{"id":5613,"date":"2026-10-12T21:56:19","date_gmt":"2026-10-12T13:56:19","guid":{"rendered":"https:\/\/www.15zhi.net\/blog\/?p=5613"},"modified":"2026-10-12T21:56:19","modified_gmt":"2026-10-12T13:56:19","slug":"202610-%e8%ae%ba%e6%96%87%e7%a0%94%e8%af%bb-can-large-language-models-keep-up-benchmarking-online-adaptation-to-continual-knowledge-streams","status":"publish","type":"post","link":"https:\/\/www.15zhi.net\/blog\/202610-%e8%ae%ba%e6%96%87%e7%a0%94%e8%af%bb-can-large-language-models-keep-up-benchmarking-online-adaptation-to-continual-knowledge-streams\/","title":{"rendered":"202610 \u8bba\u6587\u7814\u8bfb-Can Large Language Models Keep Up? Benchmarking Online Adaptation to Continual Knowledge Streams"},"content":{"rendered":"\n

\u4f5c\u8005\uff1aJiyeon Kim\u3001Hyunji Lee\u3001Dylan Zhou \u7b49<\/p>\n\n\n\n

\u5355\u4f4d\uff1aKAIST AI\uff1bUNC Chapel Hill\uff1bGoogle\uff1bKRAFTON\uff1bAdobe Research\uff1bNew York University<\/p>\n\n\n\n

\u6765\u6e90\uff1aACL 2026\uff08Long Papers\uff09<\/p>\n\n\n\n

\u65f6\u95f4\uff1a2026.07<\/p>\n\n\n\n

\u94fe\u63a5\uff1aCan Large Language Models Keep Up? Benchmarking Online Adaptation to Continual Knowledge Streams<\/a><\/p>\n\n\n\n

\u4e00. \u7814\u7a76\u80cc\u666f<\/h3>\n\n\n\n

\u5047\u8bbe\u4e00\u4e2a\u4eba\u5148\u5728\u53a8\u623f\uff0c\u968f\u540e\u53bb\u4e86\u82b1\u56ed\uff0c\u6700\u540e\u8fdb\u5165\u529e\u516c\u5ba4\u3002\u4e24\u4e2a\u7cfb\u7edf\u6700\u7ec8\u90fd\u56de\u7b54\u201c\u529e\u516c\u5ba4\u201d\uff0c\u4f46\u4e00\u4e2a\u59cb\u7ec8\u53ca\u65f6\u66f4\u65b0\uff0c\u53e6\u4e00\u4e2a\u76f4\u5230\u6700\u540e\u624d\u6539\u5bf9\u3002\u8fd9\u4e2a\u7b80\u5355\u4f8b\u5b50\u8bf4\u660e\uff1a\u672b\u6b21\u56de\u7b54\u6b63\u786e\uff0c\u53ef\u80fd\u63a9\u76d6\u4e2d\u95f4\u5f88\u957f\u4e00\u6bb5\u65f6\u95f4\u7684\u9519\u8bef\u3002<\/strong><\/p>\n\n\n\n

\u5f53\u6a21\u578b\u6301\u7eed\u63a5\u6536\u65b0\u8d44\u6599\u65f6\uff0c\u6211\u4eec\u9700\u8981\u540c\u65f6\u89c2\u5bdf\u4e24\u79cd\u80fd\u529b\uff1a\u4e8b\u5b9e\u53d8\u5316\u540e\u80fd\u5426\u8ddf\u4e0a\uff0c\u4e8b\u5b9e\u6ca1\u6709\u53d8\u5316\u65f6\u80fd\u5426\u4fdd\u6301\u6b63\u786e\u3002OAKS \u56f4\u7ed5\u8fd9\u4e24\u4e2a\u95ee\u9898\uff0c\u628a\u4e00\u6b21\u6027\u7684\u957f\u6587\u95ee\u7b54\u6539\u9020\u6210\u6cbf\u4fe1\u606f\u6d41\u6301\u7eed\u8fdb\u884c\u7684\u8bc4\u6d4b\u3002<\/p>\n\n\n\n

\u4e8c. \u8bba\u6587\u6982\u8981<\/h3>\n\n\n\n

OAKS \u662f\u9762\u5411\u6301\u7eed\u77e5\u8bc6\u6d41\u7684\u5728\u7ebf\u9002\u5e94\u8bc4\u6d4b\u57fa\u51c6\u3002\u4f5c\u8005\u5c06\u957f\u6587\u672c\u6309\u987a\u5e8f\u5206\u5757\uff0c\u6bcf\u5230\u8fbe\u4e00\u4e2a\u65b0\u5757\uff0c\u5c31\u5411\u6a21\u578b\u63d0\u51fa\u540c\u4e00\u7ec4\u95ee\u9898\uff0c\u5e76\u6839\u636e\u622a\u81f3\u5f53\u524d\u53ef\u89c1\u7684\u5185\u5bb9\u5224\u65ad\u7b54\u6848\u3002\u8fd9\u91cc\u7684\u201c\u5728\u7ebf\u9002\u5e94\u201d\u4e3b\u8981\u4f53\u73b0\u4e3a\u5229\u7528\u65b0\u589e\u4e0a\u4e0b\u6587\u8ddf\u8e2a\u7b54\u6848\u72b6\u6001\u3002<\/p>\n\n\n\n

