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English(EN) Longtail-SWE: High-Quality SWE Tasks for Underrepresented Languages

新的Longtail-SWE基准测试评估13种代表性不足语言的编码代理

一项名为Longtail-SWE的新基准测试已被开发出来,用于评估编码代理在13种代表性不足的编程语言中的软件工程任务。该基准测试包含20个来自GitHub issue和pull request的真实世界任务,并配有可执行环境和测试。采用了一种新颖的求解器-裁判-修复器管道来完善任务描述和测试,通过纠正可能拒绝有效替代实现或接受不正确解决方案的问题,确保更可靠的评估。 AI

影响 增强了AI编码代理的评估能力,尤其是在不太常见的编程语言方面。

排序理由 发布了用于评估AI模型的新学术基准测试。[lever_c_demoted from research: ic=1 ai=1.0]

在 Hugging Face Daily Papers 阅读 →

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

新的Longtail-SWE基准测试评估13种代表性不足语言的编码代理

本文如何被排名

Signal score
0 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
发布了用于评估AI模型的新学术基准测试。[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
3 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

完整方法见我们的编辑标准。

报道来源 [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    Longtail-SWE:代表性不足语言的高质量SWE任务

    Challenging repository-level benchmarks remain limited for many programming language ecosystems, where filtering scarce candidates with ambiguous descriptions or defective tests can discard valuable engineering problems. We introduce Longtail-SWE, a benchmark of 202 issue-resolut…