Cover Image

V-DPO: Mitigating Hallucination in Large Vision Language Models via Vision-Guided Direct Preference Optimization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xie, Yuxi, Li, Guanzhen, Xu, Xiao, Kan, Min-Yen
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

MVP-Bench: Can Large Vision--Language Models Conduct Multi-level Visual Perception Like Humans?
by: Li, Guanzhen, et al.
Published: (2024)

Mitigating Hallucinations in Large Vision-Language Models via Entity-Centric Multimodal Preference Optimization
by: Wu, Jiulong, et al.
Published: (2025)

MIA-DPO: Multi-Image Augmented Direct Preference Optimization For Large Vision-Language Models
by: Liu, Ziyu, et al.
Published: (2024)

Mitigating Hallucination in Multimodal Large Language Model via Hallucination-targeted Direct Preference Optimization
by: Fu, Yuhan, et al.
Published: (2024)

Mitigating Hallucinations in Large Vision-Language Models via Summary-Guided Decoding
by: Min, Kyungmin, et al.
Published: (2024)

Mitigating Hallucinations in Large Vision-Language Models via DPO: On-Policy Data Hold the Key
by: Yang, Zhihe, et al.
Published: (2025)

VL-DPO: Vision-Language-Guided Finetuning for Preference-Aligned Autonomous Driving
by: Xu, Zhefan, et al.
Published: (2026)

Mitigating Object Hallucinations in Large Vision-Language Models via Attention Calibration
by: Zhu, Younan, et al.
Published: (2025)

Mitigating Multilingual Hallucination in Large Vision-Language Models
by: Qu, Xiaoye, et al.
Published: (2024)

CLIP-DPO: Vision-Language Models as a Source of Preference for Fixing Hallucinations in LVLMs
by: Ouali, Yassine, et al.
Published: (2024)

MedHEval: Benchmarking Hallucinations and Mitigation Strategies in Medical Large Vision-Language Models
by: Chang, Aofei, et al.
Published: (2025)

Prefill-Time Intervention for Mitigating Hallucination in Large Vision-Language Models
by: Zhang, Chengsheng, et al.
Published: (2026)

Mitigating Entangled Steering in Large Vision-Language Models for Hallucination Reduction
by: Zhang, Yuanhong, et al.
Published: (2026)

Retrieval Visual Contrastive Decoding to Mitigate Object Hallucinations in Large Vision-Language Models
by: Lee, Jihoon, et al.
Published: (2025)

Residual Decoding: Mitigating Hallucinations in Large Vision-Language Models via History-Aware Residual Guidance
by: Chen, Xinrong, et al.
Published: (2026)

Investigating and Mitigating the Multimodal Hallucination Snowballing in Large Vision-Language Models
by: Zhong, Weihong, et al.
Published: (2024)

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling
by: Dong, Xin, et al.
Published: (2025)

Dynamic Multimodal Activation Steering for Hallucination Mitigation in Large Vision-Language Models
by: Yin, Jianghao, et al.
Published: (2026)

Prescribing the Right Remedy: Mitigating Hallucinations in Large Vision-Language Models via Targeted Instruction Tuning
by: Hu, Rui, et al.
Published: (2024)

SDCD: Structure-Disrupted Contrastive Decoding for Mitigating Hallucinations in Large Vision-Language Models
by: Xia, Yuxuan, et al.
Published: (2026)

MAP: Mitigating Hallucinations in Large Vision-Language Models with Map-Level Attention Processing
by: Li, Chenxi, et al.
Published: (2025)

Mitigating Hallucinations via Inter-Layer Consistency Aggregation in Large Vision-Language Models
by: Tang, Kai, et al.
Published: (2025)

Seeing is Believing: Mitigating Hallucination in Large Vision-Language Models via CLIP-Guided Decoding
by: Deng, Ailin, et al.
Published: (2024)

Mitigating Hallucinations in Large Vision-Language Models (LVLMs) via Language-Contrastive Decoding (LCD)
by: Manevich, Avshalom, et al.
Published: (2024)

S2H-DPO: Hardness-Aware Preference Optimization for Vision-Language Models
by: Shukla, Nitish, et al.
Published: (2026)

VEGAS: Mitigating Hallucinations in Large Vision-Language Models via Vision-Encoder Attention Guided Adaptive Steering
by: Wang, Zihu, et al.
Published: (2025)

Adaptive Residual-Update Steering for Low-Overhead Hallucination Mitigation in Large Vision Language Models
by: Zou, Zhengtao, et al.
Published: (2025)

mDPO: Conditional Preference Optimization for Multimodal Large Language Models
by: Wang, Fei, et al.
Published: (2024)

Investigating and Mitigating Object Hallucinations in Pretrained Vision-Language (CLIP) Models
by: Liu, Yufang, et al.
Published: (2024)

Mitigating Hallucinations in Large Vision-Language Models with Instruction Contrastive Decoding
by: Wang, Xintong, et al.
Published: (2024)

Detecting and Mitigating Hallucination in Large Vision Language Models via Fine-Grained AI Feedback
by: Xiao, Wenyi, et al.
Published: (2024)

Delve into Visual Contrastive Decoding for Hallucination Mitigation of Large Vision-Language Models
by: Lee, Yi-Lun, et al.
Published: (2024)

AdPO: Enhancing the Adversarial Robustness of Large Vision-Language Models with Preference Optimization
by: Liu, Chaohu, et al.
Published: (2025)

Reducing Hallucination in Vision-Language Models via Stage-wise Preference Optimization under Distribution Shift
by: Xu, Qinwu
Published: (2026)

Review of Hallucination Understanding in Large Language and Vision Models
by: Ho, Zhengyi, et al.
Published: (2025)

Mitigating Object Hallucinations in Vision-Language Models through Region-Aware Attention Recalibration
by: Xu, Yuanzhi, et al.
Published: (2026)

Image Tokens Matter: Mitigating Hallucination in Discrete Tokenizer-based Large Vision-Language Models via Latent Editing
by: Wang, Weixing, et al.
Published: (2025)

When Text Hijacks Vision: Benchmarking and Mitigating Text Overlay-Induced Hallucination in Vision Language Models
by: Yakun, Cui, et al.
Published: (2026)

VIB-Probe: Detecting and Mitigating Hallucinations in Vision-Language Models via Variational Information Bottleneck
by: Zhang, Feiran, et al.
Published: (2026)

InpaintDPO: Mitigating Spatial Relationship Hallucinations in Foreground-conditioned Inpainting via Diverse Preference Optimization
by: Li, Qirui, et al.
Published: (2025)