Eric Wallace
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
33
Venues
5
Active years
2018–2025
Best venue rank
A*
Where they publish
Papers
33 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | NAACL | Unfamiliar Finetuning Examples Control How Language Models Hallucinate. | Katie Kang, Eric Wallace, Claire J. Tomlin, Aviral Kumar, Sergey Levine |
| 2024 | ACL | What Evidence Do Language Models Find Convincing? | Alexander Wan, Eric Wallace, Dan Klein |
| 2024 | ICLR | The False Promise of Imitating Proprietary Language Models. | Arnav Gudibande, Eric Wallace, Charlie Snell, Xinyang Geng, Hao Liu, Pieter Abbeel, Sergey Levine, Dawn Song |
| 2024 | ICLR | SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore. | Sewon Min, Suchin Gururangan, Eric Wallace, Weijia Shi, Hannaneh Hajishirzi, Noah A. Smith, Luke Zettlemoyer |
| 2024 | ICML | Stealing part of a production language model. | 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 Tramr |
| 2024 | ICML | Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation. | Danny Halawi, Alexander Wei, Eric Wallace, Tony Tong Wang, Nika Haghtalab, Jacob Steinhardt |
| 2023 | ICLR | InCoder: A Generative Model for Code Infilling and Synthesis. | Daniel Fried, Armen Aghajanyan, Jessy Lin, Sida Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Scott Yih, Luke Zettlemoyer, Mike Lewis |
| 2023 | ICLR | Measuring Forgetting of Memorized Training Examples. | Matthew Jagielski, Om Thakkar, Florian Tramr, Daphne Ippolito, Katherine Lee, Nicholas Carlini, Eric Wallace, Shuang Song, Abhradeep Guha Thakurta, Nicolas Papernot, Chiyuan Zhang |
| 2023 | ICML | Large Language Models Struggle to Learn Long-Tail Knowledge. | Nikhil Kandpal, Haikang Deng, Adam Roberts, Eric Wallace, Colin Raffel |
| 2023 | ICML | Poisoning Language Models During Instruction Tuning. | Alexander Wan, Eric Wallace, Sheng Shen, Dan Klein |
| 2022 | ACL | Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models. | Robert L. Logan IV, Ivana Balazevic, Eric Wallace, Fabio Petroni, Sameer Singh, Sebastian Riedel |
| 2022 | ACL | Automated Crossword Solving. | Eric Wallace, Nicholas Tomlin, Albert Xu, Kevin Yang, Eshaan Pathak, Matthew L. Ginsberg, Dan Klein |
| 2022 | ACL | Analyzing Dynamic Adversarial Training Data in the Limit. | Eric Wallace, Adina Williams, Robin Jia, Douwe Kiela |
| 2022 | ICML | Deduplicating Training Data Mitigates Privacy Risks in Language Models. | Nikhil Kandpal, Eric Wallace, Colin Raffel |
| 2021 | ICML | Calibrate Before Use: Improving Few-shot Performance of Language Models. | Zihao Zhao, Eric Wallace, Shi Feng, Dan Klein, Sameer Singh |
| 2021 | NAACL | Concealed Data Poisoning Attacks on NLP Models. | Eric Wallace, Tony Z. Zhao, Shi Feng, Sameer Singh |
| 2021 | NAACL | Detoxifying Language Models Risks Marginalizing Minority Voices. | Albert Xu, Eshaan Pathak, Eric Wallace, Suchin Gururangan, Maarten Sap, Dan Klein |
| 2020 | ACL | Pretrained Transformers Improve Out-of-Distribution Robustness. | Dan Hendrycks, Xiaoyuan Liu, Eric Wallace, Adam Dziedzic, Rishabh Krishnan, Dawn Song |
| 2020 | EMNLP | Evaluating Models' Local Decision Boundaries via Contrast Sets. | 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 |
| 2020 | EMNLP | AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts. | Taylor Shin, Yasaman Razeghi, Robert L. Logan IV, Eric Wallace, Sameer Singh |
| 2020 | EMNLP | Interpreting Predictions of NLP Models. | Eric Wallace, Matt Gardner, Sameer Singh |
| 2020 | EMNLP | Imitation Attacks and Defenses for Black-box Machine Translation Systems. | Eric Wallace, Mitchell Stern, Dawn Song |
| 2020 | EMNLP | Gradient-based Analysis of NLP Models is Manipulable. | Junlin Wang, Jens Tuyls, Eric Wallace, Sameer Singh |
| 2020 | ICML | Train Big, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers. | Zhuohan Li, Eric Wallace, Sheng Shen, Kevin Lin, Kurt Keutzer, Dan Klein, Joey Gonzalez |
| 2019 | ACL | Misleading Failures of Partial-input Baselines. | Shi Feng, Eric Wallace, Jordan L. Boyd-Graber |
| 2019 | ACL | Compositional Questions Do Not Necessitate Multi-hop Reasoning. | Sewon Min, Eric Wallace, Sameer Singh, Matt Gardner, Hannaneh Hajishirzi, Luke Zettlemoyer |
| 2019 | EMNLP | Universal Adversarial Triggers for Attacking and Analyzing NLP. | Eric Wallace, Shi Feng, Nikhil Kandpal, Matt Gardner, Sameer Singh |
| 2019 | EMNLP | AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models. | Eric Wallace, Jens Tuyls, Junlin Wang, Sanjay Subramanian, Matt Gardner, Sameer Singh |
| 2019 | EMNLP | Do NLP Models Know Numbers? Probing Numeracy in Embeddings. | Eric Wallace, Yizhong Wang, Sujian Li, Sameer Singh, Matt Gardner |
| 2019 | ICML | Understanding Impacts of High-Order Loss Approximations and Features in Deep Learning Interpretation. | Sahil Singla, Eric Wallace, Shi Feng, Soheil Feizi |
| 2018 | ACL | Trick Me If You Can: Adversarial Writing of Trivia Challenge Questions. | Eric Wallace, Jordan L. Boyd-Graber |
| 2018 | EMNLP | Pathologies of Neural Models Make Interpretation Difficult. | Shi Feng, Eric Wallace, Alvin Grissom II, Mohit Iyyer, Pedro Rodriguez, Jordan L. Boyd-Graber |
| 2018 | EMNLP | Interpreting Neural Networks with Nearest Neighbors. | Eric Wallace, Shi Feng, Jordan L. Boyd-Graber |