Retrieval Visual Contrastive Decoding to Mitigate Object Hallucinations in Large Vision-Language Models
Despite significant advancements in LargeVision-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.Code and data are released at https: //github.com/JiHoonLee9898/RVCD.
Authors
- Ji‐Hoon Lee (ORCID: https://orcid.org/0000-0001-7387-935X)
- Minho Song (ORCID: https://orcid.org/0000-0002-4515-5212)
Publication Details
- Published
- 2025-01-01
- DOI
- https://doi.org/10.18653/v1/2025.findings-acl.430
- Citations
- 1
- Primary Topic
- Epilepsy research and treatment
- Type
- article
- Field-Weighted Citation Impact
- 1.47
Funders
- Yonsei University
- Ministry of Culture, Sports and Tourism
- Korea Creative Content Agency
- Ministry of Science and ICT, South Korea
- Institute for Information and Communications Technology Promotion