{"id":6201,"date":"2025-09-25T12:24:16","date_gmt":"2025-09-25T04:24:16","guid":{"rendered":"https:\/\/nullthought.net\/?p=6201"},"modified":"2025-09-27T13:37:49","modified_gmt":"2025-09-27T05:37:49","slug":"%e7%94%a8%e4%b8%8a%e4%b8%8b%e6%96%87%e5%86%85%e5%be%ae%e8%b0%83%ef%bc%88in-context-fine-tuning-icf%ef%bc%89%e6%96%b9%e6%b3%95%e6%94%b9%e8%bf%9btimesfm%ef%bc%88%e8%b7%a8%e9%a2%86","status":"publish","type":"post","link":"https:\/\/nullthought.net\/?p=6201","title":{"rendered":"\u7528\u201c\u4e0a\u4e0b\u6587\u5185\u5fae\u8c03\uff08In-Context Fine-Tuning, ICF\uff09\u201d\u65b9\u6cd5\u6539\u8fdbTimesFM\uff08\u8de8\u9886\u57df\u96f6\u6837\u672c\u9884\u6d4b\u7684\u65f6\u5e8f\u57fa\u7840\u6a21\u578b\uff09"},"content":{"rendered":"\n<p>\u8bba\u6587<strong><a href=\"https:\/\/openreview.net\/forum?id=uxzgGLWPj2\" target=\"_blank\" rel=\"noreferrer noopener\">In-Context Fine-Tuning for Time-Series Foundation Models<\/a><\/strong>\u805a\u7126\u201c\u5c06\u591a\u6761\u76f8\u5173\u65f6\u95f4\u5e8f\u5217\u7684\u5c11\u91cf\u6837\u4f8b\u5728\u63a8\u7406\u65f6\u4f5c\u4e3a\u4e0a\u4e0b\u6587\u63d0\u4f9b\u7ed9\u57fa\u7840\u6a21\u578b\u201d\uff0c\u4ee5\u5728<strong>\u96f6\u6837\u672c\/\u5c11\u6837\u672c<\/strong>\u573a\u666f\u4e0b\u63d0\u5347\u9884\u6d4b\u7cbe\u5ea6\uff0c\u5e76\u907f\u514d\u9010\u6570\u636e\u96c6\u5fae\u8c03\u7684\u6602\u8d35\u4ee3\u4ef7\u3002\u4f5c\u8005\u63d0\u51fa\u4e00\u79cd\u201c<a href=\"https:\/\/nullthought.net\/?p=5522\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>\u4e0a\u4e0b\u6587<\/strong><\/a>\u5185<strong><a href=\"https:\/\/nullthought.net\/?p=6045\" target=\"_blank\" rel=\"noreferrer noopener\">\u5fae\u8c03<\/a><\/strong>\uff08In-Context Fine-Tuning, ICF\uff09\u201d<strong>\u7684\u65b9\u6cd5\uff1a\u628a\u57fa\u7840\u7684 <a href=\"https:\/\/nullthought.net\/?p=5602\" target=\"_blank\" rel=\"noreferrer noopener\">TimesFM <\/a>\u7ee7\u7eed\u9884\u8bad\u7ec3\uff0c\u4f7f\u5176\u5b66\u4f1a\u5728\u63a8\u7406\u65f6\u5229\u7528\u6765\u81ea\u591a\u6761\u76f8\u5173\u5e8f\u5217\u7684<\/strong>\u793a\u4f8b\u5757\uff08examples\uff09\uff0c\u4ece\u800c\u5bf9\u76ee\u6807\u57df\u5206\u5e03\u5728\u7ebf\u9002\u914d\u3002\u8bba\u6587\u6458\u8981\u5ba3\u79f0\uff1aICF \u5728\u5e38\u89c1\u57fa\u51c6\u4e0a\u4f18\u4e8e\u7edf\u8ba1\u6a21\u578b\u4e0e\u6df1\u5ea6\u76d1\u7763\u65b9\u6cd5\uff0c\u4e5f\u4f18\u4e8e\u5176\u4ed6\u65f6\u95f4\u5e8f\u5217\u57fa\u7840\u6a21\u578b\uff0c\u5e76\u4e14\u5176\u8868\u73b0<strong>\u53ef\u4e0e\u9010\u6570\u636e\u96c6\u5fae\u8c03\u7684 