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LLMs can learn new tasks without forgetting old ones, thanks to a memory-aware replay strategy that selectively rehearses important examples.
Unlock $O(T^{1/2})$ regret for non-monotone DR-submodular maximization with just one gradient query per round by cleverly linearizing the problem.
