Partial Answer of How Transformers Learn Automata
arXiv:2504.20395v2
Originality Incremental advance
AI Analysis
This addresses a foundational problem in understanding how Transformers learn computational structures, though it appears incremental in method.
The paper tackles the problem of simulating finite automata with Transformers by introducing a framework using representation-theoretic semidirect products and Fourier modules, achieving more efficient implementations.
We introduce a novel framework for simulating finite automata using representation-theoretic semidirect products and Fourier modules, achieving more efficient Transformer-based implementations.