Mitigating Object Hallucinations in LVLMs via Attention Imbalance Rectification
Fuente:
arXiv
Saved in:
| Main Authors: | Sun, Han, Li, Qin, Wang, Peixin, Zhang, Min |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
MHSA: A Lightweight Framework for Mitigating Hallucinations via Steered Attention in LVLMs
by: Ding, Wei, et al.
Published: (2026)
by: Ding, Wei, et al.
Published: (2026)
Causally-Grounded Dual-Path Attention Intervention for Object Hallucination Mitigation in LVLMs
by: Yu, Liu, et al.
Published: (2025)
by: Yu, Liu, et al.
Published: (2025)
TARAC: Mitigating Hallucination in LVLMs via Temporal Attention Real-time Accumulative Connection
by: Jiang, Lei, et al.
Published: (2025)
by: Jiang, Lei, et al.
Published: (2025)
Countering the Over-Reliance Trap: Mitigating Object Hallucination for LVLMs via a Self-Validation Framework
by: Liu, Shiyu, et al.
Published: (2026)
by: Liu, Shiyu, et al.
Published: (2026)
Optimizing LVLMs with On-Policy Data for Effective Hallucination Mitigation
by: Yu, Chengzhi, et al.
Published: (2025)
by: Yu, Chengzhi, et al.
Published: (2025)
Attention-space Contrastive Guidance for Efficient Hallucination Mitigation in LVLMs
by: Jo, Yujin, et al.
Published: (2026)
by: Jo, Yujin, et al.
Published: (2026)
Finding the Correct Visual Evidence Without Forgetting: Mitigating Hallucination in LVLMs via Inter-Layer Visual Attention Discrepancy
by: Xie, Yutong, et al.
Published: (2026)
by: Xie, Yutong, et al.
Published: (2026)
Steering LVLMs via Sparse Autoencoder for Hallucination Mitigation
by: Hua, Zhenglin, et al.
Published: (2025)
by: Hua, Zhenglin, 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)
CATCH: Complementary Adaptive Token-level Contrastive Decoding to Mitigate Hallucinations in LVLMs
by: Kan, Zhehan, et al.
Published: (2024)
by: Kan, Zhehan, et al.
Published: (2024)
MRFD: Multi-Region Fusion Decoding with Self-Consistency for Mitigating Hallucinations in LVLMs
by: Ge, Haonan, et al.
Published: (2025)
by: Ge, Haonan, et al.
Published: (2025)
Seeing Clearly by Layer Two: Enhancing Attention Heads to Alleviate Hallucination in LVLMs
by: Zhang, Xiaofeng, et al.
Published: (2024)
by: Zhang, Xiaofeng, et al.
Published: (2024)
Identify, Isolate, and Purge: Mitigating Hallucinations in LVLMs via Self-Evolving Distillation
by: Li, Wenhao, et al.
Published: (2025)
by: Li, Wenhao, et al.
Published: (2025)
Mitigating Object Hallucinations in Large Vision-Language Models via Attention Calibration
by: Zhu, Younan, et al.
Published: (2025)
by: Zhu, Younan, 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)
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)
CLAIM: Mitigating Multilingual Object Hallucination in Large Vision-Language Models with Cross-Lingual Attention Intervention
by: Ye, Zekai, et al.
Published: (2025)
by: Ye, Zekai, et al.
Published: (2025)
Cross-Modal Attention Calibration for LVLM Hallucination Mitigation
by: Li, Jiaming, et al.
Published: (2025)
by: Li, Jiaming, et al.
Published: (2025)
Mitigating Object Hallucinations in MLLMs via Multi-Frequency Perturbations
by: Li, Shuo, et al.
Published: (2025)
by: Li, Shuo, et al.
Published: (2025)
When RAG Hurts: Diagnosing and Mitigating Attention Distraction in Retrieval-Augmented LVLMs
by: Zhao, Beidi, et al.
Published: (2026)
by: Zhao, Beidi, et al.
Published: (2026)
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)
CHASD: Language Increment-Calibrated Contrastive Decoding against Hallucination in LVLMs
by: Huang, Xiaoyi, et al.
Published: (2026)
by: Huang, Xiaoyi, et al.
