#hallucination-mitigation2 articles

2 articles

AIBullisharXiv – CS AI · 5h ago1

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Through the Lens of Contrast: Self-Improving Visual Reasoning in VLMs

Researchers introduce VC-STaR, a new framework that improves visual reasoning in vision-language models by using contrastive image pairs to reduce hallucinations. The approach creates VisCoR-55K, a new dataset that outperforms existing visual reasoning methods when used for model fine-tuning.

AIBullisharXiv – CS AI · 5h ago0

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Self-Aug: Query and Entropy Adaptive Decoding for Large Vision-Language Models

Researchers developed a new training-free decoding strategy for Large Vision-Language Models that reduces hallucinations by using query-adaptive visual augmentation and entropy-based token selection. The method showed significant improvements in factual consistency across four LVLMs and seven benchmarks compared to existing approaches.