Beyond Hallucinations: Enhancing LVLMs through Hallucination-Aware Direct Preference Optimization
Fuente:
arXiv
Saved in:
| Main Authors: | Zhao, Zhiyuan, Wang, Bin, Ouyang, Linke, Dong, Xiaoyi, Wang, Jiaqi, He, Conghui |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Cracking the Code of Hallucination in LVLMs with Vision-aware Head Divergence
by: He, Jinghan, et al.
Published: (2024)
by: He, Jinghan, et al.
Published: (2024)
Mitigating Hallucination in Multimodal Large Language Model via Hallucination-targeted Direct Preference Optimization
by: Fu, Yuhan, et al.
Published: (2024)
by: Fu, Yuhan, et al.
Published: (2024)
Grounding Language with Vision: A Conditional Mutual Information Calibrated Decoding Strategy for Reducing Hallucinations in LVLMs
by: Fang, Hao, et al.
Published: (2025)
by: Fang, Hao, et al.
Published: (2025)
Modality Bias in LVLMs: Analyzing and Mitigating Object Hallucination via Attention Lens
by: Zheng, Haohan, et al.
Published: (2025)
by: Zheng, Haohan, et al.
Published: (2025)
Steering LVLMs via Sparse Autoencoder for Hallucination Mitigation
by: Hua, Zhenglin, et al.
Published: (2025)
by: Hua, Zhenglin, et al.
Published: (2025)
OPERA: Alleviating Hallucination in Multi-Modal Large Language Models via Over-Trust Penalty and Retrospection-Allocation
by: Huang, Qidong, et al.
Published: (2023)
by: Huang, Qidong, et al.
Published: (2023)
Visual Description Grounding Reduces Hallucinations and Boosts Reasoning in LVLMs
by: Ghosh, Sreyan, et al.
Published: (2024)
by: Ghosh, Sreyan, et al.
Published: (2024)
HELPD: Mitigating Hallucination of LVLMs by Hierarchical Feedback Learning with Vision-enhanced Penalty Decoding
by: Yuan, Fan, et al.
Published: (2024)
by: Yuan, Fan, et al.
Published: (2024)
Direct Preference Optimization for Suppressing Hallucinated Prior Exams in Radiology Report Generation
by: Banerjee, Oishi, et al.
Published: (2024)
by: Banerjee, Oishi, et al.
Published: (2024)
SHALE: A Scalable Benchmark for Fine-grained Hallucination Evaluation in LVLMs
by: Yan, Bei, et al.
Published: (2025)
by: Yan, Bei, et al.
Published: (2025)
GLSim: Detecting Object Hallucinations in LVLMs via Global-Local Similarity
by: Park, Seongheon, et al.
Published: (2025)
by: Park, Seongheon, et al.
Published: (2025)
Why LVLMs Are More Prone to Hallucinations in Longer Responses: The Role of Context
by: Zheng, Ge, et al.
Published: (2025)
by: Zheng, Ge, et al.
Published: (2025)
HIME: Mitigating Object Hallucinations in LVLMs via Hallucination Insensitivity Model Editing
by: Akl, Ahmed, et al.
Published: (2026)
by: Akl, Ahmed, et al.
Published: (2026)
OViP: Online Vision-Language Preference Learning for VLM Hallucination
by: Liu, Shujun, et al.
Published: (2025)
by: Liu, Shujun, et al.
Published: (2025)
Image Over Text: Transforming Formula Recognition Evaluation with Character Detection Matching
by: Wang, Bin, et al.
Published: (2024)
by: Wang, Bin, et al.
Published: (2024)
CHASD: Language Increment-Calibrated Contrastive Decoding against Hallucination in LVLMs
by: Huang, Xiaoyi, et al.
Published: (2026)
by: Huang, Xiaoyi, et al.
Published: (2026)
When Prompts Override Vision: Prompt-Induced Hallucinations in LVLMs
by: Khayatan, Pegah, et al.
Published: (2026)
by: Khayatan, Pegah, et al.
Published: (2026)
Mitigating Hallucinations in Multimodal Spatial Relations through Constraint-Aware Prompting
by: Wu, Jiarui, et al.
Published: (2025)
by: Wu, Jiarui, et al.
Published: (2025)
Systematic Reward Gap Optimization for Mitigating VLM Hallucinations
by: He, Lehan, et al.
Published: (2024)
by: He, Lehan, et al.
Published: (2024)
DocLayout-YOLO: Enhancing Document Layout Analysis through Diverse Synthetic Data and Global-to-Local Adaptive Perception
by: Zhao, Zhiyuan, et al.
Published: (2024)
by: Zhao, Zhiyuan, et al.
Published: (2024)
Hallucination at a Glance: Controlled Visual Edits and Fine-Grained Multimodal Learning
by: Bai, Tianyi, et al.
