# TinyCeNN-LM: Quality-Gated Conversion of Pretrained Attention with CeNN-Inspired Cellular-Recurrent Layers

**Published:** September 22, 2026
**Author:** Kabeh Mohsenzadegan, Vahid Tavakkoli, Kyandoghere Kyamakya
**Source:** arXiv — cs.AI
**Language:** en-US
**HTML:** https://aiqazaqstan.com/en/articles/tinycenn-lm-quality-gated-conversion-of-pretrained-attention-with-cenn-i

Replacing attention in a pretrained language model is a compatibility problem: a plausible substitute may alter representations expected by later layers. TinyCeNN-LM introduces a \emph{quality-gated post-training conversion} framework using CeNN-inspired cellular-recurrent…

> From the original source: **arXiv — cs.AI**
> [Read full article at arXiv — cs.AI](https://arxiv.org/abs/2609.21139)

**Tags:** #arXiv

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