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English(EN) Agentic-TTT: Training test-time policy for test-time training

新的Agentic-TTT系统学会自主改进模型

研究人员开发了Agentic-TTT,这是一种新颖的方法,使模型能够自主决定何时以及如何应用测试时训练(TTT)。该系统将TTT过程视为可调用的工具,并根据其决策观察到的效用增益来学习策略。Agentic-TTT在基准测试中展示了效用近乎翻倍于骨干模型,学会了在效用和计算成本之间取得平衡,并泛化到新领域。 AI

影响 使模型能够从部署经验中自主学习,可能加速自我改进周期。

排序理由 这是一篇描述AI模型自改进新方法的论文。[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 →

新的Agentic-TTT系统学会自主改进模型

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这是一篇描述AI模型自改进新方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Jiahao Lu, Mohan Kankanhalli ·

    Agentic-TTT:为测试时训练训练测试时策略

    arXiv:2610.12002v1 Announce Type: cross Abstract: Test-time training (TTT) adapts an LLM's parameters using signals derived from test inputs, and can make striking improvements in pre-specified settings such as IMO competitions or designated open problems. By turning deployment e…