On the Challenges and Practices of Reinforcement Learning from Real Human Feedback. - Timo Kaufmann; Sarah Ball; Jacob Beck; Eyke Hüllermeier; Frauke Kreuter (PKDD/ECML Workshops (2), 2023)

OCALM: Object-Centric Assessment with Language Models. - Timo Kaufmann; Jannis Blüml; Antonia Wüst; Quentin Delfosse; Kristian Kersting; Eyke Hüllermeier (CoRR, 2024)

Problem Solving Through Human-AI Preference-Based Cooperation. - Subhabrata Dutta; Timo Kaufmann; Goran Glavas; Ivan Habernal; Kristian Kersting; Frauke Kreuter; Mira Mezini; Iryna Gurevych; Eyke Hüllermeier; Hinrich Schütze (CoRR, 2024)

DUO: Diverse, Uncertain, On-Policy Query Generation and Selection for Reinforcement Learning from Human Feedback. - Xuening Feng; Zhaohui Jiang; Timo Kaufmann; Puchen Xu; Eyke Hüllermeier; Paul Weng; Yifei Zhu (AAAI, 2025)

Inverse Constitutional AI: Compressing Preferences into Principles. - Arduin Findeis; Timo Kaufmann; Eyke Hüllermeier; Samuel Albanie; Robert D. Mullins (ICLR, 2025)

A Survey of Reinforcement Learning from Human Feedback. - Timo Kaufmann; Paul Weng; Viktor Bengs; Eyke Hüllermeier (Trans. Mach. Learn. Res., 2025)