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English(EN) SWE-bench needs 90% of tasks for reliable agent benchmark results A replay analysis of three LLM agent benchmarks finds the safe partial-run fraction ranges fro

LLM 漏洞检测在真实代码上表现不佳;SWE-bench 需要 90% 的任务才能保证可靠性

研究人员发现,虽然 LLM 漏洞检测在利用结构先验的合成基准测试上可以达到 100% 的召回率,但在真实代码上的性能会急剧下降。此外,对 LLM 代理基准测试的另一项分析表明,SWE-bench 需要大约 90% 的任务才能产生可靠的结果,并且没有找到通用的局部运行捷径。 AI

影响 强调了当前 LLM 安全评估和基准测试可靠性的局限性,表明需要更稳健的测试方法。

排序理由 该集群讨论了对 LLM 基准测试和检测方法分析的结果,属于研究类别。

在 Mastodon — fosstodon.org 阅读 →

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LLM 漏洞检测在真实代码上表现不佳;SWE-bench 需要 90% 的任务才能保证可靠性

报道来源 [2]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    LLM vulnerability detection hits 100% recall, then collapses on real code Structural priors lift LLM vulnerability recall from 20% to 100% on synthetic benchmar

    LLM vulnerability detection hits 100% recall, then collapses on real code Structural priors lift LLM vulnerability recall from 20% to 100% on synthetic benchmarks, but real CVE data exposes a 51-point collapse. https://www. notatechguy.com/llm-vulnerabil ity-detection-hits-100-re…

  2. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    SWE-bench needs 90% of tasks for reliable agent benchmark results A replay analysis of three LLM agent benchmarks finds the safe partial-run fraction ranges fro

    SWE-bench needs 90% of tasks for reliable agent benchmark results A replay analysis of three LLM agent benchmarks finds the safe partial-run fraction ranges from 15% to over 95%, with no universal shortcut. https://www. notatechguy.com/swe-bench-need s-90-of-tasks-for-reliable-ag…