Jul 2026
Induction in Both Directions: A Mechanistic Analysis of In-Context Learning in Masked Diffusion Language Models
This work studies how diffusion language models implement induction, a mechanism behind in-context learning in which the model finds a repeated context and copies the token that followed it, and compares attention-only AR models and absorbing-mask DLMs with matched architectures.
Andy Catruna, Emilian Radoi
· arXiv.org · 0 citations