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Retrieval Visual Contrastive Decoding to Mitigate Object Hallucinations in Large Vision-Language Models

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Despite significant advancements in Large Vision-Language Models, Object Hallucination (OH) remains a persistent challenge. Building upon prior studies on contrastive decoding that address this issue without requiring additional model training, we introduce RVCD (Retrieval Visual Contrastive Decoding), an advanced method to suppress OH. RVCD leverages both negative and positive images at the logit level, explicitly referencing AI-generated images designed to represent a single concept. Our approach demonstrates substantial improvements over existing decoding-based methods.

Jihoon Lee, Min Song• 2025

Related benchmarks

TaskDatasetResultRank
Visual Hallucination EvaluationPOPE MS-COCO Adversarial sampling (val)
Accuracy85.48
39
Object Hallucination EvaluationMSCOCO
Accuracy88.54
21
Image CaptioningMSCOCO (random sampling of 500 instances)
CHAIRs11.32
21
Vision-Language EvaluationMME Leaderboard (full)
Existence Score130
18
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