Published: (2025)
by: Bai, Tianyi, et al.
Published: (2025)
Mitigating Hallucinations in Large Vision-Language Models (LVLMs) via Language-Contrastive Decoding (LCD)
by: Manevich, Avshalom, et al.
Published: (2024)
by: Manevich, Avshalom, 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)
by: Ouali, Yassine, et al.
Published: (2024)
AMBER: An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation
by: Wang, Junyang, et al.
Published: (2023)
by: Wang, Junyang, et al.
Published: (2023)
Mitigating Hallucinations in Large Vision-Language Models via Entity-Centric Multimodal Preference Optimization
by: Wu, Jiulong, et al.
Published: (2025)
by: Wu, Jiulong, et al.
Published: (2025)
Optimizing LVLMs with On-Policy Data for Effective Hallucination Mitigation
by: Yu, Chengzhi, et al.
Published: (2025)
by: Yu, Chengzhi, et al.
Published: (2025)
Mitigating Hallucinations in Multimodal LLMs via Object-aware Preference Optimization
by: Compagnoni, Alberto, et al.
Published: (2025)
by: Compagnoni, Alberto, et al.
Published: (2025)
Mitigating Hallucinations in Large Vision-Language Models by Self-Injecting Hallucinations
by: Lu, Yifan, et al.
Published: (2025)
by: Lu, Yifan, et al.
Published: (2025)
What Makes LVLMs Hallucinate Less? Unveiling the Architectural Factors Behind Hallucination Robustness
by: He, Yusheng, et al.
Published: (2026)
by: He, Yusheng, et al.
Published: (2026)
R-CoV: Region-Aware Chain-of-Verification for Alleviating Object Hallucinations in LVLMs
by: Xie, Jiahao, et al.
Published: (2026)
by: Xie, Jiahao, et al.
Published: (2026)
Instruction-Aligned Visual Attention for Mitigating Hallucinations in Large Vision-Language Models
by: Li, Bin, et al.
Published: (2025)
by: Li, Bin, et al.
Published: (2025)
MIA-DPO: Multi-Image Augmented Direct Preference Optimization For Large Vision-Language Models
by: Liu, Ziyu, et al.
Published: (2024)
by: Liu, Ziyu, et al.
Published: (2024)
Volcano: Mitigating Multimodal Hallucination through Self-Feedback Guided Revision
by: Lee, Seongyun, et al.
Published: (2023)
by: Lee, Seongyun, et al.
Published: (2023)
Mitigating Action-Relation Hallucinations in LVLMs via Relation-aware Visual Enhancement
by: Qin, Zhenxin, et al.
Published: (2026)
by: Qin, Zhenxin, et al.
Published: (2026)
Mitigating Object Hallucinations in LVLMs via Attention Imbalance Rectification
by: Sun, Han, et al.
Published: (2026)
by: Sun, Han, et al.
Published: (2026)
DAMRO: Dive into the Attention Mechanism of LVLM to Reduce Object Hallucination
by: Gong, Xuan, et al.
Published: (2024)
by: Gong, Xuan, et al.
Published: (2024)
PyramidDrop: Accelerating Your Large Vision-Language Models via Pyramid Visual Redundancy Reduction
by: Xing, Long, et al.
Published: (2024)
by: Xing, Long, et al.
Published: (2024)
BEAF: Observing BEfore-AFter Changes to Evaluate Hallucination in Vision-language Models
by: Ye-Bin, Moon, et al.
Published: (2024)
by: Ye-Bin, Moon, et al.
Published: (2024)
Tone Matters: The Impact of Linguistic Tone on Hallucination in VLMs
by: Hong, Weihao, et al.
Published: (2026)
by: Hong, Weihao, et al.
Published: (2026)
Mitigating Multimodal Hallucinations via Gradient-based Self-Reflection
by: Wang, Shan, et al.
Published: (2025)
by: Wang, Shan, et al.
Published: (2025)
Similar Items
-
Cracking the Code of Hallucination in LVLMs with Vision-aware Head Divergence
by: He, Jinghan, et al.
Published: (2024) -
Mitigating Hallucination in Multimodal Large Language Model via Hallucination-targeted Direct Preference Optimization
by: Fu, Yuhan, et al.
Published: (2024) -
Grounding Language with Vision: A Conditional Mutual Information Calibrated Decoding Strategy for Reducing Hallucinations in LVLMs
by: Fang, Hao, et al.
Published: (2025) -
Modality Bias in LVLMs: Analyzing and Mitigating Object Hallucination via Attention Lens
by: Zheng, Haohan, et al.
Published: (2025) -
Steering LVLMs via Sparse Autoencoder for Hallucination Mitigation
by: Hua, Zhenglin, et al.
Published: (2025)