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Affective computing has progressed from categorical emotion recognition to open-ended affective analysis with large multimodal models. Yet affective science describes emotion as an unfolding process shaped by appraisal, regulation, and social interpretation, which remains underexplored computationally. We propose TRACE...
It is argued that accurate citation requires a shift from similarity-based search to active, claim-level reasoning, and proposed ReCite, a decoupled agentic framework that orchestrates location perception, intent-aware query planning, and reflective verification.
This paper introduces Implicit Social Context Analysis (MoCA), a novel task that systematically models implicit social scenarios along three key dimensions: affection, intent, and stance, and proposes Conflict-Driven Abductive Reasoning (CoDAR), a novel framework that models the discrepancy between observed expressions...
OmniScientist is introduced, an end-to-end, omni-modal AI scientist that conducts multidisciplinary research directly from heterogeneous raw evidence and demonstrates that lifecycle-wide perception is essential for evidence-grounded scientific discovery and provides a practical path toward broadly capable AI scientists...
IBA-Bench is introduced, a benchmark for implicit behavioral alignment constructed from longitudinal interaction histories that contain noise, implicit cues, and temporal inconsistencies, and the proposed IBA-Agent is proposed, an agent framework that reconciles conflicting priorities through broad retrieval and trajec...
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