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Test-Time Compute improves answer quality by adding sampling, search, or reflection steps at the inference stage, for example Self-Consistency sampling multiple reasoning paths in parallel and then voting, and Reflexion letting the Agent self-criticize and retry; each sample and each parallel path corresponds to a complete forward computation.
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10/14/2026
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UnverifiedThe evaluation closed loop is a typical application of the test-time compute research direction, improving output quality by investing more computation during the inference stage rather than relying on larger model parameters.75% similarUnverifiedTest-time compute is essentially a strategy of trading more FLOPs for higher intelligence performance.75% similarUnverifiedMore effective methods for testing AI logical reasoning capabilities include multi-step reasoning chains, contextual consistency tracking, counterfactual hypotheses, and self-correction ability74% similarUnverified多路推理验证的核心思路是让正确答案能够通过多条推理路径被推导出来,而错误答案往往是偶发性的,可通过多次采样筛除73% similar
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