12 papers
Finding Kissing Numbers with Game-theoretic Reinforcement Learning
Chengdong Ma, Théo Tao Zhaowei, Pengyu Li +7
Since Isaac Newton first studied the Kissing Number Problem in 1694, determining the maximal number of non-overlapping spheres around a central sphere has remained a defining chall…
DistFlow: A Fully Distributed RL Framework for Scalable and Efficient LLM Post-Training
Zhixin Wang, Jiaming Xu, Tianyi Zhou +10
Effectively scaling Reinforcement Learning (RL) is crucial for enhancing the reasoning and alignment of Large Language Models. The massive data and complex execution flows inherent…
SemiSAM-O1: Pushing the Boundary of Annotation-Efficient Medical Image Segmentation with Generalist Knowledge Fusion
Yichi Zhang, Le Xue, Bichun Xu +6
Semi-supervised learning (SSL) has become a promising solution to alleviate the annotation burden of deep learning-based medical image segmentation models. While recent advances in…
Developing Foundation Models for Universal Segmentation from 3D Whole-Body Positron Emission Tomography
Yichi Zhang, Le Xue, Wenbo Zhang +16
Positron emission tomography (PET) is a key nuclear medicine imaging modality that visualizes radiotracer distributions to quantify in vivo physiological and metabolic processes, p…
SegAnyPET: Universal Promptable Segmentation from Positron Emission Tomography Images
Yichi Zhang, Le Xue, Wenbo Zhang +5
Positron Emission Tomography (PET) is a powerful molecular imaging tool that plays a crucial role in modern medical diagnostics by visualizing radio-tracer distribution to reveal p…
Universality Reconsidered: Rethinking the Validation of Foundation Models for General-Purpose 3D Medical Segmentation
Yichi Zhang, Feiyang Xiao, Le Xue +6
Foundation models have emerged as a transformative paradigm in 3D medical imaging, with the promise of unified quantitative analysis across diverse targets and imaging modalities.…