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LLMs can reason more effectively by directly tracking their own belief in the correct answer throughout the reasoning process, enabling more targeted policy updates.
Navigate massive codebases with LLMs using a "scouting-first" approach that slashes token consumption without sacrificing reasoning accuracy.