Linearly Structured World Representations in Maze-Solving Transformers. - Michael I. Ivanitskiy; Alex F. Spies; Tilman Räuker; Guillaume Corlouer; Chris Mathwin; Lucia Quirke; Can Rager; Rusheb Shah; Dan Valentine; Cecilia G. Diniz Behn; Katsumi Inoue; Samy Wu Fung (UniReps, 2023)

A Configurable Library for Generating and Manipulating Maze Datasets. - Michael Igorevich Ivanitskiy; Rusheb Shah; Alex F. Spies; Tilman Räuker; Dan Valentine; Can Rager; Lucia Quirke; Chris Mathwin; Guillaume Corlouer; Cecilia G. Diniz Behn; Samy Wu Fung (CoRR, 2023)

Structured World Representations in Maze-Solving Transformers. - Michael I. Ivanitskiy; Alex F. Spies; Tilman Räuker; Guillaume Corlouer; Chris Mathwin; Lucia Quirke; Can Rager; Rusheb Shah; Dan Valentine; Cecilia G. Diniz Behn; Katsumi Inoue; Samy Wu Fung (CoRR, 2023)

Debating with More Persuasive LLMs Leads to More Truthful Answers. - Akbir Khan; John Hughes; Dan Valentine; Laura Ruis; Kshitij Sachan; Ansh Radhakrishnan; Edward Grefenstette; Samuel R. Bowman; Tim Rocktäschel; Ethan Perez (ICML, 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)

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)