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Synapse
January 24, 20260 citationsOpen Access

When Recognition Does Not Imply Inhibition

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DTDanilo Tavella

Key Points

  • This work aims to understand how recognition of constraints in AI does not lead to effective inhibition in operations.
  • Analyzed structural failure modes in large language models.
  • Reframed behavior as regime transitions between recognition and execution.
  • Explored non-parametric limits to controllability.
  • Identified a disconnect between semantic recognition and operational actions.
  • Highlighted implications for AI safety and system design.

Abstract

This technical note analyzes a structural failure mode in large language models, where semantic recognition of constraints does not translate into operational inhibition. The work reframes this behavior as a regime transition without a faithful embedding between diagnostic and execution regimes, highlighting non-parametric limits to controllability relevant to AI safety and system architecture.

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Cite This Study

Danilo Tavella (2025) studied this question.

synapsesocial.com/papers/69746187bb9d90c67120b5ebhttps://doi.org/10.5281/zenodo.18338330
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