English(EN) SWE-Clar: Can Coding Agents Clarify Incomplete Client Requirements and Deliver Greenfield Software?

新的SWE-Clar基准测试AI编码代理的需求澄清能力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-26 04:00

一个名为SWE-Clar的新基准已被开发出来，用于评估编码AI代理澄清不完整客户需求和交付全新软件的能力。该基准使用了来自Upwork的100个真实世界软件开发任务，每个任务价值超过4000美元，并包含一个需求澄清的多轮交互阶段，随后是代码实现和测试。对包括GPT-6 Astra在内的九个前沿模型的实验表明，即使是表现最好的模型，任务通过率也仅为67%，这凸显了在自由职业环境中自主交付软件的难度。 AI

影响该基准可以通过提供一个标准化的需求澄清评估方法，来加速开发更强大的软件开发AI代理。

排序理由该集群包含一篇介绍AI代理新基准的学术论文。[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 →

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Signal score: 13 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 该集群包含一篇介绍AI代理新基准的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: paper, product; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: Same-day; Cluster formed today. Ranking reflects the current source set at time of score.

完整方法见我们的编辑标准。

报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Jialei Li, Dingxian Wang, Xiaoyan Zhao, Yimeng Bai, Xuanyi Zhu, Yang Zhang, Chao Yin, Wentao Shi, Ganesh Prabhu, Karthik Gomadam Rajagopal, Brett Levert, Darvin Yi, Andrew Rabinovich, Zhao Chen · 2026-10-26 04:00

SWE-Clar：编码代理能否澄清不完整的客户需求并交付全新的软件？

arXiv:2610.31854v1 Announce Type: cross Abstract: Greenfield software development in freelance settings requires coding agents to turn incomplete client requests into working software. This makes requirement clarification essential, yet clients may be unable to provide continuous…

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报道来源 [1]

SWE-Clar：编码代理能否澄清不完整的客户需求并交付全新的软件？

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