4 papers
Low-Dimensional High-Leverage Subspace Optimization: Beyond Full-Parameter Coupled Training for Neural Network Quantization
Peng Xia, Junbiao Pang, Zheng Huang
Low-bit quantization suffers severe accuracy degradation on compact networks, rooted in the dominant full-parameter coupled training paradigm that ignores parameter subspace hetero…
Gradient-Energy Guided Block-Wise Perturbations for Sharpness-Aware Minimization
Zhen Huang, Jiaxin Deng, Junbiao Pang
Sharpness-Aware Minimization (SAM) improves generalization by minimizing the worst-case loss in a local parameter neighborhood. Standard SAM implicitly allocates its global perturb…
Adversarial LassoNet: Robust Feature Selection via Stability-Driven Sparse Learning
Zhen Huang, Peicheng Xu, Junbiao Pang +1
Sparse feature selection is critical for high-dimensional machine learning, yet traditional -regularized methods are often brittle under observational noise and spurious co…
Which Tokens Matter? Adaptive Token Selection for RLVR with the Relative Surprisal Index
Outongyi Lv, Yanzhao Zheng, Yuanwei Zhang +5
Reinforcement learning (RL) has become a powerful tool for propelling Large Language Models (LLMs) beyond imitation-based training towards more robust reasoning capabilities. Among…