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English(EN) The Unused Input: The Initial State as a Conditioning Interface for Recurrent TSFMs

研究人员探索在循环TSFM中使用初始状态进行条件设置

研究人员探索了利用循环时间序列基础模型(TSFM)的初始状态作为条件接口,而不是按照惯例将其留空。一项使用基于xLSTM的TiRex模型的案例研究表明,将输入窗口的学习到的频谱摘要注入初始状态可以提高准确性。进一步的实验表明,将状态用作每个数据集的适应表面或作为外源文本信息的通道,也能带来微小但可衡量的改进,有时在与LoRA适配器结合使用时,其效果甚至超过了完全微调。 AI

影响 这项研究提出了一个新途径,通过利用循环时间序列模型的初始状态来提高其性能。

排序理由 研究论文,详细介绍了一种用于条件设置循环时间序列基础模型的新颖方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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

研究人员探索在循环TSFM中使用初始状态进行条件设置

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研究论文,详细介绍了一种用于条件设置循环时间序列基础模型的新颖方法。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Bernhard Voggenberger, Christian Ganh\"or, Levente Z\'olyomi, Sebastian B\"ock, Sepp Hochreiter ·

    未使用的输入:初始状态作为循环TSFM的条件接口

    arXiv:2611.14357v1 Announce Type: new Abstract: Time series foundation models (TSFMs) forecast unseen series without task-specific training. Increasingly they are built on recurrent backbones, whose constant per-step cost makes long-context inference cheap, and which, unlike tran…