Generative Representation Learning for Scalable Latent Tokenization
A generative tokenizer avoids representation collapse and reaches FID-50K 2.18 with JiT-L.
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A generative tokenizer avoids representation collapse and reaches FID-50K 2.18 with JiT-L.
Data-space iteration enables few-step image generation without tuning a flow timestep schedule.
StreamMAE adapts masked autoencoders so pretraining works on continuous video streams without global shuffling.
Entities are extracted by the model from each article. First seen , last mentioned . Watching keeps it in this browser only (no account); the watchlist page and dashboard alerts use it.
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