Semantic Lenia: Emergence of Homeostatic Solitons within the Semantic Space of Large Language Models

Abstract:We introduce Semantic Lenia, an artificial life framework that transforms Large Language Model (LLM) inference from a static optimization problem into a continuous, closed-loop dynamical system. By establishing a non-linear homeostatic feedback loop to dynamically balance semantic attraction and syntactic repulsion, we demonstrate the emergence of ``Homeostatic Solitons''-metastable semantic structures that actively resist repetitive crystallization. Our exhaustive parameter sweeps map a critical ``Habitable Ridge'' where applied steering forces balance the model's intrinsic syntactic inertia. This approach successfully maintains generative trajectories in a numerically sensitive critical regime, triggering profound abductive leaps without structural collapse, and reveals a capacity-dependent scaling trend in the syntactic inertia across different model sizes.

18 pages, 6 figures. Code, datasets, and interactive phase diagrams are available at this https URL

Computation and Language (cs.CL); Artificial Intelligence (cs.AI); Cellular Automata and Lattice Gases (nlin.CG)

arXiv:2608.11657 [cs.CL]

(or arXiv:2608.11657v2 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2608.11657 Focus to learn more arXiv-issued DOI via DataCite

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