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Forget catastrophic forgetting: sparse memory finetuning, enhanced with a KL-divergence-based update rule, lets LLMs learn continuously without trashing old knowledge.
Masked diffusion models can finally achieve faster inference without sacrificing generation quality, thanks to a clever speculative decoding scheme.
