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English(EN) ViBench 2.0: A Benchmark for Long-Horizon Software Building

ViBench 2.0 基准测试评估AI代理在长周期软件构建方面的能力

研究人员推出了ViBench 2.0,这是一个旨在评估AI代理长周期软件构建能力的新基准测试。与专注于单个、完全指定的任务的现有基准测试不同,ViBench 2.0 通过连续的功能请求来评估整个产品的开发,模拟真实的用户交互。对九个模型的初步评估显示,通过测试计划与交付功能齐全的产品之间存在显著差距,没有开源模型能够完全交付产品。然而,进展迅速,一个模型家族在其三个版本中显示出成功率和成本的大幅提高。 AI

影响 为评估AI代理在复杂、长期的软件开发任务方面树立了新标准。

排序理由 该集群描述了一个用于评估AI代理在软件构建任务方面的基准测试,该测试发表在一篇学术论文中。[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 →

ViBench 2.0 基准测试评估AI代理在长周期软件构建方面的能力

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25 / 100
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Tool
该集群描述了一个用于评估AI代理在软件构建任务方面的基准测试,该测试发表在一篇学术论文中。[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
Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

完整方法见我们的编辑标准。

报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Daniel Furman, Preeya Kirani, Ibrahim Sheikh, Zhen Li, Peter Zhong, Michele Catasta ·

    ViBench 2.0:面向长周期软件构建的基准测试

    arXiv:2611.05620v1 Announce Type: new Abstract: On Replit, our agentic engineering platform, users now build entire products without writing code, through successive feature requests to an agent. Yet existing coding benchmarks evaluate single, fully specified tasks, and many are …