Cover Image

Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	You, Liangliang, Yao, Junchi, Yang, Shu, Hu, Guimin, Hu, Lijie, Wang, Di
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence Computation and Language Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Tracing and Mitigating Hallucinations in Multimodal LLMs via Dynamic Attention Localization
by: Yang, Tiancheng, et al.
Published: (2025)

ICT: Image-Object Cross-Level Trusted Intervention for Mitigating Object Hallucination in Large Vision-Language Models
by: Chen, Junzhe, et al.
Published: (2024)

Investigating and Mitigating the Multimodal Hallucination Snowballing in Large Vision-Language Models
by: Zhong, Weihong, 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 Entity-Centric Multimodal Preference Optimization
by: Wu, Jiulong, et al.
Published: (2025)

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

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

ODE: Open-Set Evaluation of Hallucinations in Multimodal Large Language Models
by: Tu, Yahan, et al.
Published: (2024)

Mitigating Hallucinations in Large Vision-Language Models via Summary-Guided Decoding
by: Min, Kyungmin, 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)

Evaluating Large Language Models on Multimodal Chemistry Olympiad Exams
by: Cui, Yiming, et al.
Published: (2025)

ChartHal: A Fine-grained Framework Evaluating Hallucination of Large Vision Language Models in Chart Understanding
by: Wang, Xingqi, et al.
Published: (2025)

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

Mitigating Object Hallucinations in Large Vision-Language Models with Assembly of Global and Local Attention
by: An, Wenbin, et al.
Published: (2024)

MedHallTune: An Instruction-Tuning Benchmark for Mitigating Medical Hallucination in Vision-Language Models
by: Yan, Qiao, et al.
Published: (2025)

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

Mitigating Object Hallucination in Large Vision-Language Models via Image-Grounded Guidance
by: Zhao, Linxi, et al.
Published: (2024)

Image-of-Thought Prompting for Visual Reasoning Refinement in Multimodal Large Language Models
by: Zhou, Qiji, et al.
Published: (2024)

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

CLAIM: Mitigating Multilingual Object Hallucination in Large Vision-Language Models with Cross-Lingual Attention Intervention
by: Ye, Zekai, et al.
Published: (2025)

Decoding by Perturbation: Mitigating MLLM Hallucinations via Dynamic Textual Perturbation
by: Jia, Sihang, et al.
Published: (2026)

Black-Box Visual Prompt Engineering for Mitigating Object Hallucination in Large Vision Language Models
by: Woo, Sangmin, et al.
Published: (2025)

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

NoLan: Mitigating Object Hallucinations in Large Vision-Language Models via Dynamic Suppression of Language Priors
by: Ren, Lingfeng, et al.
Published: (2026)

Woodpecker: Hallucination Correction for Multimodal Large Language Models
by: Yin, Shukang, et al.
Published: (2023)

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

Efficient Contrastive Decoding with Probabilistic Hallucination Detection - Mitigating Hallucinations in Large Vision Language Models -
by: Fieback, Laura, et al.
Published: (2025)

Mixture of Decoding: An Attention-Inspired Adaptive Decoding Strategy to Mitigate Hallucinations in Large Vision-Language Models
by: Chen, Xinlong, et al.
Published: (2025)

First Logit Boosting: Visual Grounding Method to Mitigate Object Hallucination in Large Vision-Language Models
by: Ha, Jiwoo, et al.
Published: (2026)

EFUF: Efficient Fine-grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language Models
by: Xing, Shangyu, et al.
Published: (2024)

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

Benchmarking and Mitigating Sycophancy in Medical Vision Language Models
by: Xu, Juangui, et al.
Published: (2025)

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

Learning to Decode Against Compositional Hallucination in Video Multimodal Large Language Models
by: Xing, Wenbin, et al.
Published: (2026)

Visual Self-Fulfilling Alignment: Shaping Safety-Oriented Personas via Threat-Related Images
by: Yang, Qishun, et al.
Published: (2026)

II-Bench: An Image Implication Understanding Benchmark for Multimodal Large Language Models
by: Liu, Ziqiang, et al.
Published: (2024)

Flattery in Motion: Benchmarking and Analyzing Sycophancy in Video-LLMs
by: Zhou, Wenrui, et al.
Published: (2025)

What if...?: Thinking Counterfactual Keywords Helps to Mitigate Hallucination in Large Multi-modal Models
by: Kim, Junho, et al.
Published: (2024)

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

Benchmarking Deflection and Hallucination in Large Vision-Language Models
by: Moratelli, Nicholas, et al.
Published: (2026)