Hashimoto, Y Oren, P Liang Transactions of the Association for Computational Linguistics 6, 437-450, 2018 | 258 | 2018 |
| 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 | 247 | 2021 |
| Unifying human and statistical evaluation for natural language generation TB Hashimoto, H Zhang, P Liang arXiv preprint arXiv:1904.02792, 2019 | 142 | 2019 |
| A retrieve-and-edit framework for predicting structured outputs TB Hashimoto, K Guu, Y Oren, PS Liang Advances in Neural Information Processing Systems 31, 2018 | 98 | 2018 |
| Long-term persistence and development of induced pancreatic beta cells generated by lineage conversion of acinar cells GWQZ Weida Li, Claudia Cavelti-Weder, Yinying Zhang, Kendell Clement, Scott ... Nature Biotechnology 32, 1223-1230, 2014 | 92 | 2014 |
| Distributionally robust language modeling Y Oren, S Sagawa, TB Hashimoto, P Liang arXiv preprint arXiv:1909.02060, 2019 | 81 | 2019 |
| Word embeddings as metric recovery in semantic spaces TB Hashimoto, D Alvarez-Melis, TS Jaakkola Transactions of the Association for Computational Linguistics 4, 273-286, 2016 | 80 | 2016 |
| Cloning-free CRISPR M Arbab, S Srinivasan, T Hashimoto, N Geijsen, RI Sherwood Stem cell reports 5 (5), 908-917, 2015 | 52 | 2015 |
| The gem benchmark: Natural language generation, its evaluation and metrics S Gehrmann, T Adewumi, K Aggarwal, PS Ammanamanchi, ... arXiv preprint arXiv:2102.01672, 2021 | 51 | 2021 |
| Learning population-level diffusions with generative RNNs T Hashimoto, D Gifford, T Jaakkola International Conference on Machine Learning, 2417-2426, 2016 | 45 | 2016 |
| Distributionally robust losses against mixture covariate shifts JC Duchi, T Hashimoto, H Namkoong Under review 2, 2019 | 42 | 2019 |
| Cas9 functionally opens chromatin AA Barkal, S Srinivasan, T Hashimoto, DK Gifford, RI Sherwood PLoS One 11 (3), e0152683, 2016 | 42 | 2016 |
| GERV: a statistical method for generative evaluation of regulatory variants for transcription factor binding H Zeng, T Hashimoto, DD Kang, DK Gifford Bioinformatics 32 (4), 490-496, 2016 | 42 | 2016 |
| Finding the rules for successful drug optimisation I Yusof, F Shah, T Hashimoto, MD Segall, N Greene Drug Discovery Today 19 (5), 680-687, 2014 | 42 | 2014 |
| Robustness to spurious correlations via human annotations M Srivastava, T Hashimoto, P Liang International Conference on Machine Learning, 9109-9119, 2020 | 35 | 2020 |
| Improved natural language generation via loss truncation D Kang, T Hashimoto arXiv preprint arXiv:2004.14589, 2020 | 31 | 2020 |
| Distributionally robust losses for latent covariate mixtures J Duchi, T Hashimoto, H Namkoong arXiv preprint arXiv:2007.13982, 2020 | 30 | 2020 |
Percy LiangAssociate Professor of Computer Science, Stanford UniversityE-mail confirmado em cs.stanford.edu
