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Journal Articles
- 2024
[j1]Buck Shlegeris, Fabien Roger, Lawrence Chan, Euan McLean:
Language Models Are Better Than Humans at Next-token Prediction. Trans. Mach. Learn. Res. 2024 (2024)
Conference and Workshop Papers
- 2024
- [c3]Ryan Greenblatt, Buck Shlegeris, Kshitij Sachan, Fabien Roger:
AI Control: Improving Safety Despite Intentional Subversion. ICML 2024 - 2023
- [c2]Kevin Ro Wang, Alexandre Variengien, Arthur Conmy, Buck Shlegeris, Jacob Steinhardt:
Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 Small. ICLR 2023 - 2022
- [c1]Daniel M. Ziegler, Seraphina Nix, Lawrence Chan, Tim Bauman, Peter Schmidt-Nielsen, Tao Lin, Adam Scherlis, Noa Nabeshima, Ben Weinstein-Raun, Daniel de Haas, Buck Shlegeris, Nate Thomas:
Adversarial training for high-stakes reliability. NeurIPS 2022
Informal and Other Publications
- 2024
- [i11]Evan Hubinger, Carson Denison, Jesse Mu, Mike Lambert, Meg Tong, Monte MacDiarmid, Tamera Lanham, Daniel M. Ziegler, Tim Maxwell, Newton Cheng, Adam S. Jermyn, Amanda Askell, Ansh Radhakrishnan, Cem Anil, David Duvenaud, Deep Ganguli, Fazl Barez, Jack Clark, Kamal Ndousse, Kshitij Sachan, Michael Sellitto, Mrinank Sharma, Nova DasSarma, Roger Grosse, Shauna Kravec, Yuntao Bai, Zachary Witten, Marina Favaro, Jan Brauner, Holden Karnofsky, Paul F. Christiano, Samuel R. Bowman, Logan Graham, Jared Kaplan, Sören Mindermann, Ryan Greenblatt, Buck Shlegeris, Nicholas Schiefer, Ethan Perez:
Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training. CoRR abs/2401.05566 (2024) - [i10]Carson Denison, Monte MacDiarmid, Fazl Barez, David Duvenaud, Shauna Kravec, Samuel Marks, Nicholas Schiefer, Ryan Soklaski, Alex Tamkin, Jared Kaplan, Buck Shlegeris, Samuel R. Bowman, Ethan Perez, Evan Hubinger:
Sycophancy to Subterfuge: Investigating Reward-Tampering in Large Language Models. CoRR abs/2406.10162 (2024) - [i9]Charlie Griffin, Louis Thomson, Buck Shlegeris, Alessandro Abate:
Games for AI Control: Models of Safety Evaluations of AI Deployment Protocols. CoRR abs/2409.07985 (2024) - 2023
- [i8]Fabien Roger, Ryan Greenblatt, Max Nadeau, Buck Shlegeris, Nate Thomas:
Measurement Tampering Detection Benchmark. CoRR abs/2308.15605 (2023) - [i7]Chris MacLeod, Evgenia Nitishinskaya, Buck Shlegeris:
Generalized Wick Decompositions. CoRR abs/2310.06686 (2023) - [i6]Ryan Greenblatt, Buck Shlegeris, Kshitij Sachan, Fabien Roger:
AI Control: Improving Safety Despite Intentional Subversion. CoRR abs/2312.06942 (2023) - 2022
- [i5]Daniel M. Ziegler, Seraphina Nix, Lawrence Chan, Tim Bauman, Peter Schmidt-Nielsen, Tao Lin, Adam Scherlis, Noa Nabeshima, Ben Weinstein-Raun, Daniel de Haas, Buck Shlegeris, Nate Thomas:
Adversarial Training for High-Stakes Reliability. CoRR abs/2205.01663 (2022) - [i4]Adam Scherlis, Kshitij Sachan, Adam S. Jermyn, Joe Benton, Buck Shlegeris:
Polysemanticity and Capacity in Neural Networks. CoRR abs/2210.01892 (2022) - [i3]Kevin Wang, Alexandre Variengien, Arthur Conmy, Buck Shlegeris, Jacob Steinhardt:
Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small. CoRR abs/2211.00593 (2022) - [i2]Buck Shlegeris, Fabien Roger, Lawrence Chan, Euan McLean:
Language models are better than humans at next-token prediction. CoRR abs/2212.11281 (2022) - 2018
- [i1]Paul F. Christiano, Buck Shlegeris, Dario Amodei:
Supervising strong learners by amplifying weak experts. CoRR abs/1810.08575 (2018)
Coauthor Index
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