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English(EN) Toto 2.0: Time Series Forecasting Enters the Scaling Era

Toto 2.0 模型在时间序列预测中展现出扩展优势

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员推出了 Toto 2.0，这是一套五个开放权重的时间序列预测模型，证明了扩展基础模型的有效性。这些模型使用单一配方进行训练，随着参数数量从 400 万增加到 25 亿，其预测质量得到提高。Toto 2.0 在三个关键预测基准测试：BOOM、GIFT-Eval 和 TIME 上取得了最先进的结果。 AI

影响 证明了扩展定律适用于时间序列预测，有可能提高各种应用中的准确性。

排序理由 发布了一个在研究论文中描述了基准测试结果的开源模型系列。[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 →

Toto 2.0 模型在时间序列预测中展现出扩展优势

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发布了一个在研究论文中描述了基准测试结果的开源模型系列。[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) · David Asker ·

    Toto 2.0：时间序列预测进入规模化时代

    We show that time series foundation models scale: a single training recipe produces reliable forecast-quality improvements from 4M to 2.5B parameters. We release Toto 2.0, a family of five open-weights forecasting models trained under this recipe. The Toto 2.0 family sets a new s…

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