muon
for ML optimization engineers
Why this scored 10
every term, weightedIts fastest-moving item, measured against the pace of its own source
Whether that velocity is itself speeding up, as a per-hour rate
How many independent communities its own items come from
Decays to zero over 14 days, counted from when we first saw it
Subtracted once something is big and old — sized by its biggest item, aged from when we first saw it
Weights are hand-tuned, not learned — we're calibrating them against realized trends as history accumulates. On an entity's first sighting there's no previous reading to compare against, so acceleration starts from a neutral prior rather than a measurement, and velocity falls back to engagement over its whole lifetime until a second reading exists. Full methodology
Signal history
7-day window (free)The evidence
The live items this entity's score aggregates — every community independently talking about it right now. This is the corroboration, shown, not claimed.
- 119
Spectral Allocation: Why Muon Outperforms Adam, and How to Improve Muon
Muon optimizer shows better convergence than Adam, suggesting a switch for faster model training. · for ml engineers
arxivSteadyai60d ago - 219
Muon meets Tamed Langevin: Momentum Preconditioning beyond Convex and gradient-Lipschitz Potentials
Introduces momentum preconditioning methods extending beyond convex and Lipschitz assumptions. · for ML optimization engineers
arxivSteadyai24d ago - 39
Muon Meets Mamba: Spectral Optimization for State Space Models
Spectral optimization method · for researchers
arxivSteadyscience82d ago - 47
When Does Muon Help Agentic Reinforcement Learning?
Muon helps reinforcement learning · for ai researchers
arxivSteadyai98d ago - 57
Sign compression for Muon: SignMuon, MuonSign, and the Limits of Error Feedback
Sign compression for muon · for hardware engineers
arxivSteadyhardware84d ago