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User feedback prediction can be learned, revealing critical performance gaps in AI assistants that traditional evaluation methods overlook.
LLMs can beat state-of-the-art tensor compilers on individual subgraphs, but struggle with consistency, revealing a path to unlock their full potential through targeted training.
