BWhat changed
Paired frozen pretrained representation encoders with trained decoders and adapted diffusion training to high-dimensional semantic latents using width, noise-schedule and decoder-robustness changes.
Scientific scope
Paired frozen pretrained representation encoders with trained decoders and adapted diffusion training to high-dimensional semantic latents using width, noise-schedule and decoder-robustness changes. Inherits pretrained DINO/SigLIP/MAE encoders, diffusion transformers, alignment work and prior DDT inspiration. Acquired delta is the RAE integration/design study; no universal default/optimality claim or independently certified theorem. Extra teacher pretraining and decoder training remain costs.
Evidence
The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Inherits pretrained DINO/SigLIP/MAE encoders, diffusion transformers, alignment work and prior DDT inspiration. Acquired delta is the RAE integration/design study; no universal default/optimality claim or independently certified theorem. Extra teacher pretraining and decoder training remain costs.
Contributors
- Source-listed authors and technical contributors · SCIENCE: Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.
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