3 papers
cs.LG2026
Expert Divergence Learning for MoE-based Language Models
Jiaang Li, Haibin Chen, Langming Liu +9
The Mixture-of-Experts (MoE) architecture is a powerful technique for scaling language models, yet it often suffers from expert homogenization, where experts learn redundant functi…
quant-ph2025
HQCC: A Hybrid Quantum-Classical Classifier with Adaptive Structure
Ren-Xin Zhao, Xinze Tong, Shi Wang
Parameterized Quantum Circuits (PQCs) with fixed structures severely degrade the performance of Quantum Machine Learning (QML). To address this, a Hybrid Quantum-Classical Classifi…
stat.ME2025
Noise-Adaptive Conformal Classification with Marginal Coverage
Teresa Bortolotti, Y. X. Rachel Wang, Xin Tong +3
Conformal inference provides a rigorous statistical framework for uncertainty quantification in machine learning, enabling well-calibrated prediction sets with precise coverage gua…