3 citations · 5 across the 9 of their papers we have counts for
10 papers
HUG-VIS: A Multimodal Benchmark for Human-centered Understanding and Generation in Visual Intelligence
Fei Ma, Zebang Cheng, Minghui Li +11
Visual intelligence seeks to perceive, interpret, and synthesize the visual world and is central to modern computer vision. Human-centered visual intelligence is especially demandi…
MOPDA: Mixed-Trajectory On-Policy Distillation for Language-Guided Industrial Anomaly Detection
Shuimu Chen, Jing Jin, Nan Su +5
Large vision-language models (LVLMs) have shown strong potential for industrial anomaly detection (IAD) by providing image-level anomaly judgments and interpretable reasoning. Howe…
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…
Reflect-R1: Evidence-Driven Reflection for Self-Correction in Long Video Understanding
Shuimu Chen, Yuteng Chen, Yuanshen Guan +7
Current multimodal reflection mechanisms for long video understanding predominantly rely on closed-loop self-reflection within internal parameters. Lacking objective external evide…
MER 2026: From Discriminative Emotion Recognition to Generative Emotion Understanding
Zheng Lian, Xiaojiang Peng, Kele Xu +16
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…
A Principle-Driven Adaptive Policy for Group Cognitive Stimulation Dialogue for Elderly with Cognitive Impairment
Jiyue Jiang, Yanyu Chen, Pengan Chen +7
Cognitive impairment is becoming a major public health challenge. Cognitive Stimulation Therapy (CST) is an effective intervention for cognitive impairment, but traditional methods…
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…
Beyond Empathy: Integrating Diagnostic and Therapeutic Reasoning with Large Language Models for Mental Health Counseling
He Hu, Yucheng Zhou, Juzheng Si +6
Large language models (LLMs) hold significant potential for mental health support, capable of generating empathetic responses and simulating therapeutic conversations. However, exi…
Exploring Embodied Multimodal Large Models: Development, Datasets, and Future Directions
Shoubin Chen, Zehao Wu, Kai Zhang +5
Embodied multimodal large models (EMLMs) have gained significant attention in recent years due to their potential to bridge the gap between perception, cognition, and action in com…
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…