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cs.LG2026
Evolving Safety Landscape of Multi-modal Large Language Models: A Survey of Emerging Threats and Safeguards
Xi Li, Shu Zhao, Xiaohan Zou +6
Multi-modal large language models (MLLMs) integrate heterogeneous modalities through modality alignment and fusion, enabling stronger understanding and reasoning. However, this arc…
cs.AI2026
When Vision-Language Models Judge Without Seeing: Exposing Informativeness Bias
Xiaohan Zou, Roshan Sridhar, Mohammadtaher Safarzadeh +1
The reliability of VLM-as-a-Judge is critical for the automatic evaluation of vision-language models (VLMs). Despite recent progress, our analysis reveals that VLM-as-a-Judge often…
cs.AI2026
CARV: A Diagnostic Benchmark for Compositional Analogical Reasoning in Multimodal LLMs
Yongkang Du, Xiaohan Zou, Minhao Cheng +1
Analogical reasoning tests a fundamental aspect of human cognition: mapping the relation from one pair of objects to another. Existing evaluations of this ability in multimodal lar…