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RITUAL: Random Image Transformations as a Universal Anti-hallucination Lever in Large Vision Language Models
By integrating the probability distributions from both the original and transformed images, RITUAL effectively reduces hallucinations.
Don't Miss the Forest for the Trees: Attentional Vision Calibration for Large Vision Language Models
This study addresses the issue observed in Large Vision Language Models (LVLMs), where excessive attention on a few image tokens, referred to as blind tokens, leads to hallucinatory responses in tasks requiring fine-grained understanding of visual objects.
Towards Robust Multimodal Prompting With Missing Modalities
Recently, multimodal prompting, which introduces learnable missing-aware prompts for all missing modality cases, has exhibited impressive performance.
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