Image de couverture de livre

SDCD: Structure-Disrupted Contrastive Decoding for Mitigating Hallucinations in Large Vision-Language Models

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Xia, Yuxuan, Wang, Siheng, Li, Peng
Format:	Preprint
Publié:	2026
Sujets:	Computer Vision and Pattern Recognition Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Mitigating Hallucinations in Large Vision-Language Models with Instruction Contrastive Decoding
par: Wang, Xintong, et autres
Publié: (2024)

Delve into Visual Contrastive Decoding for Hallucination Mitigation of Large Vision-Language Models
par: Lee, Yi-Lun, et autres
Publié: (2024)

Mitigating Hallucinations in Large Vision-Language Models (LVLMs) via Language-Contrastive Decoding (LCD)
par: Manevich, Avshalom, et autres
Publié: (2024)

Mitigating Hallucinations in Video Large Language Models via Spatiotemporal-Semantic Contrastive Decoding
par: Gao, Yuansheng, et autres
Publié: (2026)

Efficient Contrastive Decoding with Probabilistic Hallucination Detection - Mitigating Hallucinations in Large Vision Language Models -
par: Fieback, Laura, et autres
Publié: (2025)

Retrieval Visual Contrastive Decoding to Mitigate Object Hallucinations in Large Vision-Language Models
par: Lee, Jihoon, et autres
Publié: (2025)

ConVis: Contrastive Decoding with Hallucination Visualization for Mitigating Hallucinations in Multimodal Large Language Models
par: Park, Yeji, et autres
Publié: (2024)

Mitigating Hallucinations in Large Vision-Language Models via Summary-Guided Decoding
par: Min, Kyungmin, et autres
Publié: (2024)

Investigating and Mitigating the Multimodal Hallucination Snowballing in Large Vision-Language Models
par: Zhong, Weihong, et autres
Publié: (2024)

Mixture of Decoding: An Attention-Inspired Adaptive Decoding Strategy to Mitigate Hallucinations in Large Vision-Language Models
par: Chen, Xinlong, et autres
Publié: (2025)

Residual Decoding: Mitigating Hallucinations in Large Vision-Language Models via History-Aware Residual Guidance
par: Chen, Xinrong, et autres
Publié: (2026)

Self-Introspective Decoding: Alleviating Hallucinations for Large Vision-Language Models
par: Huo, Fushuo, et autres
Publié: (2024)

Prefill-Time Intervention for Mitigating Hallucination in Large Vision-Language Models
par: Zhang, Chengsheng, et autres
Publié: (2026)

Mitigating Entangled Steering in Large Vision-Language Models for Hallucination Reduction
par: Zhang, Yuanhong, et autres
Publié: (2026)

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling
par: Dong, Xin, et autres
Publié: (2025)

Mitigating Multilingual Hallucination in Large Vision-Language Models
par: Qu, Xiaoye, et autres
Publié: (2024)

CATCH: Complementary Adaptive Token-level Contrastive Decoding to Mitigate Hallucinations in LVLMs
par: Kan, Zhehan, et autres
Publié: (2024)

SEASON: Mitigating Temporal Hallucination in Video Large Language Models via Self-Diagnostic Contrastive Decoding
par: Wu, Chang-Hsun, et autres
Publié: (2025)

MAP: Mitigating Hallucinations in Large Vision-Language Models with Map-Level Attention Processing
par: Li, Chenxi, et autres
Publié: (2025)

Dynamic Multimodal Activation Steering for Hallucination Mitigation in Large Vision-Language Models
par: Yin, Jianghao, et autres
Publié: (2026)

Mitigating Object Hallucinations in Large Vision-Language Models via Attention Calibration
par: Zhu, Younan, et autres
Publié: (2025)

Octopus: Alleviating Hallucination via Dynamic Contrastive Decoding
par: Suo, Wei, et autres
Publié: (2025)

V-DPO: Mitigating Hallucination in Large Vision Language Models via Vision-Guided Direct Preference Optimization
par: Xie, Yuxi, et autres
Publié: (2024)

Adaptive Residual-Update Steering for Low-Overhead Hallucination Mitigation in Large Vision Language Models
par: Zou, Zhengtao, et autres
Publié: (2025)

MedHEval: Benchmarking Hallucinations and Mitigation Strategies in Medical Large Vision-Language Models
par: Chang, Aofei, et autres
Publié: (2025)

The Mirage of Performance Gains: Why Contrastive Decoding Fails to Mitigate Object Hallucinations in MLLMs?
par: Yin, Hao, et autres
Publié: (2025)

Temporal Insight Enhancement: Mitigating Temporal Hallucination in Multimodal Large Language Models
par: Sun, Li, et autres
Publié: (2024)

Mitigating Object Hallucinations in Large Vision-Language Models with Assembly of Global and Local Attention
par: An, Wenbin, et autres
Publié: (2024)

VEGAS: Mitigating Hallucinations in Large Vision-Language Models via Vision-Encoder Attention Guided Adaptive Steering
par: Wang, Zihu, et autres
Publié: (2025)

Seeing is Believing: Mitigating Hallucination in Large Vision-Language Models via CLIP-Guided Decoding
par: Deng, Ailin, et autres
Publié: (2024)

Learning to Decode Against Compositional Hallucination in Video Multimodal Large Language Models
par: Xing, Wenbin, et autres
Publié: (2026)

Investigating and Mitigating Object Hallucinations in Pretrained Vision-Language (CLIP) Models
par: Liu, Yufang, et autres
Publié: (2024)

CHASD: Language Increment-Calibrated Contrastive Decoding against Hallucination in LVLMs
par: Huang, Xiaoyi, et autres
Publié: (2026)

BIMA: Bijective Maximum Likelihood Learning Approach to Hallucination Prediction and Mitigation in Large Vision-Language Models
par: Tran, Huu-Thien, et autres
Publié: (2025)

Prescribing the Right Remedy: Mitigating Hallucinations in Large Vision-Language Models via Targeted Instruction Tuning
par: Hu, Rui, et autres
Publié: (2024)

CoFi-Dec: Hallucination-Resistant Decoding via Coarse-to-Fine Generative Feedback in Large Vision-Language Models
par: Cao, Zongsheng, et autres
Publié: (2025)

Black-Box Visual Prompt Engineering for Mitigating Object Hallucination in Large Vision Language Models
par: Woo, Sangmin, et autres
Publié: (2025)

Mitigating Hallucinations in Large Vision-Language Models via Entity-Centric Multimodal Preference Optimization
par: Wu, Jiulong, et autres
Publié: (2025)

NoLan: Mitigating Object Hallucinations in Large Vision-Language Models via Dynamic Suppression of Language Priors
par: Ren, Lingfeng, et autres
Publié: (2026)

Image Tokens Matter: Mitigating Hallucination in Discrete Tokenizer-based Large Vision-Language Models via Latent Editing
par: Wang, Weixing, et autres
Publié: (2025)