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2020 – today
- 2024
[c35]Alexander Wan, Eric Wallace, Dan Klein:
What Evidence Do Language Models Find Convincing? ACL (1) 2024: 7468-7484- [c34]Arnav Gudibande, Eric Wallace, Charlie Snell, Xinyang Geng, Hao Liu, Pieter Abbeel, Sergey Levine, Dawn Song:
The False Promise of Imitating Proprietary Language Models. ICLR 2024 - [c33]Sewon Min, Suchin Gururangan, Eric Wallace, Weijia Shi, Hannaneh Hajishirzi, Noah A. Smith, Luke Zettlemoyer:
SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore. ICLR 2024 - [c32]Nicholas Carlini, Daniel Paleka, Krishnamurthy Dj Dvijotham, Thomas Steinke, Jonathan Hayase, A. Feder Cooper, Katherine Lee, Matthew Jagielski, Milad Nasr, Arthur Conmy, Eric Wallace, David Rolnick, Florian Tramèr:
Stealing part of a production language model. ICML 2024 - [c31]Danny Halawi, Alexander Wei, Eric Wallace, Tony Tong Wang, Nika Haghtalab, Jacob Steinhardt:
Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation. ICML 2024 - [c30]Edoardo Debenedetti, Giorgio Severi, Milad Nasr, Christopher A. Choquette-Choo, Matthew Jagielski, Eric Wallace, Nicholas Carlini, Florian Tramèr:
Privacy Side Channels in Machine Learning Systems. USENIX Security Symposium 2024 - [i38]Alexander Wan, Eric Wallace, Dan Klein:
What Evidence Do Language Models Find Convincing? CoRR abs/2402.11782 (2024) - [i37]Katie Kang, Eric Wallace, Claire J. Tomlin, Aviral Kumar, Sergey Levine:
Unfamiliar Finetuning Examples Control How Language Models Hallucinate. CoRR abs/2403.05612 (2024) - [i36]Nicholas Carlini, Daniel Paleka, Krishnamurthy (Dj) Dvijotham, Thomas Steinke, Jonathan Hayase, A. Feder Cooper, Katherine Lee, Matthew Jagielski, Milad Nasr, Arthur Conmy, Eric Wallace, David Rolnick, Florian Tramèr:
Stealing Part of a Production Language Model. CoRR abs/2403.06634 (2024) - [i35]Eric Wallace, Kai Xiao, Reimar Leike, Lilian Weng, Johannes Heidecke, Alex Beutel:
The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions. CoRR abs/2404.13208 (2024) - [i34]Danny Halawi, Alexander Wei, Eric Wallace, Tony T. Wang, Nika Haghtalab, Jacob Steinhardt:
Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation. CoRR abs/2406.20053 (2024) - 2023
- [c29]Daniel Fried, Armen Aghajanyan, Jessy Lin, Sida Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Scott Yih, Luke Zettlemoyer, Mike Lewis:
InCoder: A Generative Model for Code Infilling and Synthesis. ICLR 2023 - [c28]Matthew Jagielski, Om Thakkar, Florian Tramèr, Daphne Ippolito, Katherine Lee, Nicholas Carlini, Eric Wallace, Shuang Song, Abhradeep Guha Thakurta, Nicolas Papernot, Chiyuan Zhang:
Measuring Forgetting of Memorized Training Examples. ICLR 2023 - [c27]Nikhil Kandpal, Haikang Deng, Adam Roberts, Eric Wallace, Colin Raffel:
Large Language Models Struggle to Learn Long-Tail Knowledge. ICML 2023: 15696-15707 - [c26]Alexander Wan, Eric Wallace, Sheng Shen, Dan Klein:
Poisoning Language Models During Instruction Tuning. ICML 2023: 35413-35425 - [c25]Nicholas Carlini, Jamie Hayes, Milad Nasr, Matthew Jagielski, Vikash Sehwag, Florian Tramèr, Borja Balle, Daphne Ippolito, Eric Wallace:
Extracting Training Data from Diffusion Models. USENIX Security Symposium 2023: 5253-5270 - [i33]Nicholas Carlini, Jamie Hayes, Milad Nasr, Matthew Jagielski, Vikash Sehwag, Florian Tramèr, Borja Balle, Daphne Ippolito, Eric Wallace:
Extracting Training Data from Diffusion Models. CoRR abs/2301.13188 (2023) - [i32]Alexander Wan, Eric Wallace, Sheng Shen, Dan Klein:
