跳到正文
@alibaba_cloud· @alibaba_cloud · X·· 2026-05-21AI 评分49
AI 导读

(3/6) AgentScaling:在 Qwen3.5 的环境扩展方法基础上,我们在 Qwen3.7 中大幅扩展了智能体训练环境的质量与多样性——智能体能力可以从多样化的环境中泛化,正如语言模型能从多样化的文本中泛化一样。下图展示了一条清晰且一致的提升轨迹,Qwen3.7-Max 取得了平均排名前三的成绩,逼近 Claude-4.6-Opus-Max。

正文

(3/6) AgentScaling: Building on Qwen3.5's environment scaling approach, we've aggressively expanded the quality and diversity of agentic training environments in Qwen3.7 — agentic capabilities generalize from diverse environments, just as language models do from diverse text. The figure below shows a clear and consistent improvement trajectory, with Qwen3.7-Max achieving a top-3 average ranking that approaches Claude-4.6-Opus-Max.

来源:@alibaba_cloud · x.com