Shi Feng
Shi Feng
Dirección de correo verificada de cs.umd.edu - Página principal
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Pathologies of Neural Models Make Interpretations Difficult
S Feng, E Wallace, A Grissom II, M Iyyer, P Rodriguez, J Boyd-Graber
EMNLP, 2018
782018
Universal adversarial triggers for attacking and analyzing NLP
E Wallace, S Feng, N Kandpal, M Gardner, S Singh
arXiv preprint arXiv:1908.07125, 2019
682019
Improving Attention Modeling with Implicit Distortion and Fertility for Machine Translation
S Feng, S Liu, N Yang, M Li, M Zhou, KQ Zhu
COLING, 2016
54*2016
What can AI do for me? evaluating machine learning interpretations in cooperative play
S Feng, J Boyd-Graber
Proceedings of the 24th International Conference on Intelligent User …, 2019
292019
Knowledge-based semantic embedding for machine translation
C Shi, S Liu, S Ren, S Feng, M Li, M Zhou, X Sun, H Wang
Proceedings of the 54th Annual Meeting of the Association for Computational …, 2016
292016
Trick me if you can: Human-in-the-loop generation of adversarial examples for question answering
E Wallace, P Rodriguez, S Feng, I Yamada, J Boyd-Graber
Transactions of the Association for Computational Linguistics 7, 387-401, 2019
23*2019
Understanding impacts of high-order loss approximations and features in deep learning interpretation
S Singla, E Wallace, S Feng, S Feizi
arXiv preprint arXiv:1902.00407, 2019
142019
Interpreting neural networks with nearest neighbors
E Wallace, S Feng, J Boyd-Graber
arXiv preprint arXiv:1809.02847, 2018
132018
Misleading failures of partial-input baselines
S Feng, E Wallace, J Boyd-Graber
arXiv preprint arXiv:1905.05778, 2019
102019
Human-Computer Question Answering: The Case for Quizbowl
J Boyd-Graber, S Feng, P Rodriguez
The NIPS'17 Competition: Building Intelligent Systems, 169-180, 2018
62018
The umd neural machine translation systems at wmt17 bandit learning task
A Sharaf, S Feng, K Nguyen, K Brantley, H Daumé III
arXiv preprint arXiv:1708.01318, 2017
32017
Quizbowl: The case for incremental question answering
P Rodriguez, S Feng, M Iyyer, H He, J Boyd-Graber
arXiv preprint arXiv:1904.04792, 2019
22019
How pre-trained word representations capture commonsense physical comparisons
P Goel, S Feng, J Boyd-Graber
Proceedings of the First Workshop on Commonsense Inference in Natural …, 2019
12019
Introduction to NIPS 2017 Competition Track
S Escalera, M Weimer, M Burtsev, V Malykh, V Logacheva, R Lowe, ...
The NIPS'17 Competition: Building Intelligent Systems, 1-23, 2018
12018
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