---
title: "Eric Wallace — all works — Elamur Research"
description: "All 26 works of Eric Wallace in the Elamur Research library, the most cited first: our summaries where we have them, else the original."
canonical: "https://research.elamur.ai/free/en/authors/eric-wallace/works/"
---
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# Eric Wallace — all works

26 works · [← Eric Wallace](https://md.research.elamur.ai/free/en/authors/eric-wallace/)

1. **[AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts](https://md.research.elamur.ai/free/en/papers/shin-2020-autoprompt-eliciting-knowledge-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Taylor Shin, Yasaman Razeghi, Robert L. Logan IV, et al.*2020 · 1,909 citations*
2. **[Universal Adversarial Triggers for Attacking and Analyzing NLP ↗](https://aclanthology.org/D19-1221/) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) · no summary yet**Eric Wallace et al.*2019 · 989 citations*
3. [**Extracting Training Data from Large Language Models arXiv:2012.07805**Nicholas Carlini, Florian Tramer, Eric Wallace, et al.*2020 · 955 citations*](https://md.research.elamur.ai/free/en/papers/carlini-2020-extracting-training-data-large-language/)
4. [**Calibrate Before Use: Improving Few-Shot Performance of Language Models arXiv:2102.09690**Tony Z. Zhao, Eric Wallace, Shi Feng, et al.*2021 · 825 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2021-calibrate-before-use-improving-few/)
5. [**Evaluating Models' Local Decision Boundaries via Contrast Sets**Matt Gardner, Yoav Artzi, Victoria Basmov, et al.*Mova's core list · 531 citations*](https://md.research.elamur.ai/free/en/papers/gardner-2020-evaluating-models-local-decision-boundaries/)
6. **[Pretrained Transformers Improve Out-of-Distribution Robustness](https://md.research.elamur.ai/free/en/papers/hendrycks-2020-pretrained-transformers-improve-out-distribution/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dan Hendrycks, Xiaoyuan Liu, Eric Wallace, et al.*2020 · 452 citations*
7. **[Pathologies of Neural Models Make Interpretations Difficult ↗](https://aclanthology.org/D18-1407/) Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · no summary yet**Shi Feng et al.*2018 · 380 citations*
8. [**Large Language Models Struggle to Learn Long-Tail Knowledge arXiv:2211.08411**Nikhil Kandpal, Haikang Deng, Adam Roberts, et al.*2022 · 366 citations*](https://md.research.elamur.ai/free/en/papers/kandpal-2022-large-language-models-struggle-learn/)
9. **[Do NLP Models Know Numbers? Probing Numeracy in Embeddings](https://md.research.elamur.ai/free/en/papers/wallace-2019-do-nlp-models-know-numbers/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Eric Wallace, Yizhong Wang, Sujian Li, et al.*2019 · 352 citations*
10. **[Compositional Questions Do Not Necessitate Multi-hop Reasoning](https://md.research.elamur.ai/free/en/papers/min-2019-compositional-questions-do-not-necessitate/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sewon Min, Eric Wallace, Sameer Singh, et al.*2019 · 235 citations*
11. **[Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models](https://md.research.elamur.ai/free/en/papers/iv-2022-cutting-down-prompts-parameters-simple/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Robert Logan IV, Ivana Balazevic, Eric Wallace, et al.*2022 · 216 citations*
12. [**Scalable Extraction of Training Data from (Production) Language Models arXiv:2311.17035**Milad Nasr, Nicholas Carlini, Jonathan Hayase, et al.*2023 · 211 citations*](https://md.research.elamur.ai/free/en/papers/nasr-2023-scalable-extraction-training-data-production/)
13. [**The False Promise of Imitating Proprietary LLMs arXiv:2305.15717**Arnav Gudibande, Eric Wallace, Charlie Snell, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/gudibande-2023-false-promise-imitating-proprietary-llms/)
14. **[AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models](https://md.research.elamur.ai/free/en/papers/wallace-2019-allennlp-interpret-framework-explaining-predictions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Eric Wallace, Jens Tuyls, Junlin Wang, et al.*2019 · 182 citations*
15. **[Trick Me If You Can: Human-in-the-Loop Generation of Adversarial Examples for Question Answering](https://md.research.elamur.ai/free/en/papers/wallace-2019-trick-me-if-you-can/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Eric Wallace, Pedro Rodriguez, Shi Feng, et al.*2019 · 182 citations*
16. [**Deduplicating Training Data Mitigates Privacy Risks in Language Models arXiv:2202.06539**Nikhil Kandpal, Eric Wallace, Colin Raffel*2022 · 172 citations*](https://md.research.elamur.ai/free/en/papers/kandpal-2022-deduplicating-training-data-mitigates-privacy/)
17. **[Concealed Data Poisoning Attacks on NLP Models ↗](https://aclanthology.org/2021.naacl-main.13/) Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yet**Eric Wallace et al.*2021 · 153 citations*
18. **[Detoxifying Language Models Risks Marginalizing Minority Voices](https://md.research.elamur.ai/free/en/papers/xu-2021-detoxifying-language-models-risks-marginalizing/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Albert Xu, Eshaan Pathak, Eric Wallace, et al.*2021 · 137 citations*
19. **[Train Big, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers ↗](https://openalex.org/W3034340181) International Conference on Machine Learning · no summary yet**Zhuohan Li et al.*2020 · 133 citations*
20. [**Deliberative Alignment: Reasoning Enables Safer Language Models arXiv:2412.16339**Melody Y. Guan, Manas Joglekar, Eric Wallace, et al.*2024 · 115 citations*](https://md.research.elamur.ai/free/en/papers/guan-2024-deliberative-alignment-reasoning-enables-safer/)
21. **[Imitation Attacks and Defenses for Black-box Machine Translation Systems ↗](https://aclanthology.org/2020.emnlp-main.446/) Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · no summary yet**Eric Wallace, Mitchell Stern, Dawn Song*2020 · 106 citations*
22. **[Train Large, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers ↗](https://arxiv.org/abs/2002.11794) arXiv (Cornell University) · no summary yet**Zhuohan Li et al.*2020 · 93 citations*
23. **[The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions ↗](https://arxiv.org/abs/2404.13208) arXiv:2404.13208 · no summary yet**Eric Wallace et al.*2024 · 83 citations*
24. **[Interpreting Neural Networks with Nearest Neighbors ↗](https://aclanthology.org/W18-5416/) Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP · no summary yet**Eric Wallace, Shi Feng, Jordan Boyd-Graber*2018 · 77 citations*
25. **[Unfamiliar Finetuning Examples Control How Language Models Hallucinate](https://md.research.elamur.ai/free/en/papers/kang-2025-unfamiliar-finetuning-examples-control-how/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Katie Kang, Eric Wallace, Claire Tomlin, et al.*2025 · 47 citations*
26. **[Automated Crossword Solving ↗](https://aclanthology.org/2022.acl-long.219/) Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Eric Wallace et al.*2022 · 19 citations*