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Instruct-to-Act reveals that decoupling planning from control can enhance action execution speed and flexibility in complex environments without sacrificing performance.
Models may give clearer instructions, but they fail to engage learners deeply, resulting in passive instruction-following rather than active understanding.
Models are substantially better at pairwise self-verification than independent scoring, unlocking a more efficient and accurate approach to test-time scaling for complex reasoning.