7 papers
Wahkon: A Statistically Principled Deep RKHS Superposition Network
Yongkai Chen, Wenxuan Zhong, Ping Ma
Deep learning excels at prediction but often lacks finite-sample guarantees and calibrated uncertainty; RKHS (Reproducing Kernel Hilbert Space)-based methods provide those guarante…
Quantum Statistical Bootstrap
Yongkai Chen, Ping Ma, Wenxuan Zhong
The bootstrap is a foundational tool in statistical inference, but its classical implementation relies on Monte Carlo resampling, introducing approximation error and incurring high…
A Single Revision Step Improves Token-Efficient LLM Reasoning
Yingchuan Zhang, Terry Ma, Wenxuan Zhong +1
Large language models (LLMs) achieve higher accuracy on challenging reasoning tasks by scaling test-time compute through multiple trajectory sampling. However, standard aggregation…
DCMM-Transformer: Degree-Corrected Mixed-Membership Attention for Medical Imaging
Huimin Cheng, Xiaowei Yu, Shushan Wu +7
Medical images exhibit latent anatomical groupings, such as organs, tissues, and pathological regions, that standard Vision Transformers (ViTs) fail to exploit. While recent work l…
Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges
Haoran Lu, Luyang Fang, Ruidong Zhang +47
Due to the remarkable capabilities and growing impact of large language models (LLMs), they have been deeply integrated into many aspects of society. Thus, ensuring their alignment…
S2MNet: Speckle-To-Mesh Net for Three-Dimensional Cardiac Morphology Reconstruction via Echocardiogram
Xilin Gong, Yongkai Chen, Shushan Wu +3
Echocardiogram is the most commonly used imaging modality in cardiac assessment duo to its non-invasive nature, real-time capability, and cost-effectiveness. Despite its advantages…