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

arXiv: https://arxiv.org/abs/2608.11657 · HTML: https://mlsanity.com/paper/2608.11657/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 14 references that are in the map.
- First posted on arXiv 12 Aug 2026.

## Builds on (most cited first, 7 of 7)

- [Classifier-Free Diffusion Guidance](https://mlsanity.com/paper/2207.12598/) (2022)
- [The Curious Case of Neural Text Degeneration](https://mlsanity.com/paper/1904.09751/) (2019)
- [Representation Engineering: A Top-Down Approach to AI Transparency](https://mlsanity.com/paper/2310.01405/) (2023)
- [DExperts: Decoding-Time Controlled Text Generation with Experts and Anti-Experts](https://mlsanity.com/paper/2105.03023/) (2021)
- [GeDi: Generative Discriminator Guided Sequence Generation](https://mlsanity.com/paper/2009.06367/) (2020)
- [Lenia - Biology of Artificial Life](https://mlsanity.com/paper/1812.05433/) (2018)
- [Lenia and Expanded Universe](https://mlsanity.com/paper/2005.03742/) (2020)

## Abstract (arXiv)

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.