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AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts

Nov 07, 2020
Taylor Shin, Yasaman Razeghi, Robert L. Logan IV, Eric Wallace, Sameer Singh

* v2: Fixed error in Figure 2 

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Customizing Triggers with Concealed Data Poisoning

Oct 23, 2020
Eric Wallace, Tony Z. Zhao, Shi Feng, Sameer Singh


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Gradient-based Analysis of NLP Models is Manipulable

Oct 12, 2020
Junlin Wang, Jens Tuyls, Eric Wallace, Sameer Singh


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Trustworthy AI Inference Systems: An Industry Research View

Aug 10, 2020
Rosario Cammarota, Matthias Schunter, Anand Rajan, Fabian Boemer, Ágnes Kiss, Amos Treiber, Christian Weinert, Thomas Schneider, Emmanuel Stapf, Ahmad-Reza Sadeghi, Daniel Demmler, Huili Chen, Siam Umar Hussain, Sadegh Riazi, Farinaz Koushanfar, Saransh Gupta, Tajan Simunic Rosing, Kamalika Chaudhuri, Hamid Nejatollahi, Nikil Dutt, Mohsen Imani, Kim Laine, Anuj Dubey, Aydin Aysu, Fateme Sadat Hosseini, Chengmo Yang, Eric Wallace, Pamela Norton


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Imitation Attacks and Defenses for Black-box Machine Translation Systems

Apr 30, 2020
Eric Wallace, Mitchell Stern, Dawn Song


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Pretrained Transformers Improve Out-of-Distribution Robustness

Apr 16, 2020
Dan Hendrycks, Xiaoyuan Liu, Eric Wallace, Adam Dziedzic, Rishabh Krishnan, Dawn Song

* ACL 2020 

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Evaluating NLP Models via Contrast Sets

Apr 06, 2020
Matt Gardner, Yoav Artzi, Victoria Basmova, Jonathan Berant, Ben Bogin, Sihao Chen, Pradeep Dasigi, Dheeru Dua, Yanai Elazar, Ananth Gottumukkala, Nitish Gupta, Hanna Hajishirzi, Gabriel Ilharco, Daniel Khashabi, Kevin Lin, Jiangming Liu, Nelson F. Liu, Phoebe Mulcaire, Qiang Ning, Sameer Singh, Noah A. Smith, Sanjay Subramanian, Reut Tsarfaty, Eric Wallace, Ally Zhang, Ben Zhou


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Train Large, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers

Feb 26, 2020
Zhuohan Li, Eric Wallace, Sheng Shen, Kevin Lin, Kurt Keutzer, Dan Klein, Joseph E. Gonzalez


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AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models

Sep 19, 2019
Eric Wallace, Jens Tuyls, Junlin Wang, Sanjay Subramanian, Matt Gardner, Sameer Singh

* EMNLP 2019 Demo 

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Do NLP Models Know Numbers? Probing Numeracy in Embeddings

Sep 18, 2019
Eric Wallace, Yizhong Wang, Sujian Li, Sameer Singh, Matt Gardner

* EMNLP 2019 

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Universal Adversarial Triggers for Attacking and Analyzing NLP

Aug 29, 2019
Eric Wallace, Shi Feng, Nikhil Kandpal, Matt Gardner, Sameer Singh

* EMNLP 2019 

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Universal Adversarial Triggers for NLP

Aug 20, 2019
Eric Wallace, Shi Feng, Nikhil Kandpal, Matt Gardner, Sameer Singh

* EMNLP 2019 

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Compositional Questions Do Not Necessitate Multi-hop Reasoning

Jun 07, 2019
Sewon Min, Eric Wallace, Sameer Singh, Matt Gardner, Hannaneh Hajishirzi, Luke Zettlemoyer

* Published as a conference paper at ACL 2019 (short). Code available at https://github.com/shmsw25/single-hop-rc 

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Misleading Failures of Partial-input Baselines

May 14, 2019
Shi Feng, Eric Wallace, Jordan Boyd-Graber

* ACL 2019 

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Understanding Impacts of High-Order Loss Approximations and Features in Deep Learning Interpretation

Feb 01, 2019
Sahil Singla, Eric Wallace, Shi Feng, Soheil Feizi


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Interpreting Neural Networks With Nearest Neighbors

Sep 08, 2018
Eric Wallace, Shi Feng, Jordan Boyd-Graber

* EMNLP 2018 BlackboxNLP 

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Trick Me If You Can: Adversarial Writing of Trivia Challenge Questions

Sep 07, 2018
Eric Wallace, Pedro Rodriguez, Shi Feng, Jordan Boyd-Graber


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Pathologies of Neural Models Make Interpretations Difficult

Aug 28, 2018
Shi Feng, Eric Wallace, Alvin Grissom II, Mohit Iyyer, Pedro Rodriguez, Jordan Boyd-Graber

* EMNLP 2018 camera ready 

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