4 papers · 1 filter
Orthogonal Witness Control for Muon Optimization via Sigmoid Spectral Reshaping
Dat Phi Van, Ngo Vu Minh, Tuc Nguyen +3
Matrix-valued optimizers such as Muon exploit the spectral structure of neural network updates through Newton--Schulz orthogonalization, but their near-flattening of the singular s…
Spectral Flattening Is All Muon Needs: How Orthogonalization Controls Learning Rate and Convergence
Tien-Phat Nguyen, Truong Nguyen, Minh-Phuc Truong +3
Muon orthogonalizes the momentum buffer before each update, replacing its singular values with ones via Newton-Schulz iterations. This simple change lets Muon tolerate far larger l…
BSO: Safety Alignment Is Density Ratio Matching
Tien-Phat Nguyen, Truong Nguyen, Thin Nguyen +3
Aligning language models for both helpfulness and safety typically requires complex pipelines-separate reward and cost models, online reinforcement learning, and primal-dual update…
Sharpness-Guided Group Relative Policy Optimization via Probability Shaping
Tue Le, Linh Ngo Van, Trung Le
Reinforcement learning with verifiable rewards (RLVR) has become a practical route to improve large language model reasoning, and Group Relative Policy Optimization (GRPO) is a wid…