Training ideas

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

Unverified 2026

Criticality-controlled sparsity schedule

Use the min-plus phase transition as a training-time controller: begin near p = 1/2 to preserve the initial active-state fraction across depth, then move above or below criticality to deliberately remove or create sparse pathways. The controller uses a measurable state variable, the activation zero fraction, rather than an arbitrary regularization coefficient.

Useful6/10
Difficulty5/10
Novelty9/10
Paper: Finite-depth scaling and an exact Bernoulli-leaf identity for the min-plus process on the binary tree arXiv:2608.12295