3 papers
cs.CV2026
Emo-Bench: A Scalable Benchmark for Multimodal Evoked and Expressed Emotion Understanding via Bayesian Pairwise Alignment
Lancheng Gao, Ziheng Jia, Shengyan Li +4
Understanding both expressed and evoked emotions is critical for multimodal large language models (MLLMs) to achieve comprehensive affect-aware interactions. However, existing benc…
cs.AI2026
RAVEN-Eval: Rubric-Guided Automatic Evaluation for AI Video Generation Models Based on LMM Preference Judgement
Ziheng Jia, Jiaying Qian, Zicheng Zhang +3
AI video generation has advanced rapidly and entered widespread commercial use. As a result, quality differences among videos produced by state-of-the-art AI video generation model…
cs.MM2025
EEmo-Bench: A Benchmark for Multi-modal Large Language Models on Image Evoked Emotion Assessment
Lancheng Gao, Ziheng Jia, Yunhao Zeng +5
The furnishing of multi-modal large language models (MLLMs) has led to the emergence of numerous benchmark studies, particularly those evaluating their perception and understanding…