Poisoning Language Models During Instruction Tuning. CoRR abs/2305.00944 (2023) - [i31]Arnav Gudibande, Eric Wallace, Charlie Snell, Xinyang Geng, Hao Liu, Pieter Abbeel, Sergey Levine, Dawn Song:
The False Promise of Imitating Proprietary LLMs. CoRR abs/2305.15717 (2023) - [i30]Sewon Min, Suchin Gururangan, Eric Wallace, Hannaneh Hajishirzi, Noah A. Smith, Luke Zettlemoyer:
SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore. CoRR abs/2308.04430 (2023) - [i29]Edoardo Debenedetti, Giorgio Severi, Nicholas Carlini, Christopher A. Choquette-Choo, Matthew Jagielski, Milad Nasr, Eric Wallace, Florian Tramèr:
Privacy Side Channels in Machine Learning Systems. CoRR abs/2309.05610 (2023) - [i28]Milad Nasr, Nicholas Carlini, Jonathan Hayase, Matthew Jagielski, A. Feder Cooper, Daphne Ippolito, Christopher A. Choquette-Choo, Eric Wallace, Florian Tramèr, Katherine Lee:
Scalable Extraction of Training Data from (Production) Language Models. CoRR abs/2311.17035 (2023) - 2022
- [c24]Eric Wallace, Adina Williams, Robin Jia
, Douwe Kiela:
Analyzing Dynamic Adversarial Training Data in the Limit. ACL (Findings) 2022: 202-217 - [c23]Robert L. Logan IV, Ivana Balazevic, Eric Wallace, Fabio Petroni, Sameer Singh, Sebastian Riedel:
Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models. ACL (Findings) 2022: 2824-2835 - [c22]Eric Wallace, Nicholas Tomlin, Albert Xu, Kevin Yang, Eshaan Pathak, Matthew L. Ginsberg, Dan Klein:
Automated Crossword Solving. ACL (1) 2022: 3073-3085 - [c21]Nikhil Kandpal, Eric Wallace, Colin Raffel:
Deduplicating Training Data Mitigates Privacy Risks in Language Models. ICML 2022: 10697-10707 - [i27]Nikhil Kandpal, Eric Wallace, Colin Raffel:
Deduplicating Training Data Mitigates Privacy Risks in Language Models. CoRR abs/2202.06539 (2022) - [i26]Daniel Fried, Armen Aghajanyan, Jessy Lin, Sida Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Wen-tau Yih, Luke Zettlemoyer, Mike Lewis:
InCoder: A Generative Model for Code Infilling and Synthesis. CoRR abs/2204.05999 (2022) - [i25]Eric Wallace, Nicholas Tomlin, Albert Xu, Kevin Yang, Eshaan Pathak, Matthew L. Ginsberg, Dan Klein:
Automated Crossword Solving. CoRR abs/2205.09665 (2022) - [i24]Matthew Jagielski, Om Thakkar, Florian Tramèr, Daphne Ippolito, Katherine Lee, Nicholas Carlini, Eric Wallace, Shuang Song, Abhradeep Thakurta, Nicolas Papernot, Chiyuan Zhang:
Measuring Forgetting of Memorized Training Examples. CoRR abs/2207.00099 (2022) - [i23]Nikhil Kandpal, Haikang Deng, Adam Roberts, Eric Wallace, Colin Raffel:
Large Language Models Struggle to Learn Long-Tail Knowledge. CoRR abs/2211.08411 (2022) - 2021
- [c20]Zihao Zhao, Eric Wallace, Shi Feng, Dan Klein, Sameer Singh:
Calibrate Before Use: Improving Few-shot Performance of Language Models. ICML 2021: 12697-12706 - [c19]Eric Wallace, Tony Z. Zhao, Shi Feng, Sameer Singh:
Concealed Data Poisoning Attacks on NLP Models. NAACL-HLT 2021: 139-150 - [c18]Albert Xu, Eshaan Pathak, Eric Wallace, Suchin Gururangan, Maarten Sap, Dan Klein:
Detoxifying Language Models Risks Marginalizing Minority Voices. NAACL-HLT 2021: 2390-2397 - [c17]Nicholas Carlini, Florian Tramèr, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom B. Brown, Dawn Song, Úlfar Erlingsson, Alina Oprea, Colin Raffel:
Extracting Training Data from Large Language Models. USENIX Security Symposium 2021: 2633-2650 - [i22]Tony Z. Zhao, Eric Wallace, Shi Feng, Dan Klein, Sameer Singh:
