Neither Parallel Nor Sequential: How DiffusionGemma Actually Commits Tokens
Open diffusion language models are marketed as parallel, non-autoregressive decoders, yet the order in which a shipped checkpoint actually commits its tokens is almost never measured. We instrument DiffusionGemma 26B, a masked discrete-diffusion mixture-of-experts model built on Gemma 4, hooking its sampler's accept step to record which canvas positions commit, when, and at what confidence. Across a 686-prompt, six-regime probe suite we find that its decoding is neither parallel nor block-autoregressive: it follows a partial left-to-right commit bias whose apparent strength depends almost entirely on the granularity at which you look. Order is weak token by token and strengthens smoothly ...
| Authors | Ali Asaria, Tony Salomone, Deep Gandhi |
|---|---|
| Primary category | cs.LG |
| Published | 12 June 2026 |
| Last updated at source | 12 June 2026 |
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