Tal Schuster
Tal Schuster
Verified email at csail.mit.edu - Homepage
Cited by
Cited by
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
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
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
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
Towards debiasing fact verification models
T Schuster, DJ Shah, YJS Yeo, D Filizzola, E Santus, R Barzilay
EMNLP 2019, 2019
The Limitations of Stylometry for Detecting Machine-Generated Fake News
T Schuster, R Schuster, DJ Shah, R Barzilay
Computational Linguistics, 2019
Optical Flow Requires Multiple Strategies (but only one network)
T Schuster, L Wolf, D Gadot
CVPR 2017, 2016
Humpty Dumpty: Controlling Word Meanings via Corpus Poisoning
R Schuster, T Schuster, Y Meri, V Shmatikov
IEEE S&P 2020, 2020
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
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
Automatic Fact-guided Sentence Modification
DJ Shah, T Schuster, R Barzilay
AAAI 2020, 2019
Exploiting Rules to Enhance Machine Learning in Extracting Information From Multi-Institutional Prostate Pathology Reports
E Santus, T Schuster, AM Tahmasebi, C Li, A Yala, CR Lanahan, ...
JCO Clinical Cancer Informatics 4, 865-874, 2020
Relaxed Conformal Prediction Cascades for Efficient Inference Over Many Labels
A Fisch, T Schuster, T Jaakkola, R Barzilay
arXiv preprint arXiv:2007.03114, 2020
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