← Authors

Eric Wallace

36 papers · 2018–2025 · 6 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (6) 🐝 Cross-Pollinator (15) 🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🌍 Conference Polyglot (6) πŸƒ Academic Marathon (7) πŸ—ΊοΈ Taxonomy Completionist (61) πŸŒ‰ Interdisciplinary Bridge 🌟 Keyword Trendsetter Combo (3) 🀝 Dynamic Duo (14) πŸ‘₯ Mega-Team (26) 🧬 Topic Evolution πŸ† Keyword Champion (5) 🌱 Topic Pioneer ❓ The Questioner (3) πŸ’Ž Century Club (36) πŸ—ƒοΈ Keyword Collector (131) πŸ“ˆ Trend Setter ⚑ Prolific Year (9) πŸ”₯ Unstoppable (8)

Conferences

EMNLP (10) ACL (8) ICML (8) ICLR (4) IJCNLP (3) NAACL (3)

Top co-authors

Sameer Singh (14) Matt Gardner (9) Shi Feng (8) Dan Klein (6) Jordan Boyd-Graber (4) Nikhil Kandpal (4) Jens Tuyls (3) Hannaneh Hajishirzi (3) Dawn Song (3) Luke Zettlemoyer (3)

Research topics

Privacy (1)

Keywords

language model (7) adversarial attack (7) neural network (7) saliency map (5) model interpretation (4) prompt engineering (3) gradient-guided search (3) question answering (3) model robustness (3) annotation artifact (3) model interpretability (3) large language model (3) self-supervised pretraining (2) few-shot learning (2) adversarial example (2) text classification (2) natural language processing (2) training datum (2) adversarial learning (2) transfer learning (2)

Papers

Unfamiliar Finetuning Examples Control How Language Models Hallucinate NAACL 2025
What Evidence Do Language Models Find Convincing? ACL 2024
Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation ICML 2024
Stealing part of a production language model ICML 2024
SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore ICLR 2024
The False Promise of Imitating Proprietary Language Models ICLR 2024
Measuring Forgetting of Memorized Training Examples ICLR 2023
InCoder: A Generative Model for Code Infilling and Synthesis ICLR 2023
Large Language Models Struggle to Learn Long-Tail Knowledge ICML 2023
Poisoning Language Models During Instruction Tuning ICML 2023
Analyzing Dynamic Adversarial Training Data in the Limit ACL 2022
Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models ACL 2022
Deduplicating Training Data Mitigates Privacy Risks in Language Models ICML 2022
Automated Crossword Solving ACL 2022
Calibrate Before Use: Improving Few-shot Performance of Language Models ICML 2021
Concealed Data Poisoning Attacks on NLP Models NAACL 2021
Detoxifying Language Models Risks Marginalizing Minority Voices NAACL 2021
Train Big, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers ICML 2020
Imitation Attacks and Defenses for Black-box Machine Translation Systems EMNLP 2020
Pretrained Transformers Improve Out-of-Distribution Robustness ACL 2020
Interpreting Predictions of NLP Models EMNLP 2020
Gradient-based Analysis of NLP Models is Manipulable EMNLP 2020
Evaluating Models’ Local Decision Boundaries via Contrast Sets EMNLP 2020
AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts EMNLP 2020
Universal Adversarial Triggers for Attacking and Analyzing NLP EMNLP 2019
Do NLP Models Know Numbers? Probing Numeracy in Embeddings EMNLP 2019
AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models EMNLP 2019
Understanding Impacts of High-Order Loss Approximations and Features in Deep Learning Interpretation ICML 2019
Compositional Questions Do Not Necessitate Multi-hop Reasoning ACL 2019
Misleading Failures of Partial-input Baselines ACL 2019
Universal Adversarial Triggers for Attacking and Analyzing NLP IJCNLP 2019
Do NLP Models Know Numbers? Probing Numeracy in Embeddings IJCNLP 2019
AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models IJCNLP 2019
Trick Me If You Can: Adversarial Writing of Trivia Challenge Questions ACL 2018
Pathologies of Neural Models Make Interpretations Difficult EMNLP 2018
Interpreting Neural Networks with Nearest Neighbors EMNLP 2018