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LLMs struggle with code migration when APIs evolve, but KCoEvo's knowledge graph augmentation boosts migration accuracy and execution success.
Chain-of-Thought prompting doesn't always improve LLMs' ability to solve discrete optimization problems, and surprisingly, "disordered" datasets can sometimes boost performance on simpler tasks.
