4 citations · 7 across the 12 of their papers we have counts for
12 papers
Complex Problem Solving in Large Language Models: A Statistical Control Survey and Diagnostic Framework
Jiazhang Cai, Tao Wang, Ruidong Zhang +35
Complex problem solving (CPS) with large language models (LLMs) is often framed as a matter of stronger reasoning or longer generation. Yet early-step error amplification, prompt b…
Knowledge Cascade: Reverse Knowledge Distillation on Nonparametric Multivariate Functional Estimation
Luyang Fang, Haoran Lu, Yongkai Chen +2
As machine learning models and datasets continue to grow, developing complex models has become increasingly computationally demanding. Knowledge distillation reduces deployment cos…
Multi-Teacher Knowledge Distillation via Teacher-Informed Mixture Priors
Luyang Fang, Yongkai Chen, Jiazhang Cai +2
Knowledge distillation is a powerful method for model compression, enabling the efficient deployment of complex deep learning models (teachers), including large language models. Ho…
NeuroMAS: Multi-Agent Systems as Neural Networks with Joint Reinforcement Learning
Haoran Lu, Luyang Fang, Wenxuan Zhong +1
Multi-agent language systems are often built as hand-designed workflows, where agents are assigned semantic roles and communication protocols are specified in advance. We propose N…
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…