Six Papers Theoretically Explaining Neural Scaling Laws

A curated collection of six papers offers theoretical explanations for scaling laws across pretraining, RL, test-time compute, and agent counts, summarizing key mechanisms such as data manifold geometry and spectral decay.

2026-10-04 ~ 2026-10-04 · 3 related posts

• A curated list of papers explaining pretraining, RL and test-time compute scaling laws — burny_tech · 2026-10-04
• A curated list of papers explaining why scaling laws work — burny_tech · 2026-10-04

1 near-duplicate retellings: burny_tech