Hallucinated captions systematically improve VLM accuracy on vision-language tasks across nine models and nine datasets, with gains linked to broadened semantic coverage and modulated reasoning entropy.
In: Proceedings of the IEEE/CVF International Conference on Computer Vision
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HIVE: Understanding Post-Hallucination Reasoning in Vision Language Models
Hallucinated captions systematically improve VLM accuracy on vision-language tasks across nine models and nine datasets, with gains linked to broadened semantic coverage and modulated reasoning entropy.