Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting. - Miles Turpin; Julian Michael; Ethan Perez; Samuel R. Bowman (NeurIPS, 2023)

Bias-Augmented Consistency Training Reduces Biased Reasoning in Chain-of-Thought. - James Chua; Edward Rees; Hunar Batra; Samuel R. Bowman; Julian Michael; Ethan Perez; Miles Turpin (CoRR, 2024)

Foundational Challenges in Assuring Alignment and Safety of Large Language Models. - Usman Anwar; Abulhair Saparov; Javier Rando; Daniel Paleka; Miles Turpin; Peter Hase; Ekdeep Singh Lubana; Erik Jenner; Stephen Casper; Oliver Sourbut; Benjamin L. Edelman; Zhaowei Zhang; et al. (CoRR, 2024)

Looking Inward: Language Models Can Learn About Themselves by Introspection. - Felix J. Binder; James Chua; Tomasz Korbak; Henry Sleight; John Hughes; Robert Long; Ethan Perez; Miles Turpin; Owain Evans (CoRR, 2024)

Foundational Challenges in Assuring Alignment and Safety of Large Language Models. - Usman Anwar; Abulhair Saparov; Javier Rando; Daniel Paleka; Miles Turpin; Peter Hase; Ekdeep Singh Lubana; Erik Jenner; Stephen Casper; Oliver Sourbut; Benjamin L. Edelman; Zhaowei Zhang; et al. (Trans. Mach. Learn. Res., 2024)

Looking Inward: Language Models Can Learn About Themselves by Introspection. - Felix Jedidja Binder; James Chua; Tomek Korbak; Henry Sleight; John Hughes; Robert Long; Ethan Perez; Miles Turpin; Owain Evans (ICLR, 2025)

Teaching Models to Verbalize Reward Hacking in Chain-of-Thought Reasoning. - Miles Turpin; Andy Arditi; Marvin Li; Joe Benton; Julian Michael (CoRR, 2025)