4 citations · 9 across the 7 of their papers we have counts for
8 papers
DTS: Enhancing Large Reasoning Models via Decoding Tree Sketching
Zicheng Xu, Xiuyi Lou, Guanchu Wang +6
Large Reasoning Models (LRMs) achieve remarkable inference-time improvements through parallel thinking. However, existing methods rely on redundant sampling of reasoning trajectori…
Self-ensemble: Mitigating Confidence Mis-calibration for Large Language Models
Zicheng Xu, Guanchu Wang, Guangyao Zheng +4
Although Large Language Models (LLMs) perform well in general fields, they exhibit a confidence distortion problem on multi-choice question-answering (MCQA), particularly as the nu…
Towards Fair Medical AI: Adversarial Debiasing of 3D CT Foundation Embeddings
Guangyao Zheng, Michael A. Jacobs, Vladimir Braverman +1
Self-supervised learning has revolutionized medical imaging by enabling efficient and generalizable feature extraction from large-scale unlabeled datasets. Recently, self-supervise…
Demographic Predictability in 3D CT Foundation Embeddings
Guangyao Zheng, Michael A. Jacobs, Vishwa S. Parekh
Self-supervised foundation models have recently been successfully extended to encode three-dimensional (3D) computed tomography (CT) images, with excellent performance across sever…
A framework for dynamically training and adapting deep reinforcement learning models to different, low-compute, and continuously changing radiology deployment environments
Guangyao Zheng, Shuhao Lai, Vladimir Braverman +2
While Deep Reinforcement Learning has been widely researched in medical imaging, the training and deployment of these models usually require powerful GPUs. Since imaging environmen…
Multi-environment lifelong deep reinforcement learning for medical imaging
Guangyao Zheng, Shuhao Lai, Vladimir Braverman +2
Deep reinforcement learning(DRL) is increasingly being explored in medical imaging. However, the environments for medical imaging tasks are constantly evolving in terms of imaging…
Asynchronous Decentralized Federated Lifelong Learning for Landmark Localization in Medical Imaging
Guangyao Zheng, Michael A. Jacobs, Vladimir Braverman +1
Federated learning is a recent development in the machine learning area that allows a system of devices to train on one or more tasks without sharing their data to a single locatio…
Selective experience replay compression using coresets for lifelong deep reinforcement learning in medical imaging
Guangyao Zheng, Samson Zhou, Vladimir Braverman +2
Selective experience replay is a popular strategy for integrating lifelong learning with deep reinforcement learning. Selective experience replay aims to recount selected experienc…