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2020 – today
- 2024
[i4]Aengus Lynch, Phillip Guo, Aidan Ewart, Stephen Casper, Dylan Hadfield-Menell:
Eight Methods to Evaluate Robust Unlearning in LLMs. CoRR abs/2402.16835 (2024)- [i3]Abhay Sheshadri, Aidan Ewart, Phillip Guo, Aengus Lynch, Cindy Wu, Vivek Hebbar, Henry Sleight, Asa Cooper Stickland, Ethan Perez, Dylan Hadfield-Menell, Stephen Casper:
Targeted Latent Adversarial Training Improves Robustness to Persistent Harmful Behaviors in LLMs. CoRR abs/2407.15549 (2024) - 2023
- [i2]Andy Zou, Long Phan, Sarah Chen, James Campbell, Phillip Guo, Richard Ren, Alexander Pan, Xuwang Yin, Mantas Mazeika, Ann-Kathrin Dombrowski, Shashwat Goel, Nathaniel Li, Michael J. Byun, Zifan Wang, Alex Mallen, Steven Basart, Sanmi Koyejo, Dawn Song, Matt Fredrikson
, J. Zico Kolter, Dan Hendrycks:
Representation Engineering: A Top-Down Approach to AI Transparency. CoRR abs/2310.01405 (2023) - [i1]James Campbell, Richard Ren, Phillip Guo:
Localizing Lying in Llama: Understanding Instructed Dishonesty on True-False Questions Through Prompting, Probing, and Patching. CoRR abs/2311.15131 (2023) - 2022
- [c1]Phillip Guo, Michael C. Fu:
Bandit-Based Multi-Start Strategies for Global Continuous Optimization. WSC 2022: 3194-3205
Coauthor Index
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