Buck Shlegeris

According to our database, Buck Shlegeris authored at least 22 papers between 2018 and 2025.

Collaborative distances:

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

2025

Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety.

Tomek Korbak, Mikita Balesni, Elizabeth Barnes, Yoshua Bengio, Joe Benton, Joseph Bloom, Mark Chen, Alan Cooney, Allan Dafoe, Anca D. Dragan, Scott Emmons, Owain Evans, David Farhi, Ryan Greenblatt, Dan Hendrycks, Marius Hobbhahn, Evan Hubinger, Geoffrey Irving, Erik Jenner, Daniel Kokotajlo, Victoria Krakovna, Shane Legg, David Lindner, David Luan, Aleksander Madry, Julian Michael, Neel Nanda, Dave Orr, Jakub Pachocki, Ethan Perez, Mary Phuong, Fabien Roger, Joshua Saxe, Buck Shlegeris, Martín Soto, Eric Steinberger, Jasmine Wang, Wojciech Zaremba, Bowen Baker, Rohin Shah, Vladimir Mikulik

CoRR, July, 2025

The Singapore Consensus on Global AI Safety Research Priorities.

Yoshua Bengio, Tegan Maharaj, Luke Ong, Stuart Russell, Dawn Song, Max Tegmark, Lan Xue, Ya-Qin Zhang, Stephen Casper, Wan Sie Lee, Sören Mindermann, Vanessa Wilfred, Vidhisha Balachandran, Fazl Barez, Michael Belinsky, Imane Bello, Malo Bourgon, Mark Brakel, Siméon Campos, Duncan Cass-Beggs, Jiahao Chen, Rumman Chowdhury, Kuan Chua Seah, Jeff Clune, Juntao Dai, Agnès Delaborde, Nouha Dziri, Francisco Eiras, Joshua Engels, Jinyu Fan, Adam Gleave, Noah Goodman, Fynn Heide, Johannes Heidecke, Dan Hendrycks, Cyrus Hodes, Bryan Low Kian Hsiang, Minlie Huang, Sami Jawhar, Wang Jingyu, Adam Tauman Kalai, Meindert Kamphuis, Mohan S. Kankanhalli, Subhash Kantamneni, Mathias Bonde Kirk, Thomas Kwa, Jeffrey Ladish, Kwok-Yan Lam, Wan Lee Sie, Taewhi Lee, Xiaojian Li, Jiajun Liu, Chaochao Lu, Yifan Mai, Richard Mallah, Julian Michael, Nick Moës, Simon Möller, Kihyuk Nam, Kwan Yee Ng, Mark Nitzberg, Besmira Nushi, Seán Ó hÉigeartaigh, Alejandro Ortega, Pierre Peigné, James Petrie, Benjamin Prud'homme, Reihaneh Rabbany, Nayat Sanchez-Pi, Sarah Schwettmann, Buck Shlegeris, Saad Siddiqui, Aradhana Sinha, Martín Soto, Cheston Tan, Dong Ting, William-Chandra Tjhi, Robert Trager, Brian Tse, Anthony Tung K. H., John Willes, Denise Wong, Wei Xu, Rongwu Xu, Yi Zeng, HongJiang Zhang, Djordje Zikelic

CoRR, June, 2025

SHADE-Arena: Evaluating Sabotage and Monitoring in LLM Agents.

Jonathan Kutasov, Yuqi Sun, Paul Colognese, Teun van der Weij, Linda Petrini, Chen Bo Calvin Zhang, John Hughes, Xiang Deng, Henry Sleight, Tyler Tracy, Buck Shlegeris, Joe Benton

CoRR, June, 2025

Ctrl-Z: Controlling AI Agents via Resampling.

Aryan Bhatt, Cody Rushing, Adam Kaufman, Tyler Tracy, Vasil Georgiev, David Matolcsi, Akbir Khan, Buck Shlegeris

CoRR, April, 2025

How to evaluate control measures for LLM agents? A trajectory from today to superintelligence.

Tomek Korbak, Mikita Balesni, Buck Shlegeris, Geoffrey Irving

CoRR, April, 2025

A sketch of an AI control safety case.

Tomek Korbak, Joshua Clymer, Benjamin Hilton, Buck Shlegeris, Geoffrey Irving

CoRR, January, 2025

Adaptive Deployment of Untrusted LLMs Reduces Distributed Threats.

Jiaxin Wen, Vivek Hebbar, Caleb Larson, Aryan Bhatt, Ansh Radhakrishnan, Mrinank Sharma, Henry Sleight, Shi Feng, He He, Ethan Perez, Buck Shlegeris, Akbir Khan

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Language Models Are Better Than Humans at Next-token Prediction.

Buck Shlegeris, Fabien Roger, Lawrence Chan, Euan McLean

Trans. Mach. Learn. Res., 2024

Alignment faking in large language models.

Ryan Greenblatt, Carson Denison, Benjamin Wright, Fabien Roger, Monte MacDiarmid, Samuel Marks, Johannes Treutlein, Tim Belonax, Jack Chen, David Duvenaud, Akbir Khan, Julian Michael, Sören Mindermann, Ethan Perez, Linda Petrini, Jonathan Uesato, Jared Kaplan, Buck Shlegeris, Samuel R. Bowman, Evan Hubinger

CoRR, 2024

Subversion Strategy Eval: Evaluating AI's stateless strategic capabilities against control protocols.

Alex Mallen, Charlie Griffin, Alessandro Abate, Buck Shlegeris

CoRR, 2024

Towards evaluations-based safety cases for AI scheming.

Mikita Balesni, Marius Hobbhahn, David Lindner, Alexander Meinke, Tomek Korbak, Joshua Clymer, Buck Shlegeris, Jérémy Scheurer, Charlotte Stix, Rusheb Shah, Nicholas Goldowsky-Dill, Dan Braun, Bilal Chughtai, Owain Evans, Daniel Kokotajlo, Lucius Bushnaq

CoRR, 2024

Sabotage Evaluations for Frontier Models.

Joe Benton, Misha Wagner, Eric Christiansen, Cem Anil, Ethan Perez, Jai Srivastav, Esin Durmus, Deep Ganguli, Shauna Kravec, Buck Shlegeris, Jared Kaplan, Holden Karnofsky, Evan Hubinger, Roger B. Grosse, Samuel R. Bowman, David Duvenaud

CoRR, 2024

Games for AI Control: Models of Safety Evaluations of AI Deployment Protocols.

Charlie Griffin, Louis Thomson, Buck Shlegeris, Alessandro Abate

CoRR, 2024

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

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

CoRR, 2024

Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training.

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 B. 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

CoRR, 2024

AI Control: Improving Safety Despite Intentional Subversion.

Ryan Greenblatt, Buck Shlegeris, Kshitij Sachan, Fabien Roger

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

2023

Generalized Wick Decompositions.

Chris MacLeod, Evgenia Nitishinskaya, Buck Shlegeris

CoRR, 2023

Measurement Tampering Detection Benchmark.

Fabien Roger, Ryan Greenblatt, Max Nadeau, Buck Shlegeris, Nate Thomas

CoRR, 2023

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

Kevin Ro Wang, Alexandre Variengien, Arthur Conmy, Buck Shlegeris, Jacob Steinhardt

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Polysemanticity and Capacity in Neural Networks.

Adam Scherlis, Kshitij Sachan, Adam S. Jermyn, Joe Benton, Buck Shlegeris

CoRR, 2022

Adversarial training for high-stakes reliability.

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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2018

Supervising strong learners by amplifying weak experts.

Paul F. Christiano, Buck Shlegeris, Dario Amodei

CoRR, 2018