It's surprising that you're able to get this much generalization out of seemingly such a small set, right? I think part of the reason is because we are leveraging these pre-trained models. And so the MLP just needs to learn how to map something that is similar to the clip image embedding space. But again, also like, we don't know how well it's going to generalize out of natural scenes.

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