The Kinetics of Training: A Driven-Nucleation Rate Law for Emergence, Plasticity Loss, and Circuit Control in Language Models
A capability appears in a language model when the last parts of its circuit align in one stochastic attempt, and getting all but one right is worth nothing. We show this no-partial-credit joint alignment is the rate-limiting step of capability formation. Two fingerprints: in a shortcut-free apparatus a five-part circuit missing three waits as long as a three-part circuit missing three (1.19-1.37), so the wait counts missing parts, not size; and on Pythia across seven capabilities and three scale
Record details
Published: 29 July 2026
Source: arXiv cs.LG
Category: Research
Topics: Regulation · Safety & alignment
Retrieved: 31 July 2026
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ethics.ai (29 July 2026), “The Kinetics of Training: A Driven-Nucleation Rate Law for Emergence, Plasticity Loss, and Circuit Control in Language Models,” evidence record 15267, https://ethics.ai/record/15267 (originally published by arXiv cs.LG).
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