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cs.CV2026
OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing
Zebang Cheng, Shuimu Chen, Boxue Yang +7
Reinforcement learning for multimodal large language models (MLLMs) is often hindered by severe reward sparsity in complex reasoning tasks. This challenge is particularly pronounce…
cs.CV2026
AffectAgent: Collaborative Multi-Agent Reasoning for Retrieval-Augmented Multimodal Emotion Recognition
Zeheng Wang, Zitong Yu, Yijie Zhu +9
LLM-based multimodal emotion recognition relies on static parametric memory and often hallucinates when interpreting nuanced affective states. In this paper, given that single-roun…
cs.CV2026
Nüwa: Mending the Spatial Integrity Torn by VLM Token Pruning
Yihong Huang, Fei Ma, Yihua Shao +4
Vision token pruning has proven to be an effective acceleration technique for the efficient Vision Language Model (VLM). However, existing pruning methods demonstrate excellent per…