AI RESEARCH
When Relations Break: Analyzing Relation Hallucination in Vision-Language Model Under Rotation and Noise
arXiv CS.CL
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ArXi:2605.05045v1 Announce Type: cross Vision-language models (VLMs) achieve strong multimodal performance but remain prone to relation hallucination, which requires accurate reasoning over inter-object interactions. We study the impact of visual perturbations, specifically rotation and noise, and show that even mild distortions significantly degrade relational reasoning across models and datasets.