{"id":7545,"date":"2025-10-10T05:32:00","date_gmt":"2025-10-09T20:32:00","guid":{"rendered":"https:\/\/devneko.jp\/wordpress\/?p=7545"},"modified":"2025-10-04T21:49:36","modified_gmt":"2025-10-04T12:49:36","slug":"timeseriesscientist-a-general-purpose-ai-agent-for-time-series-analysis","status":"publish","type":"post","link":"https:\/\/devneko.jp\/wordpress\/?p=7545","title":{"rendered":"TimeSeriesScientist: A General-Purpose AI Agent for Time Series Analysis"},"content":{"rendered":"\n<ul class=\"wp-block-list\">\n<li><strong>TimeSeriesScientist: A General-Purpose AI Agent for Time Series Analysis\u00a0<\/strong>[25.4]<br>TimeSeriesScientist(TSci)\u306f\u6642\u7cfb\u5217\u4e88\u6e2c\u306e\u305f\u3081\u306e\u4e00\u822c\u7684\u306a\u30c9\u30e1\u30a4\u30f3\u306b\u4f9d\u5b58\u3057\u306a\u3044\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3067\u3042\u308b\u3002 \u3053\u308c\u306f\u305d\u308c\u305e\u308c\u5e73\u574710.4%\u306838.2%\u306e\u4e88\u6e2c\u8aa4\u5dee\u3092\u6e1b\u5c11\u3055\u305b\u308b\u3002 \u900f\u660e\u306a\u81ea\u7136\u8a00\u8a9e\u306e\u5408\u7406\u6027\u3068\u5305\u62ec\u7684\u306a\u5831\u544a\u306b\u3088\u308a\u3001TSci\u306f\u4e88\u6e2c\u3092\u30db\u30ef\u30a4\u30c8\u30dc\u30c3\u30af\u30b9\u30b7\u30b9\u30c6\u30e0\u306b\u5909\u63db\u3059\u308b\u3002<br><a href=\"http:\/\/arxiv.org\/abs\/2510.01538v1\">\u8ad6\u6587<\/a>\u00a0\u00a0<a href=\"https:\/\/fugumt.com\/fugumt\/paper_check\/2510.01538v1\">\u53c2\u8003\u8a33\uff08\u30e1\u30bf\u30c7\u30fc\u30bf\uff09<\/a>\u00a0 \u00a0(Thu, 02 Oct 2025 00:18:59 GMT)<\/li>\n\n\n\n<li>\u300cUpon receiving input time series data, the framework executes a structured four-agent workflow. Curator generates analytical reports (Section 3.2), Planner selects model configurations through reasoning and validation (Section 3.3), Forecaster integrates model results to produce the final forecast (Section 3.4), Reporter generates a comprehensive report as the final output of our framework (Section 3.5).\u300d\u3068\u3044\u3046\u6642\u7cfb\u5217\u5206\u6790\u306e\u30a8\u30fc\u30b8\u30a7\u30f3\u30c8\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af<\/li>\n\n\n\n<li>\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u30b5\u30a4\u30c8\u306f<a href=\"https:\/\/y-research-sbu.github.io\/TimeSeriesScientist\/\">TimeSeriesScientist: A General-Purpose AI Agent for Time Series Analysis<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[595],"class_list":["post-7545","post","type-post","status-publish","format-standard","hentry","category-arxiv","tag-595"],"_links":{"self":[{"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/7545","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=7545"}],"version-history":[{"count":1,"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/7545\/revisions"}],"predecessor-version":[{"id":7546,"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/7545\/revisions\/7546"}],"wp:attachment":[{"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=7545"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=7545"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=7545"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}