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cs.LG2026
LoRA-Muon: Spectral Steepest Descent on the Low-Rank Manifold
Franz Louis Cesista, Katherine Crowson, Cédric Simal +1
Low-Rank Adaptation (LoRA) significantly reduces compute and memory costs for finetuning Deep Learning models but is often harder to tune than dense training: when using factor-wis…
cs.LG2025★ 1 cited
Training Transformers with Enforced Lipschitz Constants
Laker Newhouse, R. Preston Hess, Franz Cesista +3
Neural networks are often highly sensitive to input and weight perturbations. This sensitivity has been linked to pathologies such as vulnerability to adversarial examples, diverge…