Joe Benton

According to our database, Joe Benton authored at least 18 papers between 2022 and 2025.

Collaborative distances:

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

2025

Inverse Scaling in Test-Time Compute.

Aryo Pradipta Gema, Alexander Hägele, Runjin Chen, Andy Arditi, Jacob Goldman-Wetzler, Kit Fraser-Taliente, Henry Sleight, Linda Petrini, Julian Michael, Beatrice Alex, Pasquale Minervini, Yanda Chen, Joe Benton, Ethan Perez

CoRR, July, 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

Teaching Models to Verbalize Reward Hacking in Chain-of-Thought Reasoning.

Miles Turpin, Andy Arditi, Marvin Li, Joe Benton, Julian Michael

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

Reasoning Models Don't Always Say What They Think.

Yanda Chen, Joe Benton, Ansh Radhakrishnan, Jonathan Uesato, Carson Denison, John Schulman, Arushi Somani, Peter Hase, Misha Wagner, Fabien Roger, Vladimir Mikulik, Samuel R. Bowman, Jan Leike, Jared Kaplan, Ethan Perez

CoRR, May, 2025

Constitutional Classifiers: Defending against Universal Jailbreaks across Thousands of Hours of Red Teaming.

Mrinank Sharma, Meg Tong, Jesse Mu, Jerry Wei, Jorrit Kruthoff, Scott Goodfriend, Euan Ong, Alwin Peng, Raj Agarwal, Cem Anil, Amanda Askell, Nathan Bailey, Joe Benton, Emma Bluemke, Samuel R. Bowman, Eric Christiansen, Hoagy Cunningham, Andy Dau, Anjali Gopal, Rob Gilson, Logan Graham, Logan Howard, Nimit Kalra, Taesung Lee, Kevin Lin, Peter Lofgren, Francesco Mosconi, Clare O'Hara, Catherine Olsson, Linda Petrini, Samir Rajani, Nikhil Saxena, Alex Silverstein, Tanya Singh, Theodore R. Sumers, Leonard Tang, Kevin K. Troy, Constantin Weisser, Ruiqi Zhong, Giulio Zhou, Jan Leike, Jared Kaplan, Ethan Perez

CoRR, January, 2025

Failures to Find Transferable Image Jailbreaks Between Vision-Language Models.

Rylan Schaeffer, Dan Valentine, Luke Bailey, James Chua, Cristóbal Eyzaguirre, Zane Durante, Joe Benton, Brando Miranda, Henry Sleight, Tony Tong Wang, John Hughes, Rajashree Agrawal, Mrinank Sharma, Scott Emmons, Sanmi Koyejo, Ethan Perez

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Error Bounds for Flow Matching Methods.

Joe Benton, George Deligiannidis, Arnaud Doucet

Trans. Mach. Learn. Res., 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

When Do Universal Image Jailbreaks Transfer Between Vision-Language Models?

Rylan Schaeffer, Dan Valentine, Luke Bailey, James Chua, Cristóbal Eyzaguirre, Zane Durante, Joe Benton, Brando Miranda, Henry Sleight, John Hughes, Rajashree Agrawal, Mrinank Sharma, Scott Emmons, Sanmi Koyejo, Ethan Perez

CoRR, 2024

Many-shot Jailbreaking.

Cem Anil, Esin Durmus, Nina Panickssery, Mrinank Sharma, Joe Benton, Sandipan Kundu, Joshua Batson, Meg Tong, Jesse Mu, Daniel Ford, Francesco Mosconi, Rajashree Agrawal, Rylan Schaeffer, Naomi Bashkansky, Samuel Svenningsen, Mike Lambert, Ansh Radhakrishnan, Carson Denison, Evan Hubinger, Yuntao Bai, Trenton Bricken, Timothy Maxwell, Nicholas Schiefer, James Sully, Alex Tamkin, Tamera Lanham, Karina Nguyen, Tomek Korbak, Jared Kaplan, Deep Ganguli, Samuel R. Bowman, Ethan Perez, Roger B. Grosse, David Kristjanson Duvenaud

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Nearly d-Linear Convergence Bounds for Diffusion Models via Stochastic Localization.

Joe Benton, Valentin De Bortoli, Arnaud Doucet, George Deligiannidis

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics.

Kamélia Daudel, Joe Benton, Yuyang Shi, Arnaud Doucet

J. Mach. Learn. Res., 2023

Measuring Feature Sparsity in Language Models.

Mingyang Deng, Lucas Tao, Joe Benton

CoRR, 2023

Linear Convergence Bounds for Diffusion Models via Stochastic Localization.

Joe Benton, Valentin De Bortoli, Arnaud Doucet, George Deligiannidis

CoRR, 2023

2022

From Denoising Diffusions to Denoising Markov Models.

Joe Benton, Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet

CoRR, 2022

Polysemanticity and Capacity in Neural Networks.

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

CoRR, 2022

A Continuous Time Framework for Discrete Denoising Models.

Andrew Campbell, Joe Benton, Valentin De Bortoli, Thomas Rainforth, George Deligiannidis, Arnaud Doucet

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