Author

Nicolas Dufour

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Preprint Sep 2026

Diffusable Latents from Structure-Agnostic Distillation

Distilling pretrained foundation models into an autoencoder bottleneck improves latent diffusability, enabling diffusion models to converge faster and reach higher sample quality. Standard distillation aligns the latent at each position to a co-located teacher feature, tying the latent layout to the teacher's. We show...

Adrien Ramanana Rahary, Nicolas Dufour, Patrick Pérez et al. · 0 citations

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A two-stage distillation pipeline first trains the causal student to match the teacher’s trajectories under a chunk-wise causal attention mask, then applies Distribution Matching Distillation (DMD) with backward simulation to close the few-step quality gap.

Nathaniel Cohen, Nicolas Dufour, Amélie Royer et al. · 0 citations