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Current LLMs can barely translate natural-language claims into formal statements, achieving only 11.5 on a critical task that could unlock automated theoretical research.
CurateEvo transforms data curation from a static process into a dynamic, failure-driven evolution, significantly boosting performance and efficiency in LLM training.
Stop blindly throwing compute at agent harnesses: effective feedback, not raw tokens, dictates scaling laws.