A Continuous Time Framework for Discrete Denoising Models. - Andrew Campbell; Joe Benton; Valentin De Bortoli; Thomas Rainforth; George Deligiannidis; Arnaud Doucet (NeurIPS, 2022)

Polysemanticity and Capacity in Neural Networks. - Adam Scherlis; Kshitij Sachan; Adam S. Jermyn; Joe Benton; Buck Shlegeris (CoRR, 2022)

From Denoising Diffusions to Denoising Markov Models. - Joe Benton; Yuyang Shi 002; Valentin De Bortoli; George Deligiannidis; Arnaud Doucet (CoRR, 2022)

Linear Convergence Bounds for Diffusion Models via Stochastic Localization. - Joe Benton; Valentin De Bortoli; Arnaud Doucet; George Deligiannidis (CoRR, 2023)

Measuring Feature Sparsity in Language Models. - Mingyang Deng; Lucas Tao; Joe Benton (CoRR, 2023)

Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics. - Kamélia Daudel; Joe Benton; Yuyang Shi 002; Arnaud Doucet (J. Mach. Learn. Res., 2023)

Nearly d-Linear Convergence Bounds for Diffusion Models via Stochastic Localization. - Joe Benton; Valentin De Bortoli; Arnaud Doucet; George Deligiannidis (ICLR, 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; et al. (NeurIPS, 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; et al. (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; et al. (CoRR, 2024)

Error Bounds for Flow Matching Methods. - Joe Benton; George Deligiannidis; Arnaud Doucet (Trans. Mach. Learn. Res., 2024)

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; et al. (ICLR, 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; et al. (CoRR, 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; et al. (CoRR, 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, 2025)

Teaching Models to Verbalize Reward Hacking in Chain-of-Thought Reasoning. - Miles Turpin; Andy Arditi; Marvin Li; Joe Benton; Julian Michael (CoRR, 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 003; Alan Cooney; Allan Dafoe; Anca D. Dragan; Scott Emmons; Owain Evans; et al. (CoRR, 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; et al. (CoRR, 2025)