Shlegeris, Buck

Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small

Wang, K., Variengien, A., Conmy, A., Shlegeris, B., & Steinhardt, J. (2022) · arXiv

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 52

Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training

Hubinger, E., Denison, C., Mu, J., Lambert, M., Tong, M., MacDiarmid, M., Lanham, T., Ziegler, D. M., Maxwell, T., Cheng, N., et al. (2024) · arXiv

Adversarial Robustness in Machine LearningEthics and Social Impacts of AI

Cited by 46

Supervising strong learners by amplifying weak experts

Christiano, P., Shlegeris, B., & Amodei, D. (2018) · arXiv

Reinforcement Learning in RoboticsMachine Learning and Algorithms

Cited by 39

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

Sycophancy to Subterfuge: Investigating Reward-Tampering in Large Language Models

Denison, C., MacDiarmid, M., Barez, F., Duvenaud, D., Kravec, S., Marks, S., Schiefer, N., Soklaski, R., Tamkin, A., Kaplan, J., et al. (2024) · arXiv

Reinforcement Learning in RoboticsEthics and Social Impacts of AI

Cited by 11

AI Control: Improving Safety Despite Intentional Subversion

Greenblatt, R., Shlegeris, B., Sachan, K., & Roger, F. (2023) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 3

Sabotage Evaluations for Frontier Models

Benton, J., Wagner, M., Christiansen, E., Anil, C., Perez, E., Srivastav, J., Durmus, E., Ganguli, D., Kravec, S., Shlegeris, B., et al. (2024) · arXiv

Adversarial Robustness in Machine LearningEthics and Social Impacts of AI

Cited by 2

Adaptive Deployment of Untrusted LLMs Reduces Distributed Threats

Wen, J., Hebbar, V., Larson, C., Bhatt, A., Radhakrishnan, A., Sharma, M., Sleight, H., Feng, S., He, H., Perez, E., et al. (2024) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 1

Ctrl-Z: Controlling AI Agents via Resampling

Bhatt, A., Rushing, C., Kaufman, A., Tracy, T., Georgiev, V., Matolcsi, D., Khan, A., & Shlegeris, B. (2025) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 0

Subversion Strategy Eval: Can language models statelessly strategize to subvert control protocols?

Mallen, A., Griffin, C., Wagner, M., Abate, A., & Shlegeris, B. (2024) · arXiv

Ethics and Social Impacts of AIAdversarial Robustness in Machine Learning

Cited by 0