The original title is "How transparent is DiffusionGemma (and why it matters)"

Short summary

Researchers audited DiffusionGemma's transparency, finding variable transparency comparable to Gemma despite larger opaque serial depth. They introduce algorithmic vs variable transparency distinction, showing diffusion models are less algorithmically transparent than autoregressive LLMs due to parallel token generation. The methodology and 24 open problems serve as precedent for evaluating future latent-reasoning architectures.

• •Transparency audit shows DiffusionGemma's intermediate vectors are interpretable, reducing effective opacity to Gemma levels
• •Distinguishes variable transparency (snapshots) from algorithmic transparency (understanding the process); diffusion models rank lower on the latter
• •Proposes audit methodology as template for evaluating future latent-reasoning models; includes 24 open research problems

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