4 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…
Memory-Statistics Tradeoff in Continual Learning with Structural Regularization
Haoran Li, Jingfeng Wu, Vladimir Braverman
We study the statistical performance of a continual learning problem with two linear regression tasks in a well-specified random design setting. We consider a structural regulariza…
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…