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English(EN) Very interesting new work from Microsoft.

Microsoft的Agent Lightning v1.0提升了Qwen3.5-9B在SWE-bench上的表现

微软开发了Agent Lightning v1.0,这是一个连接强化学习以进行智能体训练的系统。这项新工作利用了一个端点代理来集成任何连接器,使训练器能够与环境循环进行交互。通过使用这种方法,并辅以适度的计算资源和6,000个训练示例,微软成功地将Qwen3.5-9B在SWE-bench Verified基准测试上的性能从41.8%提高到了56.4%。 AI

影响 这一发展可能会提高智能体训练的效率和在编码基准测试上的性能,并可能影响未来AI智能体的能力。

排序理由 该条目描述了微软的一项新研究工作,详细介绍了一种智能体训练方法及其在基准测试上的性能提升。[lever_c_demoted from research: ic=1 ai=1.0]

在 X — Omar Sanseviero (HF research) 阅读 →

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

Microsoft的Agent Lightning v1.0提升了Qwen3.5-9B在SWE-bench上的表现

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该条目描述了微软的一项新研究工作,详细介绍了一种智能体训练方法及其在基准测试上的性能提升。[lever_c_demoted from research: ic=1 ai=1.0]
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  1. X — Omar Sanseviero (HF research) TIER_1 English(EN) · omarsar0 ·

    微软一项非常有趣的新工作。

    Very interesting new work from Microsoft. (bookmark it) This work is related to this emerging theme of leveraging harnesses for model post-training. Modern agents run inside a harness that owns tools, context, and control flow. When you train them, the harness owns the https:/…