AI RESEARCH
On Emotion-Sensitive Decision Making of Small Language Model Agents
arXiv CS.AI
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ArXi:2604.06562v1 Announce Type: new Small language models (SLM) are increasingly used as interactive decision-making agents, yet most decision-oriented evaluations ignore emotion as a causal factor influencing behavior. We study emotion-sensitive decision making by combining representation-level emotion induction with a structured game-theoretic evaluation. Emotional states are induced using activation steering derived from crowd-validated, real-world emotion-eliciting texts, enabling controlled and transferable interventions beyond prompt-based methods. We.