ZetaGPT: A Reference Implementation of Positional--Encoding--Free State--Space--Attention Language Models
This work explores a language model architecture that integrates causal state-space equations to implicitly encode positional information before attention computation, and establishes a compact, reproducible reference implementation for the development and empirical study of positional-encoding-free language models.