3 citations · 4 across the 9 of their papers we have counts for
9 papers
Beyond Raw Context Transfer: Representation-based Federated Retrieval-Augmented Generation
Can Peng, Yu Liu, Yingyu Yang +4
Retrieval-augmented generation (RAG) improves the factuality of large language models (LLMs) and vision-language models (VLMs) by grounding generation in external knowledge. Howeve…
DECAF: De-Clustering for Adaptive Representational Unlearning
Anjie Le, Can Peng, Hongcheng Guo +1
Machine unlearning, which aims to remove the influence of specific training data from a trained model, is a key requirement for privacy, accountability, and adaptive deployment. We…
Interpretable Probabilistic Medical Image Segmentation via Gaussian Process with Explicit Modelling of Annotation Bias and Variability
Qi Li, Yuliang Huang, Shaheer U. Saeed +7
Deep learning-based medical image segmentation models are trained using annotations that exhibit systematic bias and variability across raters. While probabilistic multi-rater appr…
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning
Yuyuan Liu, Can Peng, Yingyu Yang +3
Recent progress in deep learning has significantly advanced CT image analysis, particularly for segmentation tasks. However, these advances are largely confined to image-level patt…
Orientation-Robust Latent Motion Trajectory Learning for Annotation-free Cardiac Phase Detection in Fetal Echocardiography
Yingyu Yang, Qianye Yang, Can Peng +4
Fetal echocardiography is essential for detecting congenital heart disease (CHD), facilitating pregnancy management, optimized delivery planning, and timely postnatal interventions…
POUR: A Provably Optimal Method for Unlearning Representations via Neural Collapse
Anjie Le, Can Peng, Yuyuan Liu +1
In computer vision, machine unlearning aims to remove the influence of specific visual concepts or training images without retraining from scratch. Studies show that existing appro…
Latent Motion Profiling for Annotation-free Cardiac Phase Detection in Adult and Fetal Echocardiography Videos
Yingyu Yang, Qianye Yang, Kangning Cui +6
The identification of cardiac phase is an essential step for analysis and diagnosis of cardiac function. Automatic methods, especially data-driven methods for cardiac phase detecti…
Semi-weakly-supervised neural network training for medical image registration
Yiwen Li, Yunguan Fu, Iani J. M. B. Gayo +11
For training registration networks, weak supervision from segmented corresponding regions-of-interest (ROIs) have been proven effective for (a) supplementing unsupervised methods,…
Prototypical few-shot segmentation for cross-institution male pelvic structures with spatial registration
Yiwen Li, Yunguan Fu, Iani Gayo +12
The prowess that makes few-shot learning desirable in medical image analysis is the efficient use of the support image data, which are labelled to classify or segment new classes,…