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)

Scalable and Transferable Black-Box Jailbreaks for Language Models via Persona Modulation. - Rusheb Shah; Quentin Feuillade-Montixi; Soroush Pour; Arush Tagade; Stephen Casper; Javier Rando (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)

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; et al. (CoRR, 2024)

Frontier Models are Capable of In-context Scheming. - Alexander Meinke; Bronson Schoen; Jérémy Scheurer; Mikita Balesni; Rusheb Shah; Marius Hobbhahn (CoRR, 2024)