SegSub: Evaluating Robustness to Knowledge Conflicts and Hallucinations in Vision-Language Models
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https://figshare.com/articles/dataset/SegSub_Enhancing_Robustness_in_Vision-Language_Models_with_Knowledge_Conflicts_and_Counterfactual_Image_Augmentation/28297076
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This research introduces \segsub, a framework for applying targeted image perturbations to investigate VLM resilience against knowledge conflicts. Our analysis reveals distinct vulnerability patterns: while VLMs are robust to parametric conflicts (20% adherence rates), they exhibit significant weaknesses in identifying counterfactual conditions (
创建时间：
2025-01-28
