English(EN) Between Spoilers and Guesswork: Avoiding Over-Specification in Coding Benchmarks

新论文提出解决方案，应对AI编码基准测试的过度指定问题

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-19 04:00

一篇新研究论文探讨了AI编码基准测试中过度指定和指定不足的挑战。作者提出了推导出简约提示的方法，以避免泄露可能导致“剧透”并降低基准测试效用的真实信息。该论文审查了SWE-bench Pro、FEA-bench、Doc2Feat-bench和Multi-SWE-bench等现有基准测试，并提出了在提供必要指导和防止解决方案绕过核心评估指标之间取得平衡的技术。 AI

影响这项研究旨在提高AI编码基准测试的可靠性和持久性，从而更准确地评估AI模型的能力。

排序理由在arXiv上发表的研究论文，讨论了AI基准测试的改进。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

本文如何被排名

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Yuanzhe Liu, Bastian Lipka, Avraham Shinnar, Jatin Ganhotra, Yao Ma, Martin Hirzel · 2026-10-19 04:00

剧透与猜测之间：避免编码基准测试中的过度指定

arXiv:2610.22760v1 Announce Type: new Abstract: Benchmarks drive AI progress, but are hampered by task under-specification and over-specification. Task under-specification causes guesswork, where solutions have to make things up, or worse, resort to contamination or reward hackin…

本文如何被排名

报道来源 [1]

剧透与猜测之间：避免编码基准测试中的过度指定

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