| A deep learning mammography-based model for improved breast cancer risk prediction A Yala, C Lehman, T Schuster, T Portnoi, R Barzilay Radiology 292 (1), 60-66, 2019 | 306 | 2019 |
| Cross-Lingual Alignment of Contextual Word Embeddings, with Applications to Zero-shot Dependency Parsing T Schuster, O Ram, R Barzilay, A Globerson NAACL 2019, 2019 | 154 | 2019 |
| Mammographic breast density assessment using deep learning: clinical implementation CD Lehman, A Yala, T Schuster, B Dontchos, M Bahl, K Swanson, ... Radiology 290 (1), 52-58, 2019 | 152 | 2019 |
| Towards debiasing fact verification models T Schuster, DJ Shah, YJS Yeo, D Filizzola, E Santus, R Barzilay EMNLP 2019, 2019 | 100 | 2019 |
| A deep learning model to triage screening mammograms: a simulation study A Yala, T Schuster, R Miles, R Barzilay, C Lehman Radiology 293 (1), 38-46, 2019 | 99 | 2019 |
| The Limitations of Stylometry for Detecting Machine-Generated Fake News T Schuster, R Schuster, DJ Shah, R Barzilay Computational Linguistics, 2019 | 68* | 2019 |
| Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence T Schuster, A Fisch, R Barzilay NAACL 2021, 2021 | 38 | 2021 |
| ExT5: Towards Extreme Multi-Task Scaling for Transfer Learning V Aribandi, Y Tay, T Schuster, J Rao, HS Zheng, SV Mehta, H Zhuang, ... ICLR 2022, 2021 | 29 | 2021 |
| Humpty Dumpty: Controlling Word Meanings via Corpus Poisoning R Schuster, T Schuster, Y Meri, V Shmatikov IEEE S&P 2020, 2020 | 24 | 2020 |
| Automatic Fact-guided Sentence Modification DJ Shah, T Schuster, R Barzilay AAAI 2020, 2019 | 21 | 2019 |
| Efficient Conformal Prediction via Cascaded Inference with Expanded Admission A Fisch, T Schuster, T Jaakkola, R Barzilay ICLR 2021, 2021 | 17 | 2021 |
| Optical Flow Requires Multiple Strategies (but only one network) T Schuster, L Wolf, D Gadot CVPR 2017, 2016 | 16 | 2016 |
| Transformer memory as a differentiable search index Y Tay, VQ Tran, M Dehghani, J Ni, D Bahri, H Mehta, Z Qin, K Hui, Z Zhao, ... arXiv preprint arXiv:2202.06991, 2022 | 15 | 2022 |
| Deep learning model to assess cancer risk on the basis of a breast MR image alone T Portnoi, A Yala, T Schuster, R Barzilay, B Dontchos, L Lamb, C Lehman American Journal of Roentgenology 213 (1), 227-233, 2019 | 15 | 2019 |
| Few-shot Conformal Prediction with Auxiliary Tasks A Fisch, T Schuster, T Jaakkola, R Barzilay ICML 2021, 2021 | 12 | 2021 |
| Consistent Accelerated Inference via Confident Adaptive Transformers T Schuster, A Fisch, T Jaakkola, R Barzilay EMNLP 2021, 2021 | 10 | 2021 |
| Distilling the evidence to augment fact verification models B Portelli, J Zhao, T Schuster, G Serra, E Santus Proceedings of the Third Workshop on Fact Extraction and VERification (FEVER …, 2020 | 9 | 2020 |
| Programming Puzzles T Schuster, A Kalyan, O Polozov, AT Kalai NeurIPS 2021, 2021 | 6 | 2021 |
| Unifying Language Learning Paradigms Y Tay, M Dehghani, VQ Tran, X Garcia, D Bahri, T Schuster, HS Zheng, ... arXiv preprint arXiv:2205.05131, 2022 | 4 | 2022 |
| Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ... arXiv preprint arXiv:2206.04615, 2022 | 3 | 2022 |
Adam YalaUC Berkeley and UCSFVerified email at berkeley.edu
