DynMuon dynamically schedules the spectral exponent p in Muon-style updates according to curvature, noise, and training stage, yielding lower validation loss with 10-26% fewer steps than fixed Muon.
Curtis, and Jorge Nocedal
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
AS-LoRA adaptively chooses which LoRA factor to update per layer and round using a curvature-aware second-order score, eliminating reconstruction error floors and improving performance in DP federated learning.
LBW-Guard is a bounded autonomous control layer above AdamW that improves stability, reduces perplexity, and speeds up training for Qwen2.5 models under learning-rate stress on WikiText-103.
citing papers explorer
-
DynMuon: A Dynamic Spectral Shaping View of Muon
DynMuon dynamically schedules the spectral exponent p in Muon-style updates according to curvature, noise, and training stage, yielding lower validation loss with 10-26% fewer steps than fixed Muon.
-
Adaptive Selection of LoRA Components in Privacy-Preserving Federated Learning
AS-LoRA adaptively chooses which LoRA factor to update per layer and round using a curvature-aware second-order score, eliminating reconstruction error floors and improving performance in DP federated learning.
-
Learn-by-Wire Training Control Governance: Bounded Autonomous Training Under Stress for Stability and Efficiency
LBW-Guard is a bounded autonomous control layer above AdamW that improves stability, reduces perplexity, and speeds up training for Qwen2.5 models under learning-rate stress on WikiText-103.