@kyutai_labs: Many generative models work in an autoencoder's latent space; They train faster and generate better when this space is …
Summary
Kyutai Labs teasers a paper on organizing autoencoder latent spaces by distilling a pretrained model into them, asking how this can work when the source and target spaces have different structures. Likely a research preprint on improving generative model training via better-structured latent representations.
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Cached at: 10/02/26, 04:44 PM
Many generative models work in an autoencoder’s latent space; They train faster and generate better when this space is well organized. One way to organize it is distilling a pretrained model into it. But how can it work when the two spaces have different structures? https://t.co/AxbBQIP0ST
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