3 papers
cs.CL2026
Where Do Models Find Happiness? Emotion Vectors in Open-Source LLMs
Sinie van der Ben, Raphaël Baur, Yannick Metz +1
Recent work identified emotion vectors in Claude Sonnet 4.5, which are internal representations that encode emotion concepts, causally influence behavior, and exhibit geometry mirr…
cs.LG2025
Reward Learning from Multiple Feedback Types
Yannick Metz, András Geiszl, Raphaël Baur +1
Learning rewards from preference feedback has become an important tool in the alignment of agentic models. Preference-based feedback, often implemented as a binary comparison betwe…
cs.LG2024
Mapping out the Space of Human Feedback for Reinforcement Learning: A Conceptual Framework
Yannick Metz, David Lindner, Raphaël Baur +1
Reinforcement Learning from Human feedback (RLHF) has become a powerful tool to fine-tune or train agentic machine learning models. Similar to how humans interact in social context…