:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Yue, Zihao, Zhang, Liang, Jin, Qin
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Computer Vision and Pattern Recognition
Online Access:	https://arxiv.org/abs/2402.14545
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

More Thinking, Less Seeing? Assessing Amplified Hallucination in Multimodal Reasoning Models
by: Liu, Chengzhi, et al.
Published: (2025)

A Unified Hallucination Mitigation Framework for Large Vision-Language Models
by: Chang, Yue, et al.
Published: (2024)

Mitigating Multimodal Hallucination via Phase-wise Self-reward
by: Zhang, Yu, et al.
Published: (2026)

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

Diving into Mitigating Hallucinations from a Vision Perspective for Large Vision-Language Models
by: Wang, Weihang, et al.
Published: (2025)

Analyzing and Mitigating Object Hallucination: A Training Bias Perspective
by: Li, Yifan, et al.
Published: (2025)

Mitigating Multimodal Hallucinations via Gradient-based Self-Reflection
by: Wang, Shan, et al.
Published: (2025)

Learning from Fine-Grained Visual Discrepancies: Mitigating Multimodal Hallucinations via In-Context Visual Contrastive Optimization
by: Deng, Haolin, et al.
Published: (2026)

Less Is More? Selective Visual Attention to High-Importance Regions for Multimodal Radiology Summarization
by: Naznin, Mst. Fahmida Sultana, et al.
Published: (2026)

Volcano: Mitigating Multimodal Hallucination through Self-Feedback Guided Revision
by: Lee, Seongyun, et al.
Published: (2023)

The Devil is in the EOS: Sequence Training for Detailed Image Captioning
by: Mohamed, Abdelrahman, et al.
Published: (2025)

Movie101v2: Improved Movie Narration Benchmark
by: Yue, Zihao, et al.
Published: (2024)

Mitigating Hallucinations in Large Vision-Language Models by Self-Injecting Hallucinations
by: Lu, Yifan, et al.
Published: (2025)

MM-LIMA: Less Is More for Alignment in Multi-Modal Datasets
by: Wei, Lai, et al.
Published: (2023)

EFUF: Efficient Fine-grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language Models
by: Xing, Shangyu, 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)

Watch Closely: Mitigating Object Hallucinations in Large Vision-Language Models with Disentangled Decoding
by: Ma, Ruiqi, et al.
Published: (2025)

Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images
by: You, Liangliang, et al.
Published: (2025)

Mitigating Hallucinations in Multimodal Spatial Relations through Constraint-Aware Prompting
by: Wu, Jiarui, et al.
Published: (2025)

Instruction-Aligned Visual Attention for Mitigating Hallucinations in Large Vision-Language Models
by: Li, Bin, et al.
Published: (2025)

Quantifying and Mitigating Unimodal Biases in Multimodal Large Language Models: A Causal Perspective
by: Chen, Meiqi, et al.
Published: (2024)

Less is More: High-value Data Selection for Visual Instruction Tuning
by: Liu, Zikang, et al.
Published: (2024)

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

ReLoop: "Seeing Twice and Thinking Backwards" via Closed-loop Training to Mitigate Hallucinations in Multimodal understanding
by: Yang, Jianjiang, et al.
Published: (2025)

Modality Bias in LVLMs: Analyzing and Mitigating Object Hallucination via Attention Lens
by: Zheng, Haohan, et al.
Published: (2025)

Mitigating Object Hallucination via Concentric Causal Attention
by: Xing, Yun, et al.
Published: (2024)

Systematic Reward Gap Optimization for Mitigating VLM Hallucinations
by: He, Lehan, et al.
Published: (2024)

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

Mask What Matters: Mitigating Object Hallucinations in Multimodal Large Language Models with Object-Aligned Visual Contrastive Decoding
by: Chen, Boqi, et al.
Published: (2026)

Mitigating Hallucinations in Multimodal LLMs via Object-aware Preference Optimization
by: Compagnoni, Alberto, et al.
Published: (2025)

Mitigating Object Hallucination via Robust Local Perception Search
by: Gao, Zixian, et al.
Published: (2025)

MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark
by: Yue, Xiang, et al.
Published: (2024)

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model
by: Arif, Kazi Hasan Ibn, et al.
Published: (2025)

Do Vision Encoders Truly Explain Object Hallucination?: Mitigating Object Hallucination via Simple Fine-Grained CLIPScore
by: Oh, Hongseok, et al.
Published: (2025)

ESREAL: Exploiting Semantic Reconstruction to Mitigate Hallucinations in Vision-Language Models
by: Kim, Minchan, et al.
Published: (2024)

ONLY: One-Layer Intervention Sufficiently Mitigates Hallucinations in Large Vision-Language Models
by: Wan, Zifu, 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)

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models
by: Zhang, Ce, et al.
Published: (2025)

Do We Really Need External Tools to Mitigate Hallucinations? SIRA: Shared-Prefix Internal Reconstruction of Attribution
by: Qin, Tian, et al.
Published: (2026)

Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language Models
by: Zheng, Kening, et al.
Published: (2024)