What needs to go right for an induction head? A mechanistic study of in-context learning circuits and their formation

arXiv:2404.07129v1 Announce Type: new
Abstract: In-context learning is a powerful emergent ability in transformer models. Prior work in mechanistic interpretability has identified a circuit element that may be critical for in-context learning -- the induction head (IH), which performs a match-and-copy operation. During training of large transformers on natural language data, IHs emerge around the same time as a notable phase change in the loss. Despite the robust evidence for IHs and this interesting coincidence with the phase change, relatively …

abstract arxiv circuits context copy cs.lg element head in-context learning interpretability match prior study transformer transformer models type work