16 citations · 48 across the 12 of their papers we have counts for
19 papers · 1 filter
Objective-Aligned Direct Answer SFT for Robust Multi-Frame Medical VQA
Site Li, Jianyi Hao, Xiaofeng Liu
Multi-frame medical VQA appears to reward increasingly complex adaptation: controller-style inference, localization-aware reranking, static hard-negative mixing, and staged continu…
Inference-Time Agentic Decision Rules Beat Longer Evolving Search for Multi-Image Medical Reasoning
Site Li, Jianyi Hao, Xiaofeng Liu
Multi-image medical VQA is not merely a prompt-length problem; it is a fundamental challenge of agentic decision-making. Medical vision-language agents must aggregate evidence acro…
Self-semantic contour adaptation for cross modality brain tumor segmentation
Xiaofeng Liu, Fangxu Xing, Georges El Fakhri +1
Unsupervised domain adaptation (UDA) between two significantly disparate domains to learn high-level semantic alignment is a crucial yet challenging task.~To this end, in this work…
Recursively Conditional Gaussian for Ordinal Unsupervised Domain Adaptation
Xiaofeng Liu, Site Li, Yubin Ge +3
The unsupervised domain adaptation (UDA) has been widely adopted to alleviate the data scalability issue, while the existing works usually focus on classifying independently discre…
Embedding Semantic Hierarchy in Discrete Optimal Transport for Risk Minimization
Yubin Ge, Site Li, Xuyang Li +4
The widely-used cross-entropy (CE) loss-based deep networks achieved significant progress w.r.t. the classification accuracy. However, the CE loss can essentially ignore the risk o…
Subtype-aware Unsupervised Domain Adaptation for Medical Diagnosis
Xiaofeng Liu, Xiongchang Liu, Bo Hu +7
Recent advances in unsupervised domain adaptation (UDA) show that transferable prototypical learning presents a powerful means for class conditional alignment, which encourages the…