34 citations · 213 across the 28 of their papers we have counts for
28 papers
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…
Motion-Scenario Decoupling for Rat-Aware Video Position Prediction: Strategy and Benchmark
Xiaofeng Liu, Jiaxin Gao, Yaohua Liu +2
Recently significant progress has been made in human action recognition and behavior prediction using deep learning techniques, leading to improved vision-based semantic understand…
Constraining Pseudo-label in Self-training Unsupervised Domain Adaptation with Energy-based Model
Lingsheng Kong, Bo Hu, Xiongchang Liu +3
Deep learning is usually data starved, and the unsupervised domain adaptation (UDA) is developed to introduce the knowledge in the labeled source domain to the unlabeled target dom…
Subtype-Aware Dynamic Unsupervised Domain Adaptation
Xiaofeng Liu, Fangxu Xing, Jia You +4
Unsupervised domain adaptation (UDA) has been successfully applied to transfer knowledge from a labeled source domain to target domains without their labels. Recently introduced tr…
Deep Unsupervised Domain Adaptation: A Review of Recent Advances and Perspectives
Xiaofeng Liu, Chaehwa Yoo, Fangxu Xing +4
Deep learning has become the method of choice to tackle real-world problems in different domains, partly because of its ability to learn from data and achieve impressive performanc…