AWhat changed
Aligned projected noisy-input hidden features with clean-image features from a pretrained visual encoder as an auxiliary loss for diffusion and flow transformers.
Scientific scope
Aligned projected noisy-input hidden features with clean-image features from a pretrained visual encoder as an auxiliary loss for diffusion and flow transformers. External representation pretraining and ordinary denoising/flow objectives are inherited. Reported training-step savings depend on the baseline, target metric and setup; they are not end-to-end compute savings including the teacher's pretraining or universal convergence guarantees.
Evidence
The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. External representation pretraining and ordinary denoising/flow objectives are inherited. Reported training-step savings depend on the baseline, target metric and setup; they are not end-to-end compute savings including the teacher's pretraining or universal convergence guarantees.
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.
Full scientific record · Browse contribution grades · Request a correction