Calibrate Before Use: Improving Few-Shot Performance of Language Models. CoRR abs/2102.09690 (2021) - [i21]Albert Xu, Eshaan Pathak, Eric Wallace, Suchin Gururangan, Maarten Sap, Dan Klein:
Detoxifying Language Models Risks Marginalizing Minority Voices. CoRR abs/2104.06390 (2021) - [i20]Robert L. Logan IV, Ivana Balazevic, Eric Wallace, Fabio Petroni, Sameer Singh, Sebastian Riedel:
Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models. CoRR abs/2106.13353 (2021) - [i19]Eric Wallace, Adina Williams, Robin Jia, Douwe Kiela:
Analyzing Dynamic Adversarial Training Data in the Limit. CoRR abs/2110.08514 (2021) - 2020
- [c16]Dan Hendrycks, Xiaoyuan Liu, Eric Wallace, Adam Dziedzic, Rishabh Krishnan, Dawn Song:
Pretrained Transformers Improve Out-of-Distribution Robustness. ACL 2020: 2744-2751 - [c15]Eric Wallace, Matt Gardner, Sameer Singh:
Interpreting Predictions of NLP Models. EMNLP (Tutorial Abstracts) 2020: 20-23 - [c14]Junlin Wang, Jens Tuyls, Eric Wallace, Sameer Singh:
Gradient-based Analysis of NLP Models is Manipulable. EMNLP (Findings) 2020: 247-258 - [c13]Matt Gardner, Yoav Artzi, Victoria Basmova, Jonathan Berant, Ben Bogin, Sihao Chen, Pradeep Dasigi, Dheeru Dua, Yanai Elazar, Ananth Gottumukkala, Nitish Gupta, Hannaneh 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:
Evaluating Models' Local Decision Boundaries via Contrast Sets. EMNLP (Findings) 2020: 1307-1323 - [c12]Taylor Shin, Yasaman Razeghi, Robert L. Logan IV, Eric Wallace, Sameer Singh:
AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts. EMNLP (1) 2020: 4222-4235 - [c11]Eric Wallace, Mitchell Stern, Dawn Song:
Imitation Attacks and Defenses for Black-box Machine Translation Systems. EMNLP (1) 2020: 5531-5546 - [c10]Zhuohan Li, Eric Wallace, Sheng Shen, Kevin Lin, Kurt Keutzer, Dan Klein, Joey Gonzalez:
Train Big, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers. ICML 2020: 5958-5968 - [i18]Zhuohan Li, Eric Wallace, Sheng Shen, Kevin Lin, Kurt Keutzer, Dan Klein, Joseph E. Gonzalez:
Train Large, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers. CoRR abs/2002.11794 (2020) - [i17]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:
Evaluating NLP Models via Contrast Sets. CoRR abs/2004.02709 (2020) - [i16]Dan Hendrycks, Xiaoyuan Liu, Eric Wallace, Adam Dziedzic, Rishabh Krishnan, Dawn Song:
Pretrained Transformers Improve Out-of-Distribution Robustness. CoRR abs/2004.06100 (2020) - [i15]Eric Wallace, Mitchell Stern, Dawn Song:
Imitation Attacks and Defenses for Black-box Machine Translation Systems. CoRR abs/2004.15015 (2020) - [i14]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, M. Sadegh Riazi, Farinaz Koushanfar, Saransh Gupta, Tajana Simunic Rosing, Kamalika Chaudhuri, Hamid Nejatollahi, Nikil D. Dutt, Mohsen Imani, Kim Laine, Anuj Dubey, Aydin Aysu, Fateme Sadat Hosseini, Chengmo Yang, Eric Wallace, Pamela Norton:
Trustworthy AI Inference Systems: An Industry Research View. CoRR abs/2008.04449 (2020) - [i13]Junlin Wang, Jens Tuyls, Eric Wallace, Sameer Singh:
Gradient-based Analysis of NLP Models is Manipulable. CoRR abs/2010.05419 (2020) - [i12]Eric Wallace, Tony Z. Zhao, Shi Feng, Sameer Singh:
Customizing Triggers with Concealed Data Poisoning. CoRR abs/2010.12563 (2020) - [i11]Taylor Shin, Yasaman Razeghi, Robert L. Logan IV, Eric Wallace, Sameer Singh:
AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts. CoRR abs/2010.15980 (2020) - [i10]Nicholas Carlini, Florian Tramèr, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom B. Brown, Dawn Song, Úlfar Erlingsson, Alina Oprea, Colin Raffel:
Extracting Training Data from Large Language Models. CoRR abs/2012.07805 (2020)
2010 – 2019
- 2019
- [j1]Eric Wallace, Pedro Rodriguez, Shi Feng, Ikuya Yamada, Jordan L. Boyd-Graber:
Trick Me If You Can: Human-in-the-loop Generation of Adversarial Question Answering Examples. Trans. Assoc. Comput. Linguistics 7: 387-401 (2019) - [c9]Sewon Min, Eric Wallace, Sameer Singh, Matt Gardner, Hannaneh Hajishirzi, Luke Zettlemoyer:
Compositional Questions Do Not Necessitate Multi-hop Reasoning. ACL (1) 2019: 4249-4257 - [c8]Shi Feng, Eric Wallace, Jordan L. Boyd-Graber:
Misleading Failures of Partial-input Baselines. ACL (1) 2019: 5533-5538 - [c7]Eric Wallace, Jens Tuyls, Junlin Wang, Sanjay Subramanian, Matt Gardner, Sameer Singh:
AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models. EMNLP/IJCNLP (3) 2019: 7-12 - [c6]Eric Wallace, Shi Feng, Nikhil Kandpal, Matt Gardner, Sameer Singh:
Universal Adversarial Triggers for Attacking and Analyzing NLP. EMNLP/IJCNLP (1) 2019: 2153-2162 - [c5]Eric Wallace, Yizhong Wang, Sujian Li, Sameer Singh, Matt Gardner:
Do NLP Models Know Numbers? Probing Numeracy in Embeddings. EMNLP/IJCNLP (1) 2019: 5306-5314 - [c4]Sahil Singla, Eric Wallace, Shi Feng, Soheil Feizi:
Understanding Impacts of High-Order Loss Approximations and Features in Deep Learning Interpretation. ICML 2019: 5848-5856 - [i9]Sahil Singla, Eric Wallace, Shi Feng, Soheil Feizi:
Understanding Impacts of High-Order Loss Approximations and Features in Deep Learning Interpretation. CoRR abs/1902.00407 (2019) - [i8]Shi Feng, Eric Wallace, Jordan L. Boyd-Graber:
Misleading Failures of Partial-input Baselines. CoRR abs/1905.05778 (2019) - [i7]Sewon Min, Eric Wallace, Sameer Singh, Matt Gardner, Hannaneh Hajishirzi, Luke Zettlemoyer:
Compositional Questions Do Not Necessitate Multi-hop Reasoning. CoRR abs/1906.02900 (2019) - [i6]Eric Wallace, Shi Feng, Nikhil Kandpal, Matt Gardner, Sameer Singh:
Universal Adversarial Triggers for NLP. CoRR abs/1908.07125 (2019) - [i5]Eric Wallace, Yizhong Wang, Sujian Li, Sameer Singh, Matt Gardner:
Do NLP Models Know Numbers? Probing Numeracy in Embeddings. CoRR abs/1909.07940 (2019) - [i4]Eric Wallace, Jens Tuyls, Junlin Wang, Sanjay Subramanian, Matt Gardner, Sameer Singh:
AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models. CoRR abs/1909.09251 (2019) - 2018
- [c3]Eric Wallace, Jordan L. Boyd-Graber:
Trick Me If You Can: Adversarial Writing of Trivia Challenge Questions. ACL (3) 2018: 127-133 - [c2]Eric Wallace, Shi Feng, Jordan L. Boyd-Graber:
Interpreting Neural Networks with Nearest Neighbors. BlackboxNLP@EMNLP 2018: 136-144 - [c1]Shi Feng, Eric Wallace, Alvin Grissom II, Mohit Iyyer, Pedro Rodriguez, Jordan L. Boyd-Graber:
Pathologies of Neural Models Make Interpretation Difficult. EMNLP 2018: 3719-3728 - [i3]Shi Feng, Eric Wallace, Mohit Iyyer, Pedro Rodriguez, Alvin Grissom II, Jordan L. Boyd-Graber:
Right Answer for the Wrong Reason: Discovery and Mitigation. CoRR abs/1804.07781 (2018) - [i2]Eric Wallace, Pedro Rodriguez, Shi Feng, Jordan L. Boyd-Graber:
Trick Me If You Can: Adversarial Writing of Trivia Challenge Questions. CoRR abs/1809.02701 (2018) - [i1]Eric Wallace, Shi Feng, Jordan L. Boyd-Graber:
Interpreting Neural Networks With Nearest Neighbors. CoRR abs/1809.02847 (2018)
Coauthor Index
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