7 papers
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…
MER 2026: From Discriminative Emotion Recognition to Generative Emotion Understanding
Zheng Lian, Xiaojiang Peng, Kele Xu +15
MER2026 marks the fourth edition of the MER series of challenges. The MER series provides valuable data resources to the research community and offers tasks centered on recent rese…
EmoBench-M: Benchmarking Emotional Intelligence for Multimodal Large Language Models
He Hu, Lianzhong You, Hongbo Xu +7
With the integration of multimodal large language models (MLLMs) into robotic systems and AI applications, embedding emotional intelligence (EI) capabilities is essential for enabl…
EmoTrans: A Benchmark for Understanding, Reasoning, and Predicting Emotion Transitions in Multimodal LLMs
He Hu, Tengjin Weng, Zebang Cheng +5
Recent multimodal large language models (MLLMs) have shown strong capabilities in perception, reasoning, and generation, and are increasingly used in applications such as social ro…
TheraMind: A Strategic and Adaptive Agent for Longitudinal Psychological Counseling
He Hu, Chiyuan Ma, Qianning Wang +5
The shortage of mental health professionals has driven the web to become a primary avenue for accessible psychological support. While Large Language Models (LLMs) offer promise for…
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…