From Truncation to Commitment: Persistent Context in Uniform Discrete Diffusion
Uniform-state discrete diffusion models update all tokens in parallel while keeping every position revisable. Even when the commonly used top-$p$ rule leaves only one candidate at a position, that choice affects only the current reverse step and can be revised at the next sampling step. We ask what changes when selected hypotheses instead become persistent context for later predictions. We…
We haven't written up this one. arXiv cs.AI has the full story — the link below goes straight to it.