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Timo Kaufmann

PhD student, Ludwig-Maximilians-Universität München

1 paper at NeurIPS 2025

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Poster Session 4

Thursday, December 4, 2025 · 4:30 PM → 7:30 PM

Exhibit Hall C,D,E

ResponseRank: Data-Efficient Reward Modeling through Preference Strength Learning

#405 · Timo Kaufmann, Yannick Metz, Daniel A. Keim, Eyke Hüllermeier

ResponseRank enables data-efficient learning of distance-aware reward models through stratified comparison strength rankings.