Wallace, Eric

AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts

Shin, T., Razeghi, Y., Logan IV, R. L., Wallace, E., & Singh, S. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Topic ModelingNatural Language Processing Techniques

Cited by 1,279

Extracting Training Data from Large Language Models

Carlini, N., Tramer, F., Wallace, E., Jagielski, M., Herbert-Voss, A., Lee, K., Roberts, A., Brown, T., Song, D., Erlingsson, U., et al. (2020) · arXiv

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 727

Universal Adversarial Triggers for Attacking and Analyzing NLP

Wallace, E., Feng, S., Kandpal, N., Gardner, M., & Singh, S. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 642

Calibrate Before Use: Improving Few-Shot Performance of Language Models

Zhao, T. Z., Wallace, E., Feng, S., Klein, D., & Singh, S. (2021) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 513

Do NLP Models Know Numbers? Probing Numeracy in Embeddings

Wallace, E., Wang, Y., Li, S., Singh, S., & Gardner, M. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

Topic ModelingNatural Language Processing Techniques

Cited by 227

GPT-4o System Card

OpenAI, :, Hurst, A., Lerer, A., Goucher, A. P., Perelman, A., Ramesh, A., Clark, A., Ostrow, A., Welihinda, A., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 180

Compositional Questions Do Not Necessitate Multi-hop Reasoning

Min, S., Wallace, E., Singh, S., Gardner, M., Hajishirzi, H., & Zettlemoyer, L. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Topic ModelingInformation Retrieval and Search Behavior

Cited by 138

Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models

Logan IV, R., Balazevic, I., Wallace, E., Petroni, F., Singh, S., & Riedel, S. (2022) · Findings of the Association for Computational Linguistics: ACL 2022

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 133

AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models

Wallace, E., Tuyls, J., Wang, J., Subramanian, S., Gardner, M., & Singh, S. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 116

Concealed Data Poisoning Attacks on NLP Models

Wallace, E., Zhao, T., Feng, S., & Singh, S. (2021) · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 115

Imitation Attacks and Defenses for Black-box Machine Translation Systems

Wallace, E., Stern, M., & Song, D. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 75

OpenAI GPT-5 System Card

Singh, A., Fry, A., Perelman, A., Tart, A., Ganesh, A., El-Kishky, A., McLaughlin, A., Low, A., Ostrow, A., Ananthram, A., et al. (2026) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 26

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

Wallace, E., & Boyd-Graber, J. (2018) · Proceedings of ACL 2018, Student Research Workshop

Topic ModelingAdversarial Robustness in Machine Learning

Cited by 14

The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions

Wallace, E., Xiao, K., Leike, R., Weng, L., Heidecke, J., & Beutel, A. (2024) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 14