A Mathematical Framework for Transformer Circuits (2021)

Researchers developed a mathematical framework to reverse-engineer transformer language models, focusing on attention-only models with two layers or less. They identified 'induction heads' that explain in-context learning in these small models, with these heads only developing in models with at least two attention layers.