Aaron D. Tucker

According to our database, Aaron D. Tucker authored at least 11 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Concept Influence: Leveraging Interpretability to Improve Performance and Efficiency in Training Data Attribution.

Matthew Kowal, Goncalo Paulo, Louis Jaburi, Tom Tseng, Lev E. McKinney, Stefan Heimersheim, Aaron David Tucker, Adam Gleave, Kellin Pelrine

CoRR, February, 2026

STACK: Adversarial Attacks on LLM Safeguard Pipelines.

Ian R. McKenzie, Oskar John Hollinsworth, Tom Tseng, Xander Davies, Stephen Casper, Aaron David Tucker, Robert Kirk, Adam Gleave

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Interpreting learned search: finding a transition model and value function in an RNN that plays Sokoban.

Mohammad Taufeeque, Aaron David Tucker, Adam Gleave, Adrià Garriga-Alonso

CoRR, June, 2025

Scaling Trends in Language Model Robustness.

Nikolaus H. R. Howe, Ian R. McKenzie, Oskar John Hollinsworth, Michal Zajac, Tom Tseng, Aaron David Tucker, Pierre-Luc Bacon, Adam Gleave

Proceedings of the Forty-second International Conference on Machine Learning, 2025

If You Give an LLM a Legal Practice Guide.

Colin Doyle, Aaron D. Tucker

Proceedings of the 2025 Symposium on Computer Science and Law, 2025

2024

Coactive Learning for Large Language Models using Implicit User Feedback.

Aaron David Tucker, Kianté Brantley, Adam Cahall, Thorsten Joachims

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Variance-Minimizing Augmentation Logging for Counterfactual Evaluation in Contextual Bandits.

Aaron David Tucker, Thorsten Joachims

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Bandits with costly reward observations.

Aaron David Tucker, Caleb Biddulph, Claire Wang, Thorsten Joachims

Proceedings of the Uncertainty in Artificial Intelligence, 2023

2022

Variance-Optimal Augmentation Logging for Counterfactual Evaluation in Contextual Bandits.

Aaron David Tucker, Thorsten Joachims

CoRR, 2022

2020

Social and Governance Implications of Improved Data Efficiency.

Aaron D. Tucker, Markus Anderljung, Allan Dafoe

Proceedings of the AIES '20: AAAI/ACM Conference on AI, 2020

2018

Inverse reinforcement learning for video games.

Aaron Tucker, Adam Gleave, Stuart Russell

CoRR, 2018