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Can continuous tokens be treated as embeddings or latent representations for downstream applications like clustering or similarity search or just supervised learning in general? What exactly is the difference of let's say DINOv2 embeddings vs Cosmos when you have the causal setup?
The text was updated successfully, but these errors were encountered:
Thanks for the great work!
Can continuous tokens be treated as embeddings or latent representations for downstream applications like clustering or similarity search or just supervised learning in general? What exactly is the difference of let's say DINOv2 embeddings vs Cosmos when you have the causal setup?
The text was updated successfully, but these errors were encountered: