Unverified50% confidenceFactExact time
General leaderboards such as MMLU and GSM8K measure average performance across a broad range of tasks, and their scores often correlate only weakly with specific business metrics.
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11/2/2026
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VerifiedOn mainstream evaluations such as MMLU, HumanEval, and GSM8K, the score gaps among leading large models are often only a few percentage points.76% similarUnverified模型在标准化评测基准（如HumanEval、MMLU）上的高分表现与真实工作场景中的可靠性之间存在显著差距68% similarUnverified研究表明，即使在 GSM8K 或 MATH 数据集上接近满分的模型，面对稍作变形或需要跨领域组合的问题时性能下降可达30-50个百分点67% similarUnverifiedAutomatically generated rubrics may still depend on the quality of the initial LLM, and may require additional calibration in certain highly specialized domains; the 9% and 4.5% improvements were achieved only on specific benchmarks, and generalization capability still needs verification.64% similarUnverifiedExisting model evaluation frameworks (such as HumanEval, MBPP, and various Arena benchmarks) primarily measure capability ceilings and rarely incorporate end-to-end task completion rate as an evaluation dimension.64% similar
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