Treutlein, Johannes

Alignment faking in large language models

Greenblatt, R., Denison, C., Wright, B., Roger, F., MacDiarmid, M., Marks, S., Treutlein, J., Belonax, T., Chen, J., Duvenaud, D., et al. (2024) · arXiv

Ethics and Social Impacts of AIAdversarial Robustness in Machine Learning

Cited by 30

Connecting the Dots: LLMs can Infer and Verbalize Latent Structure from Disparate Training Data

Treutlein, J., Choi, D., Betley, J., Marks, S., Anil, C., Grosse, R., & Evans, O. (2024) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 6

Auditing language models for hidden objectives

Marks, S., Treutlein, J., Bricken, T., Lindsey, J., Marcus, J., Mishra-Sharma, S., Ziegler, D., Ameisen, E., Batson, J., Belonax, T., et al. (2025) · arXiv

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 4

Normative Disagreement as a Challenge for Cooperative AI

Stastny, J., Riché, M., Lyzhov, A., Treutlein, J., Dafoe, A., & Clifton, J. (2021) · arXiv

Reinforcement Learning in RoboticsMulti-Agent Systems and Negotiation

Cited by 3

School of Reward Hacks: Hacking harmless tasks generalizes to misaligned behavior in LLMs

Taylor, M., Chua, J., Betley, J., Treutlein, J., & Evans, O. (2025) · arXiv

Ethics and Social Impacts of AIAdversarial Robustness in Machine Learning

Cited by 0