Semantic Segmentation of Histopathological Slides for the Classification of Cutaneous Lymphoma and Eczema. - Jérémy Scheurer; Claudio Ferrari; Luis Berenguer Todo Bom; Michaela Beer; Werner Kempf; Luis Haug (MIUA, 2020)

Instance-wise algorithm configuration with graph neural networks. - Romeo Valentin; Claudio Ferrari; Jérémy Scheurer; Andisheh Amrollahi; Chris Wendler; Max B. Paulus (CoRR, 2022)

Learning from Natural Language Feedback. - Jérémy Scheurer; Jon Ander Campos; Jun Shern Chan; Angelica Chen; Kyunghyun Cho; Ethan Perez (CoRR, 2022)

Few-shot Adaptation Works with UnpredicTable Data. - Jun Shern Chan; Michael Pieler; Jonathan Jao; Jérémy Scheurer; Ethan Perez (ACL (1), 2023)

Improving Code Generation by Training with Natural Language Feedback. - Angelica Chen; Jérémy Scheurer; Tomasz Korbak; Jon Ander Campos; Jun Shern Chan; Samuel R. Bowman; Kyunghyun Cho; Ethan Perez (CoRR, 2023)

Training Language Models with Language Feedback at Scale. - Jérémy Scheurer; Jon Ander Campos; Tomasz Korbak; Jun Shern Chan; Angelica Chen; Kyunghyun Cho; Ethan Perez (CoRR, 2023)

Technical Report: Large Language Models can Strategically Deceive their Users when Put Under Pressure. - Jérémy Scheurer; Mikita Balesni; Marius Hobbhahn (CoRR, 2023)

Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback. - Stephen Casper; Xander Davies; Claudia Shi; Thomas Krendl Gilbert; Jérémy Scheurer; Javier Rando; Rachel Freedman; Tomasz Korbak; David Lindner; Pedro Freire; Tony Tong Wang; Samuel Marks; et al. (Trans. Mach. Learn. Res., 2023)

Black-Box Access is Insufficient for Rigorous AI Audits. - Stephen Casper; Carson Ezell; Charlotte Siegmann; Noam Kolt; Taylor Lynn Curtis; Benjamin Bucknall; Andreas A. Haupt; Kevin Wei; Jérémy Scheurer; Marius Hobbhahn; Lee Sharkey; Satyapriya Krishna; et al. (FAccT, 2024)

Me, Myself, and AI: The Situational Awareness Dataset (SAD) for LLMs. - Rudolf Laine; Bilal Chughtai; Jan Betley; Kaivalya Hariharan; Mikita Balesni; Jérémy Scheurer; Marius Hobbhahn; Alexander Meinke; Owain Evans (NeurIPS, 2024)

TracrBench: Generating Interpretability Testbeds with Large Language Models. - Hannes Thurnherr; Jérémy Scheurer (CoRR, 2024)

Analyzing Probabilistic Methods for Evaluating Agent Capabilities. - Axel Højmark; Govind Pimpale; Arjun Panickssery; Marius Hobbhahn; Jérémy Scheurer (CoRR, 2024)

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)

Learning from Natural Language Feedback. - Angelica Chen; Jérémy Scheurer; Jon Ander Campos; Tomasz Korbak; Jun Shern Chan; Samuel R. Bowman; Kyunghyun Cho; Ethan Perez (Trans. Mach. Learn. Res., 2024)

Forecasting Frontier Language Model Agent Capabilities. - Govind Pimpale; Axel Højmark; Jérémy Scheurer; Marius Hobbhahn (CoRR, 2025)