TimesFM-FT \u76f8\u5f53<\/strong>\u3002<\/p>\n\n\n\n<p>\u8bba\u6587\u4f5c\u8005\u4e3aMatthew Faw, Rajat Sen, Yichen Zhou, Abhimanyu Das\uff0c\u6765\u81eaGeorgia Institute of Technology\u548cGoogle Research\u3002<\/p>\n\n\n\n<figure class=\"wp-block-image aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"950\" height=\"536\" src=\"https:\/\/nullthought.net\/wp-content\/uploads\/2025\/09\/image-9.png\" alt=\"\" class=\"wp-image-6202\" srcset=\"https:\/\/nullthought.net\/wp-content\/uploads\/2025\/09\/image-9.png 950w, https:\/\/nullthought.net\/wp-content\/uploads\/2025\/09\/image-9-300x169.png 300w, https:\/\/nullthought.net\/wp-content\/uploads\/2025\/09\/image-9-768x433.png 768w\" sizes=\"auto, (max-width: 950px) 100vw, 950px\" \/><figcaption class=\"wp-element-caption\"><strong><a href=\"https:\/\/openreview.net\/forum?id=uxzgGLWPj2\" target=\"_blank\" rel=\"noreferrer noopener\">In-Context Fine-Tuning for Time-Series Foundation Models<\/a><\/strong><\/figcaption><\/figure>\n\n\n\n<h5 class=\"wp-block-heading\">\u4e00\u3001\u603b\u4f53\u65b9\u6cd5\u4e0e\u6a21\u578b\u6846\u67b6<\/h5>\n\n\n\n<p>\u65b9\u6cd5\u4ee5 <strong><a href=\"https:\/\/nullthought.net\/?p=5602\" target=\"_blank\" rel=\"noreferrer noopener\">TimesFM<\/a>(base)<\/strong> \u4e3a\u8d77\u70b9\uff0c\u901a\u8fc7<strong>\u7ee7\u7eed\u9884\u8bad\u7ec3<\/strong>\u5f97\u5230 <strong>TimesFM-ICF<\/strong>\uff0c\u6838\u5fc3\u662f\u6539\u9020\u89e3\u7801\u5668\u5f0f\u5806\u53e0 Transformer\uff0c\u4f7f\u5176\u80fd\u591f\u63a5\u6536\u201c\u76ee\u6807\u5e8f\u5217\u5386\u53f2 + \u591a\u6761\u4e0a\u4e0b\u6587\u793a\u4f8b\u201d\u3002\u8bad\u7ec3\u9636\u6bb5\u5148\u6309 TimesFM \u539f\u6cd5\u83b7\u5f97 TimesFM(base)\uff0c\u518d\u5728\u6784\u9020\u4e86\u4e0a\u4e0b\u6587\u6837\u4f8b\u7684\u6570\u636e\u4e0a\u7ee7\u7eed\u8bad\u7ec3\uff0c\u5f97\u5230 TimesFM-ICF\u3002<br>\u6574\u4f53\u4ecd\u6cbf\u7528 TimesFM \u7684<strong>\u5206\u5757\u2014\u6b8b\u5dee\u5757\u5d4c\u5165\u2014\u89e3\u7801\u5668\u5806\u53e0\u2014\u6b8b\u5dee\u5757\u8f93\u51fa<\/strong>\u6d41\u7a0b\uff0c\u53ea\u662f\u4e3a\u652f\u6301 ICF \u5728\u67b6\u6784\u5c42\u9762\u52a0\u5165\u4e86\u65b0\u7684\u7ec4\u4ef6\u4e0e\u7ea6\u675f\u3002<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">\u4e8c\u3001\u5173\u952e\u67b6\u6784\u6539\u9020<\/h5>\n\n\n\n<p>1\uff09<strong>\u793a\u4f8b\u5206\u9694\u7b26\uff08Separator\uff09<\/strong>\uff1a\u7b80\u5355\u4e32\u63a5\u591a\u6761\u793a\u4f8b\u4f1a\u8ba9\u6a21\u578b\u628a\u201c\u591a\u6761\u7ebf\u6027\u8d8b\u52bf\u7684\u62fc\u63a5\u201d\u8bef\u8ba4\u4e3a\u4e00\u79cd\u65b0\u6a21\u5f0f\uff08\u5982\u4e09\u89d2\u6ce2\uff09\uff0c\u56e0\u6b64\u4f5c\u8005\u5728<strong>\u6bcf\u6761\u793a\u4f8b\u7ed3\u5c3e\u63d2\u5165\u4e00\u4e2a\u53ef\u5b66\u4e60\u7684\u5206\u9694\u7b26 token<\/strong>\uff0c\u663e\u5f0f\u6807\u6ce8\u6837\u4f8b\u8fb9\u754c\uff0c\u9632\u6b62\u6a21\u5f0f\u201c\u6df7\u53e0\u201d\u3002<br>2\uff09<strong>\u8de8\u793a\u4f8b\u6ce8\u610f\u529b\uff08Cross-Example Attention\uff09<\/strong>\uff1aTransformer \u5728\u56e0\u679c\u6ce8\u610f\u529b\u4e2d<strong>\u5141\u8bb8\u5173\u6ce8\u6b64\u524d\u6240\u6709\u8865\u4e01\u53ca\u5206\u9694\u7b26 token<\/strong>\uff0c\u4f7f\u6a21\u578b\u80fd\u6570\u6e05\u5df2\u5904\u7406\u7684\u793a\u4f8b\u6bb5\uff0c\u5e76\u7528\u5206\u9694\u7b26\u4f4d\u7684\u8f93\u51fa token \u5728\u6df1\u5c42\u5bf9\u672c\u793a\u4f8b\u4fe1\u606f\u8fdb\u884c\u201c\u6c47\u603b\/\u8fb9\u754c\u4f20\u9012\u201d\u3002<br>3\uff09<strong>\u4f4d\u7f6e\u7f16\u7801\u7b56\u7565\uff08NoPE \u4e0e\u957f\u5ea6\u6cdb\u5316\uff09<\/strong>\uff1a\u4e3a\u66f4\u597d\u5730\u5904\u7406\u8de8\u793a\u4f8b\u4e0e\u53d8\u957f\u5ea6\uff0c\u57fa\u7840\u6a21\u578b\u9884\u8bad\u7ec3\u65f6\u91c7\u7528**\u4e0d\u663e\u5f0f\u4f4d\u7f6e\u7f16\u7801\uff08NoPE\uff09**\u7684\u505a\u6cd5\uff1b\u5b9e\u9a8c\u663e\u793a NoPE \u5728\u8bad\u7ec3\u9a8c\u8bc1\u4e0a\u4e0d\u900a\u4e8e APE \u7b49\u80fd\u6cdb\u5316\u957f\u5ea6\u7684\u4f4d\u7f6e\u7f16\u7801\uff08\u5982 FIRE\uff09\u3002<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">\u4e09\u3001\u4e0a\u4e0b\u6587\u6784\u9020\u4e0e\u7ee7\u7eed\u9884\u8bad\u7ec3\u6570\u636e<\/h5>\n\n\n\n<p>\u8bbe TimesFM(base) \u7684\u6700\u5927\u5386\u53f2 <strong>Lmax=512<\/strong>\u3001\u8f93\u51fa\u8865\u4e01\u957f\u5ea6 <strong>h=128<\/strong>\uff0c\u5219\u5355\u6761\u793a\u4f8b\u7684\u603b\u957f\u5ea6 <strong>T=Lmax+h=640<\/strong>\u3002\u4f5c\u8005\u5bf9\u6bcf\u6761\u5e8f\u5217\u4ee5\u6ed1\u7a97\u6b65\u957f 1 \u751f\u6210\u957f\u5ea6\u4e3a T \u7684\u793a\u4f8b\uff0c\u5e76\u628a <strong>n \u6761\u793a\u4f8b\u6253\u5305\u4e3a\u4e00\u4e2a\u4e0a\u4e0b\u6587<\/strong>\u3002\u5206\u7ec4\u6709\u4e24\u79cd\uff1a<br>\uff08a\uff09<strong>\u5e8f\u5217\u7ea7<\/strong>\uff1a\u628a\u4e00\u6761\u957f\u5e8f\u5217\u5207\u6210\u591a\u6bb5\u793a\u4f8b\u518d\u9009 n \u6bb5\u7ec4\u6210\u4e0a\u4e0b\u6587\uff1b\uff08b\uff09<strong>\u6570\u636e\u96c6\u7ea7<\/strong>\uff1a\u4ece\u540c\u4e00\u6570\u636e\u96c6\u4efb\u610f\u5e8f\u5217\u5207\u51fa n \u6bb5\u7ec4\u6210\u4e0a\u4e0b\u6587\u3002\u4e24\u6cd5\u90fd\u4fdd\u8bc1\u6a21\u5f0f\u76f8\u8fd1\u3001\u53ef\u4e92\u501f\u4fe1\u606f\u3002<br>\u7ee7\u7eed\u9884\u8bad\u7ec3\u65f6\uff0c<strong>\u6bcf\u4e2a\u4e0a\u4e0b\u6587\u6700\u591a n=50 \u4e2a\u793a\u4f8b<\/strong>\uff0c\u5e76\u4ece\u4e24\u79cd\u5206\u7ec4\u65b9\u5f0f\u540c\u65f6\u91c7\u6837\uff1b\u8003\u8651\u7ec4\u5408\u6570\u8fc7\u5927\uff0c\u4f5c\u8005<strong>\u968f\u673a\u751f\u6210\u7ea6 20N \u7ec4<\/strong>\u4f5c\u4e3a\u8bad\u7ec3\u4e0a\u4e0b\u6587\uff1b\u771f\u5b9e:\u5408\u6210\u6570\u636e\u6309 <strong>90%:10%<\/strong> \u6df7\u5408\uff0c\u5e76\u5728\u4e0d\u540c\u9891\u7387\u7ec4\u4e4b\u95f4\u5747\u8861\u91c7\u6837\u3002<br><strong>\u793a\u4f8b\u9009\u62e9<\/strong>\u7b56\u7565\u5f88\u6734\u7d20\uff1a\u6bcf\u4e2a\u4e0a\u4e0b\u6587\u53d6<strong>5 \u6761\u6765\u81ea\u76ee\u6807\u5e8f\u5217\u7684\u201c\u8fd1\u5386\u53f2\u201d\u793a\u4f8b<\/strong>\uff0c\u5176\u4f59\u4ece\u540c\u6570\u636e\u96c6\u7684\u5176\u4ed6\u5e8f\u5217<strong>\u968f\u673a<\/strong>\u62bd\u53d6\uff1b\u5176\u4ed6\u7b80\u5355\u7b56\u7565\u5728\u9644\u5f55\u4e5f\u6709\u5bf9\u6bd4\uff0c\u4f46<strong>\u968f\u673a + \u8fd1\u5386\u53f2<\/strong>\u5df2\u8db3\u4ee5\u5e26\u6765\u663e\u8457\u589e\u76ca\u3002<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">\u56db\u3001\u63a8\u7406\u65f6\u7684\u63d0\u793a\u4e0e\u4ee3\u4ef7<\/h5>\n\n\n\n<p>\u63a8\u7406\u65f6\u628a\u201c\u76ee\u6807\u5e8f\u5217\u5386\u53f2 + \u6700\u591a 50 \u6761\u4e0a\u4e0b\u6587\u793a\u4f8b\uff08\u5176\u4e2d\u5c3d\u53ef\u80fd\u542b 5 \u6761\u540c\u5e8f\u5217\u8fd1\u5386\u53f2\u793a\u4f8b\uff09\u201d\u4e32\u63a5\uff0c\u5e76\u4ee5\u5206\u9694\u7b26\u754c\u5b9a\u6837\u4f8b\u8fb9\u754c\u3002\u7531\u4e8e<strong>\u6ce8\u610f\u529b\u8ba1\u7b97\u968f\u793a\u4f8b\u6570\u589e\u52a0\u800c\u589e\u957f<\/strong>\uff0c\u5b58\u5728\u201c\u7cbe\u5ea6 \u2191 vs \u8ba1\u7b97\u65f6\u5ef6 \u2191\u201d\u7684\u6743\u8861\u3002<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">\u4e94\u3001\u5b9e\u9a8c\u8bbe\u7f6e\u4e0e\u8bc4\u4ef7\u6307\u6807<\/h5>\n\n\n\n<p>\u4f5c\u8005\u5728 <strong>Chronos \u96f6\u6837\u672c\u96c6\u5408\uff08\u8986\u76d6 27 \u4e2a\u6570\u636e\u96c6\uff09\u4e2d\u9009\u53d6\u8bad\u7ec3\u672a\u89c1\u8fc7\u7684 23 \u4e2a\u6570\u636e\u96c6<\/strong>\uff0c\u6784\u6210<strong>OOD