Is inference-time stability regulation sufficient to prevent collapse and unsafe behavior in sequence models under regime shift?
About TwoQuarks
TwoQuarks defines model collapse as a failure of inference-time stability rather than capacity.
It introduces a modular control layer that monitors internal pre-instability signals and applies targeted interventions during execution—without modifying model parameters, policies, or training objectives.
Framework
A modular control layer for inference-time stability. Six flavors, one coherent system.
Six modular flavors that monitor pre-instability signals and apply targeted interventions during execution—without modifying model parameters, policies, or training objectives.
Empirical validation of isomeric polarization and the TwoQuarks analogy across production LLMs.
Cross-architecture PfV validation across Claude Haiku and GPT-4o-mini. Statistically significant regime separation (p < 0.05, 5,000-permutation null) with control negative at L₃ = 0.000 in both architectures.