[2604.06562] On Emotion-Sensitive Decision Making of Small Language Model Agents

Computer Science > Artificial Intelligence arXiv:2604.06562 (cs) [Submitted on 8 Apr 2026] Title:On Emotion-Sensitive Decision Making of Small Language Model Agents Authors:Jiaju Lin, Xingjian Du, Qingyun Wu, Ellen Wenting Zou, Jindong Wang View a PDF of the paper titled On Emotion-Sensitive Decision Making of Small Language Model Agents, by Jiaju Lin and 4 other authors View PDF HTML (experimental) Abstract: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 introduce a benchmark built around canonical decision templates that span cooperative and competitive incentives under both complete and incomplete information. These templates are instantiated using strategic scenarios from \textsc{Diplomacy}, \textsc{StarCraft II}, and diverse real-world personas. Experiments across multiple model families in various architecture and modalities, show that emotional perturbations systematically affect strategic choices, but the resulting behaviors are often unstable and not fully aligned with human expectations. Fina...