Benchmark<\/strong>\uff1b\u53e6\u5728 <strong>ETT Rolling Window<\/strong>\u4e0a\u505a\u6eda\u52a8\u8bc4\u4f30\u3002\u8bc4\u4ef7\u91c7\u7528<strong>MASE<\/strong>\uff0c\u5e76\u5bf9\u6bcf\u4e2a\u6570\u636e\u96c6\u7528<strong>\u5b63\u8282\u6027\u6734\u7d20\u6cd5<\/strong>\u7684 MASE \u5f52\u4e00\u5316\u540e\u53d6<strong>\u51e0\u4f55\u5e73\u5747\uff08GM\uff09<\/strong>\uff0c\u4ee5\u6d88\u9664\u91cf\u7eb2\u4e0e\u5c3a\u5ea6\u5dee\u5f02\u3002<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">\u516d\u3001\u4e3b\u8981\u7ed3\u679c<\/h5>\n\n\n\n<p>1\uff09<strong>OOD Benchmark \u603b\u7ed3<\/strong>\uff1a<br>\u00b7 <strong>TimesFM-ICF \u5728\u96f6\u6837\u672c\u63a8\u7406\u4e0b\u201c\u5339\u914d\u201d\u9010\u6570\u636e\u96c6\u5fae\u8c03\u7684 TimesFM-FT<\/strong>\uff1b<br>\u00b7 \u76f8\u6bd4 TimesFM(base) <strong>\u51e0\u4f55\u5e73\u5747 Scaled-MASE \u63d0\u5347 6.8%<\/strong>\uff1b<br>\u00b7 <strong>\u76f8\u5bf9\u6700\u5f3a\u7684\u975e\u5fae\u8c03\u57fa\u7ebf PatchTST \u518d\u4f18 5%<\/strong>\u3002<br>2\uff09<strong>ETT Rolling Window<\/strong>\uff1a\u591a\u6570\u6570\u636e\u96c6\u548c\u4e0d\u540c\u5730\u5e73\u7ebf\u4e0b\uff0cTimesFM-ICF \u7684 MAE \u4f18\u4e8e\u6216\u63a5\u8fd1\u5f3a\u76d1\u7763\u4e0e\u96f6\u6837\u672c\u57fa\u7ebf\uff08\u5982 iTransformer\u3001TimesNet\u3001PatchTST \u7b49\uff09\uff0c\u7ec6\u8868\u7ed9\u51fa\u9010\u6570\u636e\u96c6\u5bf9\u6bd4\u3002<br>3\uff09<strong>\u65f6\u95f4\u4e0e\u6210\u672c<\/strong>\uff1a<br>\u5728\u987a\u5e8f\u5904\u7406\u5168\u90e8\u6570\u636e\u96c6\u7684\u8bbe\u5b9a\u4e0b\uff0c<strong>ICF \u65e0\u9700\u5fae\u8c03\uff0c\u4ec5\u63a8\u7406\u7ea6 25 \u5206\u949f<\/strong>\uff1b\u800c TimesFM-FT \u9700\u8981<strong>\u5fae\u8c03 29\u201384 \u5206\u949f + \u63a8\u7406 57\u2013418 \u5206\u949f<\/strong>\uff08\u968f\u8bbe\u5b9a\u4e0d\u540c\uff09\uff0c\u4e14\u5e76\u4e0d\u603b\u80fd\u8d85\u8fc7 ICF \u7684\u8868\u73b0\u3002<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">\u4e03\u3001\u6d88\u878d\u4e0e\u6743\u8861<\/h5>\n\n\n\n<p>1\uff09<strong>\u793a\u4f8b\u6570\u91cf vs \u8bef\u5dee\/\u65f6\u5ef6<\/strong>\uff1a\u5728 OOD \u7684\u201c\u77ed\u4e0a\u4e0b\u6587\u201d\u6570\u636e\u96c6\u4e0a\uff0c<strong>\u968f\u7740\u4e0a\u4e0b\u6587\u793a\u4f8b\u6570\u589e\u52a0\uff0cScaled-MASE \u5355\u8c03\u4e0b\u964d<\/strong>\uff0c\u540c\u65f6<strong>\u603b\u63a8\u7406\u65f6\u95f4\u4e0a\u5347<\/strong>\uff0c\u5448\u73b0\u6e05\u6670\u7684\u7cbe\u5ea6-\u65f6\u5ef6\u6743\u8861\u3002<br>2\uff09<strong>\u66f4\u957f\u5386\u53f2\u662f\u5426\u7b49\u4ef7\u4e8e\u66f4\u591a\u793a\u4f8b\uff1f<\/strong> \u4f5c\u8005\u5bf9\u6bd4\u201c\u5ef6\u957f\u57fa\u7840\u6a21\u578b\u5386\u53f2\u4e0a\u9650\u201d\u4e0e\u201c\u52a0\u5165\u4e0a\u4e0b\u6587\u793a\u4f8b\u201d\uff0c\u663e\u793a ICF \u7684\u6536\u76ca\u5e76\u975e\u4ec5\u6765\u81ea\u201c\u66f4\u957f\u4e0a\u4e0b\u6587\u201d\uff0c\u800c\u662f\u6765\u81ea<strong>\u8de8\u793a\u4f8b\u8fc1\u79fb\u4e0e\u5bf9\u9f50<\/strong>\u3002<br>3\uff09<strong>\u793a\u4f8b\u9009\u62e9\u7b56\u7565<\/strong>\uff1a\u968f\u673a + \u8fd1\u5386\u53f2\u5df2\u5f88\u5f3a\uff0c\u9644\u5f55\u7ed9\u51fa\u591a\u79cd\u7b56\u7565\uff08\u542b\u57fa\u4e8e DTW \u7684\u76f8\u4f3c\u5ea6\u9009\u62e9\uff09\u5bf9\u6bd4\uff1b\u603b\u4f53\u5dee\u5f02\u6709\u9650\uff0c<strong>\u7b80\u5355\u7b56\u7565\u8db3\u4ee5\u7a33\u5b9a\u83b7\u76ca<\/strong>\u3002<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">\u516b\u3001\u4f4d\u7f6e\u7f16\u7801\u4e0e\u957f\u5ea6\u6cdb\u5316<\/h5>\n\n\n\n<p>\u5728\u7ee7\u7eed\u9884\u8bad\u7ec3\u65f6\u91c7\u7528 <strong>NoPE<\/strong> \u7684\u8bbe\u8ba1\u5728\u9a8c\u8bc1\u4e0a\u4e0e APE \u6216\u5176\u4ed6\u201c\u53ef\u957f\u5ea6\u6cdb\u5316\u201d\u7684\u4f4d\u7f6e\u7f16\u7801\uff08\u5982 <strong>FIRE<\/strong>\uff09<strong>\u6301\u5e73\u6216\u66f4\u4f18<\/strong>\uff0c\u652f\u6301\u4e86\u201c\u4e0d\u663e\u5f0f\u7edd\u5bf9\u4f4d\u7f6e\u201d\u5728 ICF \u6846\u67b6\u91cc\u7684\u7a33\u5065\u6027\u3002<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">\u4e5d\u3001\u7ed3\u8bba\u4e0e\u5c40\u9650<\/h5>\n\n\n\n<p>\u4f5c\u8005\u8bc1\u5b9e\uff1a<strong>\u8ba9\u65f6\u95f4\u5e8f\u5217\u57fa\u7840\u6a21\u578b\u5b66\u4f1a\u5728\u63a8\u7406\u65f6\u5229\u7528\u4e0a\u4e0b\u6587\u793a\u4f8b<\/strong>\uff0c\u80fd\u5728\u96f6\u6837\u672c\u6761\u4ef6\u4e0b\u53d6\u5f97\u4e0e\u5fae\u8c03\u76f8\u5f53\u7684\u6027\u80fd\uff0c\u540c\u65f6\u8282\u7701\u5927\u91cf\u5fae\u8c03\u65f6\u95f4\u4e0e\u8fd0\u7ef4\u6210\u672c\u3002\u672a\u6765\u5de5\u4f5c\u5305\u62ec\uff1a\u628a ICF \u7684\u9002\u914d\u63a8\u5e7f\u5230<strong>\u5176\u4ed6\u57fa\u7840\u6a21\u578b<\/strong>\uff0c\u4ee5\u53ca\u63a2\u7d22<strong>\u66f4\u597d\u7684\u76f8\u5bf9\u4f4d\u7f6e\u7f16\u7801<\/strong>\u4e0e<strong>\u66f4\u4f18\u7684\u793a\u4f8b\u9009\u62e9<\/strong>\u3002<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">\u5341\u3001\u5b9e\u8df5\u542f\u793a\u4e0e\u843d\u5730\u5efa\u8bae<\/h5>\n\n\n\n<p>1\uff09<strong>\u4f55\u65f6\u9009 