Papers explore Muon optimizer geometry and matrix factorization performance

Two new arXiv papers analyze Muon, an optimizer using approximate orthogonalization. One introduces "Muse" to study Muon's representation geometry beyond normalized momentum; the other reassesses Muon for matrix factorization, finding it can outperform Adam/AdamW in LLM training.