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Universal Adversarial Triggers for Attacking and Analyzing NLP
- Eric Wallace, Shi Feng, Nikhil Kandpal, Matt Gardner, Sameer Singh
- Computer ScienceEMNLP
- 20 August 2019
Adversarial examples highlight model vulnerabilities and are useful for evaluation and interpretation. We define universal adversarial triggers: input-agnostic sequences of tokens that trigger a…
Calibrate Before Use: Improving Few-Shot Performance of Language Models
- Tony Zhao, Eric Wallace, Shi Feng, D. Klein, Sameer Singh
- Computer ScienceICML
- 19 February 2021
TLDR
Compositional Questions Do Not Necessitate Multi-hop Reasoning
- Sewon Min, Eric Wallace, Sameer Singh, Matt Gardner, Hannaneh Hajishirzi, Luke Zettlemoyer
- Computer ScienceACL
- 7 June 2019
TLDR
Pathologies of Neural Models Make Interpretations Difficult
- Shi Feng, Eric Wallace, Alvin Grissom II, Mohit Iyyer, Pedro Rodriguez, Jordan L. Boyd-Graber
- Computer ScienceEMNLP
- 20 April 2018
TLDR
Pretrained Transformers Improve Out-of-Distribution Robustness
- Dan Hendrycks, Xiaoyuan Liu, Eric Wallace, Adam Dziedzic, R. Krishnan, D. Song
- Computer ScienceACL
- 13 April 2020
TLDR
Extracting Training Data from Large Language Models
- Nicholas Carlini, Florian Tramèr, Colin Raffel
- Computer ScienceUSENIX Security Symposium
- 14 December 2020
TLDR
Do NLP Models Know Numbers? Probing Numeracy in Embeddings
- Eric Wallace, Yizhong Wang, Sujian Li, Sameer Singh, Matt Gardner
- Computer ScienceEMNLP
- 17 September 2019
TLDR
AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models
- Eric Wallace, Jens Tuyls, Junlin Wang, Sanjay Subramanian, Matt Gardner, Sameer Singh
- Computer ScienceEMNLP
- 1 September 2019
TLDR
Eliciting Knowledge from Language Models Using Automatically Generated Prompts
- Taylor Shin, Yasaman Razeghi, Robert L Logan IV, Eric Wallace, Sameer Singh
- Computer ScienceEMNLP
- 29 October 2020
The remarkable success of pretrained language models has motivated the study of what kinds of knowledge these models learn during pretraining. Reformulating tasks as fill-in-the-blanks problems…
Evaluating Models’ Local Decision Boundaries via Contrast Sets
- Matt Gardner, Yoav Artzi, Ben Zhou
- Computer ScienceFINDINGS
- 6 April 2020
TLDR
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