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        <title>Retrieval Visual Contrastive Decoding to Mitigate Object Hallucinations in Large Vision-Language Models</title>
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    <abstract>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.</abstract>
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%0 Conference Proceedings
%T Retrieval Visual Contrastive Decoding to Mitigate Object Hallucinations in Large Vision-Language Models
%A Lee, Jihoon
%A Song, Min
%Y Che, Wanxiang
%Y Nabende, Joyce
%Y Shutova, Ekaterina
%Y Pilehvar, Mohammad Taher
%S Findings of the Association for Computational Linguistics: ACL 2025
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-256-5
%F lee-song-2025-retrieval
%X 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.
%R 10.18653/v1/2025.findings-acl.430
%U https://aclanthology.org/2025.findings-acl.430/
%U https://doi.org/10.18653/v1/2025.findings-acl.430
%P 8200-8219

Markdown (Informal)

[Retrieval Visual Contrastive Decoding to Mitigate Object Hallucinations in Large Vision-Language Models](https://aclanthology.org/2025.findings-acl.430/) (Lee & Song, Findings 2025)

• Retrieval Visual Contrastive Decoding to Mitigate Object Hallucinations in Large Vision-Language Models (Lee & Song, Findings 2025)

ACL

• Jihoon Lee and Min Song. 2025. Retrieval Visual Contrastive Decoding to Mitigate Object Hallucinations in Large Vision-Language Models. In Findings of the Association for Computational Linguistics: ACL 2025, pages 8200–8219, Vienna, Austria. Association for Computational Linguistics.