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LLMs can be made far more efficient at code editing by having them focus on generating concise "edit sketches," while smaller models handle the less demanding task of applying those sketches to the original code.
Code LLMs are surprisingly good at memorizing gibberish secrets, thanks to quirks in how they tokenize code.
