Kaufmann, Timo

7 publications

TMLR 2025 A Survey of Reinforcement Learning from Human Feedback Timo Kaufmann, Paul Weng, Viktor Bengs, Eyke Hüllermeier

ICML 2025 Comparing Comparisons: Informative and Easy Human Feedback with Distinguishability Queries Xuening Feng, Zhaohui Jiang, Timo Kaufmann, Eyke Hüllermeier, Paul Weng, Yifei Zhu

AAAI 2025 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

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

NeurIPS 2025 ResponseRank: Data-Efficient Reward Modeling Through Preference Strength Learning Timo Kaufmann, Yannick Metz, Daniel A. Keim, Eyke Hüllermeier

ICMLW 2024 Comparing Comparisons: Informative and Easy Human Feedback with Distinguishability Queries Xuening Feng, Zhaohui Jiang, Timo Kaufmann, Eyke Hüllermeier, Paul Weng, Yifei Zhu

ICMLW 2024 Relatively Rational: Learning Utilities and Rationalities Jointly from Pairwise Preferences Taku Yamagata, Tobias Oberkofler, Timo Kaufmann, Viktor Bengs, Eyke Hüllermeier, Raul Santos-Rodriguez