Author

François Fleuret

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Preprint Oct 2026

Pooling Representation Autoencoders for Efficient Diffusion

Representation Autoencoders (RAEs) generate images from pre-trained visual fea- tures, but their dense token grids make generative modeling expensive. Motivated by local feature correlations, we introduce PoolDINO, a learned affine pooling operator that merges neighboring tokens. Training the pooling operator jointly w...

Ramón Calvo-González, Youssef Saied, François Fleuret · 0 citations

#artificial intelligence Preprint Sep 2026

Let It Go or Learn to Self-Correct: Continuous Diffusion for Constrained Discrete Tasks

Denoising Diffusion Probabilistic Models (DDPMs) generate samples by starting from noise and repeatedly denoising while keeping each update close to the current noisy state. This behavior is effective in many continuous domains, but its role is less clear for globally constrained discrete tasks, such as Sudoku, graph c...

M. Drozdova, Stéphane Liem Nguyen, François Fleuret · 0 citations