collaborators

6 papers

cs.AI2026

VideoAgent: Personalized Synthesis of Scientific Videos

Xiao Liang, Bangxin Li, Zixuan Chen +5

The technical complexity of research papers often limits their reach, necessitating more accessible formats like scientific videos to disseminate key insights through engaging narr…

cs.CV2025

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 (…

cs.CV2025

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…

cs.LG2025

EvoFormer: Learning Dynamic Graph-Level Representations with Structural and Temporal Bias Correction

Haodi Zhong, Liuxin Zou, Di Wang +3

Dynamic graph-level embedding aims to capture structural evolution in networks, which is essential for modeling real-world scenarios. However, existing methods face two critical ye…

cs.CV2025

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…

cs.CV2025

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…