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moment-timeseries-foundation-model/moment

默认分支 main · commit 38f7310a · 扫描时间 2026/6/9 18:03:32

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AI 可见性总分
40 /100
亟需修复
品类召回
0 / 2
在所有问题中均未被推荐
规则结果
通过 2 · 警告 0 · 失败 0
客观元数据检查
AI 认识你的名字
3 / 3
直接询问时，AI 是否点名你的仓库
如何阅读这份报告

行动计划告诉你下一步要做什么——按影响力排序、可直接复制粘贴的修改。品类可见性是真正的 GEO 测试：当用户向 AI 提一个不带品牌、本应让 moment-timeseries-foundation-model/moment 浮出水面的问题时，AI 是真的推荐了你，还是推荐了你的竞品？客观检查验证 AI 引擎最先权衡的那些元数据信号。自指检查判断 AI 是否还认识你的名字。

行动计划 — 可复制粘贴的修复

3 条由 gemini-2.5-flash 生成、按优先级排序的修改。修完后请把对应条目标记为完成。

整体方向
  • highreadme#1
    Strengthen README introduction to emphasize pre-trainable foundation model

    原因：

    当前
    We introduce MOMENT, a family of open-source foundation models for general-purpose time-series analysis. Pre-training large models on time-series data is challenging due to (1) the absence a large and cohesive public time-series repository, and (2) diverse time-series
    复制粘贴的修复
    MOMENT is an open-source family of time-series foundation models designed to simplify and accelerate general-purpose time-series analysis. It enables researchers and data scientists to pre-train custom models on their own data and adapt them for tasks like forecasting, classification, and anomaly detection.
  • mediumtopics#2
    Add specific topics for pre-training and custom foundation models

    原因：

    当前
    anomaly-detection, classification, forecasting, foundational-models, imputation, large-language-models, time-series, time-series-anomaly-detection, time-series-classification, time-series-forecasting, transformers
    复制粘贴的修复
    anomaly-detection, classification, forecasting, foundational-models, imputation, large-language-models, time-series, time-series-anomaly-detection, time-series-classification, time-series-forecasting, time-series-pretraining, custom-foundation-models, transformers
  • mediumabout#3
    Enhance repository description to highlight pre-trainable and general-purpose nature

    原因：

    当前
    MOMENT: A Family of Open Time-series Foundation Models, ICML'24
    复制粘贴的修复
    MOMENT: A family of open-source, pre-trainable foundation models for general-purpose time-series analysis (forecasting, classification, anomaly detection, imputation). Accepted at ICML'24.

本次扫描解析到的品类 GEO 通道：google/gemini-2.5-flash, deepseek/deepseek-v4-flash

品类可见性 — 真正的 GEO 测试

向 google/gemini-2.5-flash 提出的不带品牌问题。AI 推荐了你，还是推荐了别人？

各模型使用同一组问题 — 切换标签对比回答与排名。

召回
0 / 2
0% 的问题里出现了 moment-timeseries-foundation-model/moment
平均排名
—
越小越好。#1 表示首位推荐。
声量占比
0%
在所有被点名的工具中，你占了多少？
头号对手
tensorflow/tensorflow
在 2 个问题中被推荐 4 次
竞品排行
  1. tensorflow/tensorflow · 被推荐 4 次
  2. huggingface/transformers · 被推荐 2 次
  3. DeepAR+ · 被推荐 1 次
  4. Temporal Fusion Transformers · 被推荐 1 次
  5. Informer / Autoformer · 被推荐 1 次
  • 品类问题
    Seeking a robust foundation model for various time series forecasting, classification, and anomaly detection tasks.
    你：未被推荐
    AI 推荐顺序：
    1. DeepAR+
    2. Temporal Fusion Transformers
    3. Informer / Autoformer
    4. Prophet
    5. XGBoost / LightGBM
    6. PyTorch Forecasting

    AI 推荐了 6 个替代方案，却始终没点名 moment-timeseries-foundation-model/moment。这就是要补上的差距。

    查看 AI 完整回答
  • 品类问题
    How can I pre-train a custom time series foundation model using my own datasets?
    你：未被推荐
    AI 推荐顺序：
    1. PyTorch
    2. Hugging Face Transformers (huggingface/transformers)
    3. Accelerate (huggingface/accelerate)
    4. Pandas (pandas-dev/pandas)
    5. NumPy (numpy/numpy)
    6. Hugging Face Trainer (huggingface/transformers)
    7. AWS
    8. Google Cloud
    9. Azure
    10. TensorFlow (tensorflow/tensorflow)
    11. Keras (keras-team/keras)
    12. TensorFlow Distributed (tensorflow/tensorflow)
    13. tf.data (tensorflow/tensorflow)
    14. tf.distribute.Strategy (tensorflow/tensorflow)
    15. JAX (google/jax)
    16. Flax (google/flax)
    17. Haiku (deepmind/dm-haiku)
    18. Google Cloud TPUs
    19. River (online-ml/river)
    20. GluonTS (awslabs/gluon-ts)
    21. Apache MXNet (apache/mxnet)

    AI 推荐了 21 个替代方案，却始终没点名 moment-timeseries-foundation-model/moment。这就是要补上的差距。

    查看 AI 完整回答

客观检查

针对 AI 引擎最看重的元数据信号的规则审计。

  • Metadata completeness
    pass

  • README presence
    pass

自指检查

当被直接问到你时，AI 是否还知道你的仓库存在？

  • Compared to common alternatives in this category, what is the core differentiator of moment-timeseries-foundation-model/moment?
    pass
    AI 明确点名了 moment-timeseries-foundation-model/moment

    AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

  • If a team adopts moment-timeseries-foundation-model/moment in production, what risks or prerequisites should they evaluate first?
    pass
    AI 明确点名了 moment-timeseries-foundation-model/moment

    AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

  • In one sentence, what problem does the repo moment-timeseries-foundation-model/moment solve, and who is the primary audience?
    pass
    AI 明确点名了 moment-timeseries-foundation-model/moment

    AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

嵌入你的 GEO 徽章

把这个徽章贴进 moment-timeseries-foundation-model/moment 的 README。每次重新扫描都会自动更新，并跳到最新报告——是「我在乎 AI 可发现性」最简单的公开证明。

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Pro

订阅 Pro，解锁深度诊断

moment-timeseries-foundation-model/moment — 轻量扫描仍免费；本卡列出 Pro 相对轻量的深度额度。

  • 深度报告每月 10 次
  • 无品牌品类查询5，轻量 2
  • 优先行动项8，轻量 3