עקוב אחר
Shi Feng
Shi Feng
The George Washington University
כתובת אימייל מאומתת בדומיין gwu.edu - דף הבית
כותרת
צוטט על ידי
צוטט על ידי
שנה
Calibrate before use: Improving few-shot performance of language models‏
Z Zhao, E Wallace, S Feng, D Klein, S Singh‏
ICML 2021, 2021‏
13252021
Universal adversarial triggers for attacking and analyzing NLP‏
E Wallace, S Feng, N Kandpal, M Gardner, S Singh‏
EMNLP 2019, 2019‏
9402019
Pathologies of Neural Models Make Interpretations Difficult‏
S Feng, E Wallace, A Grissom II, M Iyyer, P Rodriguez, J Boyd-Graber‏
EMNLP 2018, 2018‏
3812018
Concealed data poisoning attacks on NLP models‏
E Wallace, TZ Zhao, S Feng, S Singh‏
NAACL 2021, 2020‏
1942020
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
TACL 2019, 2019‏
1902019
Active example selection for in-context learning‏
Y Zhang, S Feng, C Tan‏
EMNLP 2022, 2022‏
1662022
What can AI do for me? evaluating machine learning interpretations in cooperative play‏
S Feng, J Boyd-Graber‏
IUI 2019, 2019‏
1532019
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
1022016
LLM evaluators recognize and favor their own generations‏
A Panickssery, SR Bowman, S Feng‏
NeurIPS 2024, 2024‏
862024
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
75*2016
Interpreting neural networks with nearest neighbors‏
E Wallace, S Feng, J Boyd-Graber‏
BlackboxNLP @ EMNLP 2018, 2018‏
612018
Understanding impacts of high-order loss approximations and features in deep learning interpretation‏
S Singla, E Wallace, S Feng, S Feizi‏
ICML 2019, 2019‏
602019
Misleading failures of partial-input baselines‏
S Feng, E Wallace, J Boyd-Graber‏
ACL 2019, 2019‏
422019
Quizbowl: The case for incremental question answering‏
P Rodriguez, S Feng, M Iyyer, H He, J Boyd-Graber‏
arXiv preprint arXiv:1904.04792, 2019‏
422019
Machine explanations and human understanding‏
C Chen, S Feng, A Sharma, C Tan‏
TMLR 2023, 2022‏
342022
Measuring inductive biases of in-context learning with underspecified demonstrations‏
C Si, D Friedman, N Joshi, S Feng, D Chen, H He‏
ACL 2023, 2023‏
312023
Large Language Models Help Humans Verify Truthfulness--Except When They Are Convincingly Wrong‏
C Si, N Goyal, ST Wu, C Zhao, S Feng, H Daumé III, J Boyd-Graber‏
NAACL 2024, 2023‏
272023
Human-centered evaluation of explanations‏
J Boyd-Graber, S Carton, S Feng, QV Liao, T Lombrozo, A Smith-Renner, ...‏
NAACL 2022 Tutorial, 2022‏
232022
Language models learn to mislead humans via rlhf‏
J Wen, R Zhong, A Khan, E Perez, J Steinhardt, M Huang, SR Bowman, ...‏
arXiv preprint arXiv:2409.12822, 2024‏
152024
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
132018
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מאמרים 1–20