2 citations · 2 across the 4 of their papers we have counts for
9 papers · 1 filter
Parameter-Efficient Adaptation of SAM3 for Prompt-Driven Surgical Concept Segmentation
Changjing Liu, Yiming Huang, Beilei Cui +5
Efficient surgical segmentation empowers clinical diagnosis, intraoperative monitoring, and downstream robotic pipelines for reconstruction and simulation. Although prompt-driven f…
A Chain of Diagnosis Framework for Accurate and Explainable Radiology Report Generation
Haibo Jin, Haoxuan Che, Sunan He +1
Despite the progress of radiology report generation (RRG), existing works face two challenges: 1) The performances in clinical efficacy are unsatisfactory, especially for lesion at…
LLM-driven Medical Report Generation via Communication-efficient Heterogeneous Federated Learning
Haoxuan Che, Haibo Jin, Zhengrui Guo +3
LLMs have demonstrated significant potential in Medical Report Generation (MRG), yet their development requires large amounts of medical image-report pairs, which are commonly scat…
FedDAG: Federated Domain Adversarial Generation Towards Generalizable Medical Image Analysis
Haoxuan Che, Yifei Wu, Haibo Jin +2
Federated domain generalization aims to train a global model from multiple source domains and ensure its generalization ability to unseen target domains. Due to the target domain b…
GameGen-X: Interactive Open-world Game Video Generation
Haoxuan Che, Xuanhua He, Quande Liu +2
We introduce GameGen-X, the first diffusion transformer model specifically designed for both generating and interactively controlling open-world game videos. This model facilitates…
Rethinking Self-training for Semi-supervised Landmark Detection: A Selection-free Approach
Haibo Jin, Haoxuan Che, Hao Chen
Self-training is a simple yet effective method for semi-supervised learning, during which pseudo-label selection plays an important role for handling confirmation bias. Despite its…