Cover Image

Mitigating Dialogue Hallucination for Large Vision Language Models via Adversarial Instruction Tuning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Park, Dongmin, Qian, Zhaofang, Han, Guangxing, Lim, Ser-Nam
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Scene Co-pilot: Procedural Text to Video Generation with Human in the Loop
by: Qian, Zhaofang, et al.
Published: (2024)

Reflective Instruction Tuning: Mitigating Hallucinations in Large Vision-Language Models
by: Zhang, Jinrui, et al.
Published: (2024)

When Semantics Mislead Vision: Mitigating Large Multimodal Models Hallucinations in Scene Text Spotting and Understanding
by: Shu, Yan, et al.
Published: (2025)

Prescribing the Right Remedy: Mitigating Hallucinations in Large Vision-Language Models via Targeted Instruction Tuning
by: Hu, Rui, et al.
Published: (2024)

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

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

Jack of All Tasks, Master of Many: Designing General-purpose Coarse-to-Fine Vision-Language Model
by: Pramanick, Shraman, et al.
Published: (2023)

Instruction-Free Tuning of Large Vision Language Models for Medical Instruction Following
by: Kang, Myeongkyun, et al.
Published: (2026)

Mitigating Hallucinations in Large Vision-Language Models via DPO: On-Policy Data Hold the Key
by: Yang, Zhihe, et al.
Published: (2025)

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

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

Mitigating Hallucinations in Large Vision-Language Models via Causal Route Gating
by: Cheng, Zhe, et al.
Published: (2026)

Beyond Generation: Unlocking Universal Editing via Self-Supervised Fine-Tuning
by: Chen, Harold Haodong, et al.
Published: (2024)

SECOND: Mitigating Perceptual Hallucination in Vision-Language Models via Selective and Contrastive Decoding
by: Park, Woohyeon, et al.
Published: (2025)

Exploring Causes and Mitigation of Hallucinations in Large Vision Language Models
by: Sun, Yaqi, et al.
Published: (2025)

Towards Chunk-Wise Generation for Long Videos
by: Zhang, Siyang, et al.
Published: (2024)

Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation
by: Zhu, Xingyu, et al.
Published: (2026)

Nullu: Mitigating Object Hallucinations in Large Vision-Language Models via HalluSpace Projection
by: Yang, Le, et al.
Published: (2024)

Mitigating Hallucination in Large Vision-Language Models via Adaptive Attention Calibration
by: Fazli, Mehrdad, et al.
Published: (2025)

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

Mitigating Object Hallucinations in Large Vision-Language Models via Attention Calibration
by: Zhu, Younan, et al.
Published: (2025)

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

SAVER: Mitigating Hallucinations in Large Vision-Language Models via Style-Aware Visual Early Revision
by: Li, Zhaoxu, et al.
Published: (2025)

SAKED: Mitigating Hallucination in Large Vision-Language Models via Stability-Aware Knowledge Enhanced Decoding
by: Li, Zhaoxu, et al.
Published: (2026)

Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning
by: Liu, Fuxiao, et al.
Published: (2023)

Towards Cross-modal Backward-compatible Representation Learning for Vision-Language Models
by: Jang, Young Kyun, et al.
Published: (2024)

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

LARM: Large Auto-Regressive Model for Long-Horizon Embodied Intelligence
by: Li, Zhuoling, et al.
Published: (2024)

VEGAS: Mitigating Hallucinations in Large Vision-Language Models via Vision-Encoder Attention Guided Adaptive Steering
by: Wang, Zihu, et al.
Published: (2025)

MAP: Mitigating Hallucinations in Large Vision-Language Models with Map-Level Attention Processing
by: Li, Chenxi, et al.
Published: (2025)

Mitigating Hallucinations in Large Vision-Language Models via Summary-Guided Decoding
by: Min, Kyungmin, et al.
Published: (2024)

VORD: Visual Ordinal Calibration for Mitigating Object Hallucinations in Large Vision-Language Models
by: Neo, Dexter, et al.
Published: (2024)

HTDC: Hesitation-Triggered Differential Calibration for Mitigating Hallucination in Large Vision-Language Models
by: Liu, Xinyun
Published: (2026)

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

Towards Mitigating Hallucinations in Large Vision-Language Models by Refining Textual Embeddings
by: Agrawal, Aakriti, et al.
Published: (2025)

Analyzing and Mitigating Object Hallucination in Large Vision-Language Models
by: Zhou, Yiyang, et al.
Published: (2023)

Distilling Vision-Language Pretraining for Efficient Cross-Modal Retrieval
by: Jang, Young Kyun, et al.
Published: (2024)

CAST: Mitigating Object Hallucination in Large Vision-Language Models via Caption-Guided Visual Attention Steering
by: Li, Qiming, et al.
Published: (2026)

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction
by: Wang, Chao, et al.
Published: (2025)

Prefill-Time Intervention for Mitigating Hallucination in Large Vision-Language Models
by: Zhang, Chengsheng, et al.
Published: (2026)