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

> 标题为英语

> 全文为英语

**Published:** 2026年9月22日
**Author:** Kabeh Mohsenzadegan, Vahid Tavakkoli, Kyandoghere Kyamakya
**Source:** arXiv — cs.AI
**Language:** en-US
**HTML:** https://aiqazaqstan.com/zh/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…

> 内容来自原始来源： **arXiv — cs.AI**
> [在 arXiv — cs.AI 阅读全文](https://arxiv.org/abs/2609.21139)

**标签：** #arXiv

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