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The results show that affective perception depends not only on the observed behavior, but also on how evidence is acquired, and by making observation acquisition experimentally controllable, AffectSim provides a foundation for studying embodied affective perception in interactive 3D environments.
HiMA-MDD is introduced, a hierarchical multi-agent harness that aligns this assessment hierarchy with three agent layers and naturally yields a Hierarchical Evidence Trace that preserves all intermediate evidence, judgments, and revisions for auditability.
This paper introduces OneEmo, a unified affective generalist capable of mastering emotion perception, comprehension, and interaction, and proposes Emo-Chord, a novel reinforcement learning strategy that stabilizes optimization through unified multi-task reward allocation.
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