Training ideas

Curricula, sampling schedules, pseudo-labeling and multi-task mixing, with the standard training recipe as the control.

△ Mechanism confirmed, baseline not beaten 2026

Lyapunov-Calibrated Multiplicative Noise

Use measured local Jacobian growth to set the variance of dropout, feature noise, or stochastic-depth perturbations, implementing the paper's fluctuation-response idea that multiplicative noise is tied to the positive scrambling or Lyapunov rate. The controller maintains a target growth regime instead of applying a fixed noise schedule throughout training. It predicts a stability transition when the estimated growth rate crosses zero and a variance-growth proportionality that can be tested…

Useful7/10
Difficulty4/10
Novelty6/10
Paper: Effective Field Theory of Operator Scrambling from Strong-to-Weak Symmetry Breaking arXiv:2607.24925