23 citations · 47 across the 24 of their papers we have counts for
8 papers · 1 filter
OneEmo: A Unified Multimodal Reasoning Model for Emotion Perception, Understanding, and Interaction
Jiahao Huang, Zheng Lian, Jingyi Zhang +3
Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in emotional intelligence. However, prevailing research predominantly focuses on task-specific sp…
Robust Speech Emotion Recognition under Tone-Word Conflict: A Benchmark and Framework
Xiaojiang Peng, Dawei Huang, Yongjie Lv +5
Speech emotion recognition (SER) is a crucial component of human-computer interaction, attracting extensive attention from both industry and academia. However, existing SER systems…
AffectSim: A Controllable Interactive 3D Simulation Benchmark for Embodied Affective Perception
Ke Xing, Zhilong Wang, Zheng Lian +8
Existing affective benchmarks largely rely on fixed recordings, where observation conditions are predetermined before inference. Consequently, they mainly evaluate passive affect r…
HiMA-MDD: A Hierarchical Multi-Agent Harness for Interpretable Multimodal Depression Detection in Clinical Interviews
Ao Chen, Xiaojiang Peng
Depression assessment from multimodal clinical interviews requires integrating dispersed evidence from multiple symptoms into a coherent PHQ-8 profile. This process is hierarchical…
What Can I Edit? Open-Ended Strategy Discovery and the Emotion Editability Landscape
Qing Li, Zeyu Dong, Yin Cui +2
Emotional image editing requires more than applying affective filters or modifying predefined visual factors: an effective edit must identify what a particular image can afford for…
AffectVerse: Emotional World Models for Multimodal Affective Computing
Bo Zhao, Fanghua Ye, Yixin Ji +3
Humans infer emotions by integrating observed multimodal cues with expectations about how affective states may unfold. Existing multimodal large language models (MLLMs), however, o…
Emotion-LLaMAv2 and MMEVerse: A New Framework and Benchmark for Multimodal Emotion Understanding
Xiaojiang Peng, Jingyi Chen, Zebang Cheng +11
Understanding human emotions from multimodal signals poses a significant challenge in affective computing and human-robot interaction. While multimodal large language models (MLLMs…
When Tone and Words Disagree: Towards Robust Speech Emotion Recognition under Acoustic-Semantic Conflict
Dawei Huang, Yongjie Lv, Ruijie Xiong +2
Speech Emotion Recognition (SER) systems often assume congruence between vocal emotion and lexical semantics. However, in real-world interactions, acoustic-semantic conflict is com…