TextNCA: Neural Cellular Automata for Language Modeling via Hierarchical Local Attention
Can a strictly local, iterated, weight-shared computation primitive support language modelling, and which of those three properties actually drives the model's behaviour? We define \textsc{TextNCA}, a 1D causal windowed-attention realisation of the Neural Cellular Automaton primitive, and study a hierarchical variant that cascades three stages with windows $w \in \{8, 32, 128\}$ and $T_s$ shared-weight iterations per stage, all on WikiText-103 at roughly 30M parameters and 60k training steps. The model does not match a parameter-matched Transformer at this scale (Hier-TextNCA $60.3$ vs.\ Transformer-6L $52.8$ and Transformer-12L $44.7$ PPL), so we treat it as an analytical probe rather th...
| Authors | Avni Mittal, Avinash Anand, Ashutosh Kumar et al. |
|---|---|
| Primary category | cs.CL |
| Published | 3 August 2026 |
| Last updated at source | 3 August 2026 |
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