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CheXPO-v2: Preference Optimization for Chest X-ray VLMs with Knowledge Graph Consistency
Xiao Liang, Yuxuan An, Di Wang +4
Medical Vision-Language Models (VLMs) are prone to hallucinations, compromising clinical reliability. While reinforcement learning methods like Group Relative Policy Optimization (…
Anatomical Region-Guided Contrastive Decoding: A Plug-and-Play Strategy for Mitigating Hallucinations in Medical VLMs
Xiao Liang, Chenxi Liu, Zhi Ma +4
Medical Vision-Language Models (MedVLMs) show immense promise in clinical applicability. However, their reliability is hindered by hallucinations, where models often fail to derive…
Uncertainty-Driven Expert Control: Enhancing the Reliability of Medical Vision-Language Models
Xiao Liang, Di Wang, Zhicheng Jiao +4
The rapid advancements in Vision Language Models (VLMs) have prompted the development of multi-modal medical assistant systems. Despite this progress, current models still have inh…
CheXPO: Preference Optimization for Chest X-ray VLMs with Counterfactual Rationale
Xiao Liang, Jiawei Hu, Di Wang +5
Vision-language models (VLMs) are prone to hallucinations that critically compromise reliability in medical applications. While preference optimization can mitigate these hallucina…