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Microsoft's Agent Lightning v1.0 boosts Qwen3.5-9B on SWE-bench

By PulseAugur Editorial · [1 sources] ·

Microsoft has developed Agent Lightning v1.0, a system that connects harnesses to reinforcement learning for agent training. This new work utilizes an endpoint proxy to integrate any harness, enabling the trainer to interact with the environment loop. By employing this method with modest compute and 6,000 training examples, Microsoft successfully improved the performance of Qwen3.5-9B on the SWE-bench Verified benchmark from 41.8% to 56.4%. AI

IMPACT This development could enhance agent training efficiency and performance on coding benchmarks, potentially influencing future AI agent capabilities.

RANK_REASON The item describes a new research work from Microsoft detailing a method for agent training and its performance improvement on a benchmark. [lever_c_demoted from research: ic=1 ai=1.0]

Read on X — Omar Sanseviero (HF research) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Microsoft's Agent Lightning v1.0 boosts Qwen3.5-9B on SWE-bench

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The item describes a new research work from Microsoft detailing a method for agent training and its performance improvement on a benchmark. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. X — Omar Sanseviero (HF research) TIER_1 English(EN) · omarsar0 ·

    Very interesting new work from Microsoft.

    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:/…

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