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MAG leverages abundant unlabeled multi-modal data to boost few-shot learning performance, achieving significant gains in label-scarce environments.
Simplax not only preserves the integrity of categorical diffusion processes but also enhances generative performance, achieving record-breaking results in both text and puzzle generation tasks.