ICF<\/strong>\uff1a\u5f53<strong>\u65b0\u57df\u6570\u636e\u96be\u4ee5\u96c6\u4e2d\u5fae\u8c03<\/strong>\u6216<strong>\u9700\u5feb\u901f\u4e0a\u7ebf<\/strong>\u65f6\uff0c\u4f18\u5148\u8003\u8651 ICF\uff1b\u5b83\u5728<strong>23 \u4e2a\u672a\u89c1\u8fc7\u7684\u6570\u636e\u96c6<\/strong>\u4e0a\u7684\u6548\u679c\u4e0e\u9010\u6570\u636e\u96c6\u5fae\u8c03\u76f8\u5f53\uff0c\u4e14\u65e0\u9700\u8bad\u7ec3\u65f6\u5ef6\u3002<br>2\uff09<strong>\u4e0a\u4e0b\u6587\u5927\u5c0f\u4e0e\u65f6\u5ef6\u6743\u8861<\/strong>\uff1a\u793a\u4f8b\u6570\u5e26\u6765\u8fd1\u4f3c<strong>\u5355\u8c03\u7684\u7cbe\u5ea6\u6536\u76ca<\/strong>\u4e0e<strong>\u7ebf\u6027\u589e\u957f\u7684\u63a8\u7406\u8017\u65f6<\/strong>\uff0c\u53ef\u5728 <strong>10\u201350<\/strong> \u7684\u8303\u56f4\u5185\u6309\u9884\u7b97\u53d6\u820d\uff1b\u82e5\u9700\u6700\u4f18\u70b9\uff0c\u4f5c\u8005\u5728\u9a8c\u8bc1\u4e0a\u89c2\u5bdf\u5230<strong>\u603b 34 \u4e2a\u793a\u4f8b\u3001\u5176\u4e2d 11 \u4e2a\u540c\u5e8f\u5217\u8fd1\u5386\u53f2<\/strong>\u7684\u7ec4\u5408\u6700\u4f18\uff08\u4f9b\u53c2\u8003\uff09\u3002<br>3\uff09<strong>\u793a\u4f8b\u9009\u62e9<\/strong>\uff1a\u4f18\u5148\u7eb3\u5165<strong>\u540c\u5e8f\u5217\u8fd1\u5386\u53f2\uff08\u22485\u201311 \u6761\uff09<\/strong>\uff0c\u5e76\u914d\u4ee5<strong>\u968f\u673a\u7684\u8de8\u5e8f\u5217\u793a\u4f8b<\/strong>\u5373\u53ef\u83b7\u5f97\u7a33\u5b9a\u6536\u76ca\uff1b\u590d\u6742\u76f8\u4f3c\u5ea6\u68c0\u7d22\uff08\u5982 DTW\uff09\u5e76\u975e\u5fc5\u8981\u6761\u4ef6\u3002<br>4\uff09<strong>\u6570\u636e\u5de5\u7a0b<\/strong>\uff1a\u6784\u9020\u793a\u4f8b\u957f\u5ea6 <strong>T=640<\/strong>\uff08\u7531 <strong>512 \u5386\u53f2 + 128 \u9884\u6d4b\u5757<\/strong>\uff09\u7684\u6ed1\u7a97\u7247\u6bb5\uff1b\u5bf9\u77ed\u5e8f\u5217\u505a\u5408\u7406<strong>\u5de6\/\u53f3\u586b\u5145<\/strong>\u5e76\u786e\u4fdd\u6ce8\u610f\u529b\u4e0d\u8bef\u8bfb\u586b\u5145\u533a\u57df\u3002<br>5\uff09<strong>\u67b6\u6784\u843d\u5730<\/strong>\uff1a\u52a1\u5fc5\u5b9e\u73b0<strong>\u53ef\u5b66\u4e60\u5206\u9694\u7b26<\/strong>\u4e0e<strong>\u8de8\u793a\u4f8b\u6ce8\u610f\u529b<\/strong>\uff1b\u4f4d\u7f6e\u7f16\u7801\u4e0a\uff0c<strong>NoPE\/FIRE \u7b49\u957f\u5ea6\u7a33\u5065\u65b9\u6848<\/strong>\u66f4\u5229\u4e8e\u8de8\u793a\u4f8b\u3001\u8de8\u957f\u5ea6\u7684\u4e00\u81f4\u6027\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u8bba\u6587In-Context Fine-Tuning for Time-Series Foundation Mod 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