13 papers
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…
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…
MME-Emotion: A Holistic Evaluation Benchmark for Emotional Intelligence in Multimodal Large Language Models
Fan Zhang, Zebang Cheng, Chong Deng +18
Recent advances in multimodal large language models (MLLMs) have catalyzed transformative progress in affective computing, enabling models to exhibit emergent emotional intelligenc…
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…