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TSCenter/awesome-time-series-papers
默认分支 master · commit 2df4d43b · 扫描时间 2026/6/7 01:18:17
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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 TSCenter/awesome-time-series-papers 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。
- highreadme#1Clarify README's opening to differentiate from academic platforms
原因:
当前This is an awesome list of the latest time series papers and code from top AI venues!
复制粘贴的修复This GitHub repository is a human-curated awesome list, providing a categorized collection of the latest time series papers and code from top AI venues. It offers a focused alternative to broad academic search engines or conference proceedings.
- mediumabout#2Refine the 'About' description to emphasize curation and GitHub hosting
原因:
当前An Awesome List of the latest time series papers and code from top AI venues.
复制粘贴的修复A human-curated GitHub awesome list of the latest time series papers and code from top AI venues, categorized for easy discovery.
- lowhomepage#3Add the repository URL as the homepage
原因:
复制粘贴的修复https://github.com/TSCenter/awesome-time-series-papers
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。
- arXiv.org · 被推荐 1 次
- Google Scholar · 被推荐 1 次
- NeurIPS (Conference on Neural Information Processing Systems) · 被推荐 1 次
- ICML (International Conference on Machine Learning) · 被推荐 1 次
- KDD (ACM SIGKDD Conference on Knowledge Discovery and Data Mining) · 被推荐 1 次
- 品类问题Where can I find recent research papers on advanced time series analysis techniques?你:未被推荐AI 推荐顺序:
- arXiv.org
- Google Scholar
- NeurIPS (Conference on Neural Information Processing Systems)
- ICML (International Conference on Machine Learning)
- KDD (ACM SIGKDD Conference on Knowledge Discovery and Data Mining)
- Journal of Machine Learning Research (JMLR)
- The American Economic Review (AER)
- Journal of Econometrics
AI 推荐了 8 个替代方案,却始终没点名 TSCenter/awesome-time-series-papers。这就是要补上的差距。
查看 AI 完整回答
- 品类问题What are the latest academic resources for time series forecasting and anomaly detection?你:未被推荐AI 推荐顺序:
- NeurIPS
- ICML
- KDD
- AAAI
- The Journal of Machine Learning Research
- IEEE Transactions on Knowledge and Data Engineering
- International Journal of Forecasting
AI 推荐了 7 个替代方案,却始终没点名 TSCenter/awesome-time-series-papers。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 completenesswarn
建议:
- README presencepass
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 TSCenter/awesome-time-series-papers?passAI 未点名 TSCenter/awesome-time-series-papers —— 很可能在说另一个项目
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 TSCenter/awesome-time-series-papers in production, what risks or prerequisites should they evaluate first?passAI 明确点名了 TSCenter/awesome-time-series-papers
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 TSCenter/awesome-time-series-papers solve, and who is the primary audience?passAI 未点名 TSCenter/awesome-time-series-papers —— 很可能在说另一个项目
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 TSCenter/awesome-time-series-papers 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。
[](https://repogeo.com/zh/r/TSCenter/awesome-time-series-papers)<a href="https://repogeo.com/zh/r/TSCenter/awesome-time-series-papers"><img src="https://repogeo.com/badge/TSCenter/awesome-time-series-papers.svg" alt="RepoGEO" /></a>订阅 Pro,解锁深度诊断
TSCenter/awesome-time-series-papers — 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