Cover Image

Hallucination Elimination and Semantic Enhancement Framework for Vision-Language Models in Traffic Scenarios

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Fan, Jiaqi, Wu, Jianhua, Chu, Hongqing, Ge, Quanbo, Gao, Bingzhao
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

MLLM-SUL: Multimodal Large Language Model for Semantic Scene Understanding and Localization in Traffic Scenarios
by: Fan, Jiaqi, et al.
Published: (2024)

RAC3: Retrieval-Augmented Corner Case Comprehension for Autonomous Driving with Vision-Language Models
by: Wang, Yujin, et al.
Published: (2024)

ScenePilot-4K: A Large-Scale First-Person Dataset and Benchmark for Vision-Language Models in Autonomous Driving
by: Wang, Yujin, et al.
Published: (2026)

RAD: Retrieval-Augmented Decision-Making of Meta-Actions with Vision-Language Models in Autonomous Driving
by: Wang, Yujin, et al.
Published: (2025)

Prospective Role of Foundation Models in Advancing Autonomous Vehicles
by: Wu, Jianhua, et al.
Published: (2023)

VaLiD: Mitigating the Hallucination of Large Vision Language Models by Visual Layer Fusion Contrastive Decoding
by: Wang, Jiaqi, et al.
Published: (2024)

AIGCs Confuse AI Too: Investigating and Explaining Synthetic Image-induced Hallucinations in Large Vision-Language Models
by: Gao, Yifei, et al.
Published: (2024)

Generate, but Verify: Reducing Hallucination in Vision-Language Models with Retrospective Resampling
by: Wu, Tsung-Han, et al.
Published: (2025)

Alleviating Hallucinations in Large Vision-Language Models through Hallucination-Induced Optimization
by: Lyu, Xinyu, et al.
Published: (2024)

Hallucination Filtering in Radiology Vision-Language Models Using Discrete Semantic Entropy
by: Wienholt, Patrick, et al.
Published: (2025)

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

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

Evaluating and Analyzing Relationship Hallucinations in Large Vision-Language Models
by: Wu, Mingrui, et al.
Published: (2024)

Evaluation and Enhancement of Semantic Grounding in Large Vision-Language Models
by: Lu, Jiaying, et al.
Published: (2023)

UniVRSE: Unified Vision-conditioned Response Semantic Entropy for Hallucination Detection in Medical Vision-Language Models
by: Liao, Zehui, et al.
Published: (2025)

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

Detecting and Evaluating Medical Hallucinations in Large Vision Language Models
by: Chen, Jiawei, et al.
Published: (2024)

Scenario Understanding of Traffic Scenes Through Large Visual Language Models
by: Rivera, Esteban, et al.
Published: (2025)

CRoPS: A Training-Free Hallucination Mitigation Framework for Vision-Language Models
by: Anand, Neeraj, et al.
Published: (2026)

HII-DPO: Eliminate Hallucination via Accurate Hallucination-Inducing Counterfactual Images
by: Yang, Yilin, et al.
Published: (2026)

KEPT: Knowledge-Enhanced Prediction of Trajectories from Consecutive Driving Frames with Vision-Language Models
by: Wang, Yujin, et al.
Published: (2025)

PolarVLM: Bridging the Semantic-Physical Gap in Vision-Language Models
by: Li, Yuliang, et al.
Published: (2026)

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

Dual-Pathway Circuits of Object Hallucination in Vision-Language Models
by: Liu, Jiaxin, et al.
Published: (2026)

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

Object Hallucination-Free Reinforcement Unlearning for Vision-Language Models
by: Jia, Kaidi, et al.
Published: (2026)

Med-StepBench: A Hierarchical Reasoning Framework for Evaluating Hallucinations in Medical Vision-Language Models
by: Nguyen, Minh Khoi, et al.
Published: (2026)

Anatomy of a Lie: A Multi-Stage Diagnostic Framework for Tracing Hallucinations in Vision-Language Models
by: Xiong, Lexiang, et al.
Published: (2026)

Robust Prompt Tuning for Vision-Language Models with Mild Semantic Noise
by: Gao, Yansheng, et al.
Published: (2025)

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

ScenarioControl: Vision-Language Controllable Vectorized Latent Scenario Generation
by: Gao, Lili, et al.
Published: (2026)

MCA-LLaVA: Manhattan Causal Attention for Reducing Hallucination in Large Vision-Language Models
by: Zhao, Qiyan, et al.
Published: (2025)

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

LLM-as-Judge Framework for Evaluating Tone-Induced Hallucination in Vision-Language Models
by: Jiang, Zhiyuan, et al.
Published: (2026)

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

Overthinking Causes Hallucination: Tracing Confounder Propagation in Vision Language Models
by: Shoby, Abin, et al.
Published: (2026)

HalLoc: Token-level Localization of Hallucinations for Vision Language Models
by: Park, Eunkyu, et al.
Published: (2025)

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task
by: Long, Xingming, et al.
Published: (2025)

ReCo: Reminder Composition Mitigates Hallucinations in Vision-Language Models
by: Chytas, Sotirios Panagiotis, et al.
Published: (2025)

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