Cover Image

Thinking Before Looking: Improving Multimodal LLM Reasoning via Mitigating Visual Hallucination

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zheng, Haojie, Xu, Tianyang, Sun, Hanchi, Pu, Shu, Chen, Ruoxi, Sun, Lichao
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Look Twice Before You Answer: Memory-Space Visual Retracing for Hallucination Mitigation in Multimodal Large Language Models
by: Zou, Xin, et al.
Published: (2024)

When Thinking Hurts: Mitigating Visual Forgetting in Video Reasoning via Frame Repetition
by: Sun, Xiaokun, et al.
Published: (2026)

Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning
by: Yang, Zexian, et al.
Published: (2025)

Look Carefully: Adaptive Visual Reinforcements in Multimodal Large Language Models for Hallucination Mitigation
by: Zhu, Xingyu, et al.
Published: (2026)

Look Again, Think Slowly: Enhancing Visual Reflection in Vision-Language Models
by: Jian, Pu, et al.
Published: (2025)

Seeing Through the Chain: Mitigate Hallucination in Multimodal Reasoning Models via CoT Compression and Contrastive Preference Optimization
by: Fang, Hao, et al.
Published: (2026)

Tell Model Where to Look: Mitigating Hallucinations in MLLMs by Vision-Guided Attention
by: Zhao, Jianfei, et al.
Published: (2025)

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

Think Before You Move: Latent Motion Reasoning for Text-to-Motion Generation
by: Qian, Yijie, et al.
Published: (2025)

See Different, Think Better: Visual Variations Mitigating Hallucinations in LVLMs
by: Dai, Ziyun, et al.
Published: (2025)

WAT: Online Video Understanding Needs Watching Before Thinking
by: Han, Zifan, 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)

Hallucination Mitigation Prompts Long-term Video Understanding
by: Sun, Yiwei, et al.
Published: (2024)

Reinforcing Video Reasoning Segmentation to Think Before It Segments
by: Gong, Sitong, et al.
Published: (2025)

Combating Multimodal LLM Hallucination via Bottom-Up Holistic Reasoning
by: Wu, Shengqiong, et al.
Published: (2024)

LLM4Brain: Training a Large Language Model for Brain Video Understanding
by: Zheng, Ruizhe, et al.
Published: (2024)

Rethinking and Red-Teaming Protective Perturbation in Personalized Diffusion Models
by: Liu, Yixin, et al.
Published: (2024)

Temporal Insight Enhancement: Mitigating Temporal Hallucination in Multimodal Large Language Models
by: Sun, Li, et al.
Published: (2024)

MIHBench: Benchmarking and Mitigating Multi-Image Hallucinations in Multimodal Large Language Models
by: Li, Jiale, 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)

Revisiting Visual Understanding in Multimodal Reasoning through a Lens of Image Perturbation
by: Li, Yuting, et al.
Published: (2025)

S1-VL: Scientific Multimodal Reasoning Model with Thinking-with-Images
by: Li, Qingxiao, et al.
Published: (2026)

Extracting Visual Facts from Intermediate Layers for Mitigating Hallucinations in Multimodal Large Language Models
by: Zhou, Haoran, et al.
Published: (2025)

Pensieve: Retrospect-then-Compare Mitigates Visual Hallucination
by: Yang, Dingchen, et al.
Published: (2024)

Mitigating Image Captioning Hallucinations in Vision-Language Models
by: Zhao, Fei, et al.
Published: (2025)

Beyond Single Models: Mitigating Multimodal Hallucinations via Adaptive Token Ensemble Decoding
by: Li, Jinlin, et al.
Published: (2025)

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

Look, Compare, Decide: Alleviating Hallucination in Large Vision-Language Models via Multi-View Multi-Path Reasoning
by: Qu, Xiaoye, et al.
Published: (2024)

Visual Attention Drifts,but Anchors Hold:Mitigating Hallucination in Multimodal Large Language Models via Cross-Layer Visual Anchors
by: Yang, Chengxu, et al.
Published: (2026)

Adversarial Orthogonal Disentanglement for LVLM Hallucination Mitigation
by: Cheng, Ruoxi, et al.
Published: (2026)

Visual Multi-Agent System: Mitigating Hallucination Snowballing via Visual Flow
by: Yu, Xinlei, et al.
Published: (2025)

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

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

Mitigating Visual Hallucinations via Semantic Curriculum Preference Optimization in MLLMs
by: Li, Yuanshuai, et al.
Published: (2025)

MLLM-as-a-Judge: Assessing Multimodal LLM-as-a-Judge with Vision-Language Benchmark
by: Chen, Dongping, et al.
Published: (2024)

Mitigating Hallucination in Visual-Language Models via Re-Balancing Contrastive Decoding
by: Liang, Xiaoyu, et al.
Published: (2024)

Localizing Before Answering: A Hallucination Evaluation Benchmark for Grounded Medical Multimodal LLMs
by: Nguyen, Dung, et al.
Published: (2025)

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

VASparse: Towards Efficient Visual Hallucination Mitigation via Visual-Aware Token Sparsification
by: Zhuang, Xianwei, et al.
Published: (2025)

Looking Back and Forth: Cross-Image Attention Calibration and Attentive Preference Learning for Multi-Image Hallucination Mitigation
by: Yang, Xiaochen, et al.
Published: (2026)