Published: (2026)
Mitigating Object Hallucinations in Large Vision-Language Models with Assembly of Global and Local Attention
by: An, Wenbin, et al.
Published: (2024)
by: An, Wenbin, et al.
Published: (2024)
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)
Mitigating Hallucinations on Object Attributes using Multiview Images and Negative Instructions
by: Tan, Zhijie, et al.
Published: (2025)
by: Tan, Zhijie, et al.
Published: (2025)
Investigating and Mitigating Object Hallucinations in Pretrained Vision-Language (CLIP) Models
by: Liu, Yufang, et al.
Published: (2024)
by: Liu, Yufang, et al.
Published: (2024)
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)
VidLBEval: Benchmarking and Mitigating Language Bias in Video-Involved LVLMs
by: Yang, Yiming, et al.
Published: (2025)
by: Yang, Yiming, et al.
Published: (2025)
Visual Description Grounding Reduces Hallucinations and Boosts Reasoning in LVLMs
by: Ghosh, Sreyan, et al.
Published: (2024)
by: Ghosh, Sreyan, et al.
Published: (2024)
MAP: Mitigating Hallucinations in Large Vision-Language Models with Map-Level Attention Processing
by: Li, Chenxi, et al.
Published: (2025)
by: Li, Chenxi, et al.
Published: (2025)
Temporal Insight Enhancement: Mitigating Temporal Hallucination in Multimodal Large Language Models
by: Sun, Li, et al.
Published: (2024)
by: Sun, Li, et al.
Published: (2024)
Mitigating Hallucinations in Video Large Language Models via Spatiotemporal-Semantic Contrastive Decoding
by: Gao, Yuansheng, et al.
Published: (2026)
by: Gao, Yuansheng, et al.
Published: (2026)
Attention Hijackers: Detect and Disentangle Attention Hijacking in LVLMs for Hallucination Mitigation
by: Chen, Beitao, et al.
Published: (2025)
by: Chen, Beitao, 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)
Mitigating Object Hallucinations in Vision-Language Models through Region-Aware Attention Recalibration
by: Xu, Yuanzhi, et al.
Published: (2026)
by: Xu, Yuanzhi, et al.
Published: (2026)
Mitigating Cross-Image Information Leakage in LVLMs for Multi-Image Tasks
by: Park, Yeji, et al.
Published: (2025)
by: Park, Yeji, et al.
Published: (2025)
Seeing It or Not? Interpretable Vision-aware Latent Steering to Mitigate Object Hallucinations
by: Chen, Boxu, et al.
Published: (2025)
by: Chen, Boxu, et al.
Published: (2025)
SAVAA: Mitigating Hallucinations in LVLMs via Step-wise Adaptive Visual Attention Amplification
by: Zhang, Jiacheng, et al.
Published: (2026)
by: Zhang, Jiacheng, et al.
Published: (2026)
V-ITI: Mitigating Hallucinations in Multimodal Large Language Models via Visual Inference-Time Intervention
by: Sun, Nan, et al.
Published: (2025)
by: Sun, Nan, et al.
Published: (2025)
Retrieval Visual Contrastive Decoding to Mitigate Object Hallucinations in Large Vision-Language Models
by: Lee, Jihoon, et al.
Published: (2025)
by: Lee, Jihoon, et al.
Published: (2025)
Similar Items
-
MHSA: A Lightweight Framework for Mitigating Hallucinations via Steered Attention in LVLMs
by: Ding, Wei, et al.
Published: (2026) -
Causally-Grounded Dual-Path Attention Intervention for Object Hallucination Mitigation in LVLMs
by: Yu, Liu, et al.
Published: (2025) -
TARAC: Mitigating Hallucination in LVLMs via Temporal Attention Real-time Accumulative Connection
by: Jiang, Lei, et al.
Published: (2025) -
Countering the Over-Reliance Trap: Mitigating Object Hallucination for LVLMs via a Self-Validation Framework
by: Liu, Shiyu, et al.
Published: (2026) -
Optimizing LVLMs with On-Policy Data for Effective Hallucination Mitigation
by: Yu, Chengzhi, et al.
Published: (2025)