6 papers
Diagnosing Corruption-Induced Reliability Failures in Vision-Language Models
Xiangjie Sui, Songyang Li, Hanwei Zhu +3
Visual corruptions can change vision--language model (VLM) behavior in ways that top-1 accuracy does not capture. A model may keep the same answer while losing distributional suppo…
Disentangling Bias by Modeling Intra- and Inter-modal Causal Attention for Multimodal Sentiment Analysis
Menghua Jiang, Yuxia Lin, Baoliang Chen +3
Multimodal sentiment analysis (MSA) aims to understand human emotions by integrating information from multiple modalities, such as text, audio, and visual data. However, existing m…
EduVQA: Towards Concept-Aware Assessment of Educational AI-Generated Videos
Baoliang Chen, Xinlong Bu, Hanwei Zhu +2
Existing AI-generated video quality assessment (AIGVQA) methods mainly focus on global perceptual realism and coarse text-video alignment, while overlooking a critical requirement…
Beyond Cosine Similarity: Magnitude-Aware CLIP for No-Reference Image Quality Assessment
Zhicheng Liao, Dongxu Wu, Zhenshan Shi +5
Recent efforts have repurposed the Contrastive Language-Image Pre-training (CLIP) model for No-Reference Image Quality Assessment (NR-IQA) by measuring the cosine similarity betwee…
Simple Lines, Big Ideas: Towards Interpretable Assessment of Human Creativity from Drawings
Zihao Lin, Zhenshan Shi, Sasa Zhao +4
Assessing human creativity through visual outputs, such as drawings, plays a critical role in fields including psychology, education, and cognitive science. However, current assess…
Q-Doc: Benchmarking Document Image Quality Assessment Capabilities in Multi-modal Large Language Models
Jiaxi Huang, Dongxu Wu, Hanwei Zhu +4
The rapid advancement of Multi-modal Large Language Models (MLLMs) has expanded their capabilities beyond high-level vision tasks. Nevertheless, their potential for Document Image…