\u57fa\u51c6\u5305\u542b\u4e24\u7c7b\u6570\u636e\uff1aOAKS-BABI<\/strong> \u5c06\u53ef\u8ffd\u8e2a\u4e8b\u4ef6\u7a7f\u63d2\u5728\u80cc\u666f\u6587\u672c\u4e2d\uff0c\u5171\u6709 1,224 \u4e2a\u95ee\u9898\uff1bOAKS-Novel<\/strong> \u5bf9\u81ea\u7136\u5c0f\u8bf4\u8fdb\u884c\u9010\u6b65\u6807\u6ce8\uff0c\u53d1\u8868\u7248\u5305\u542b 39 \u672c\u5c0f\u8bf4\u3001870 \u4e2a\u95ee\u9898\u3002\u524d\u8005\u91c7\u7528\u5f00\u653e\u56de\u7b54\uff0c\u540e\u8005\u91c7\u7528\u9009\u62e9\u9898\uff0c\u7528\u4e8e\u89c2\u5bdf\u4e0d\u540c\u60c5\u5883\u4e0b\u7684\u6301\u7eed\u72b6\u6001\u8ddf\u8e2a\u3002<\/p>\n\n\n\n

\u4e09. \u6838\u5fc3\u8bbe\u8ba1\uff1a\u6cbf\u65f6\u95f4\u89c2\u5bdf\u66f4\u65b0\u4e0e\u4fdd\u6301<\/h3>\n\n\n\n

3.1 \u6bcf\u4e2a\u6587\u672c\u524d\u7f00\u90fd\u6709\u81ea\u5df1\u7684\u6b63\u786e\u7b54\u6848<\/h4>\n\n\n\n

\u6587\u672c\u6309\u7ea6 2k token \u5207\u5757\u3002\u65f6\u523b \\(t\\) \u7684\u6a21\u578b\u53ea\u80fd\u4f7f\u7528\u622a\u81f3\u6b64\u65f6\u5df2\u5230\u8fbe\u7684\u4fe1\u606f\uff0c\u8bc4\u6d4b\u4e5f\u4f7f\u7528\u8fd9\u4e2a\u524d\u7f00\u5bf9\u5e94\u7684\u6807\u51c6\u7b54\u6848\uff0c\u800c\u4e0d\u662f\u6545\u4e8b\u7ed3\u675f\u540e\u7684\u6700\u7ec8\u7b54\u6848\u3002<\/p>\n\n\n\n

\"OAKS
\u539f\u6587 Figure 1\uff1a\u6301\u7eed\u77e5\u8bc6\u6d41\u4e2d\u7684\u9010\u6b65\u8bc4\u6d4b\uff08PDF \u7b2c 2 \u9875\uff09\u3002<\/figcaption><\/figure>\n\n\n\n

\u5148\u770b\u56fe\u4e2d\u4e0a\u65b9\u7684\u65f6\u95f4\u7ebf\uff1a\u7070\u8272\u884c\u8868\u793a\u5404\u6b65\u7684\u6b63\u786e\u7b54\u6848\uff0c\u52fe\u53c9\u8868\u793a\u6a21\u578b\u662f\u5426\u7b54\u5bf9\uff1b\u4e0b\u65b9\u5c55\u793a\u5230\u7b2c 29 \u4e2a\u6587\u672c\u5757\u65f6\u7684\u4e00\u6b21\u95ee\u7b54\u3002\u6b63\u786e\u7b54\u6848\u8fde\u7eed\u4e0d\u53d8\u7684\u4e00\u6bb5\u79f0\u4e3a Phase<\/strong>\u3002\u540c\u4e00\u9636\u6bb5\u5185\u4e5f\u53ef\u80fd\u5148\u5bf9\u540e\u9519\uff0c\u56e0\u6b64\u201c\u8ddf\u4e0a\u53d8\u5316\u201d\u548c\u201c\u4fdd\u6301\u6b63\u786e\u201d\u9700\u8981\u5206\u522b\u89c2\u5bdf\uff1bA\u2192B\u2192A \u5219\u5c5e\u4e8e\u4e09\u4e2a\u9636\u6bb5\u3002<\/p>\n\n\n\n

3.2 \u7528\u9519\u8bef\u53d1\u751f\u7684\u4f4d\u7f6e\u89e3\u91ca\u603b\u5206<\/h4>\n\n\n\n

OAKS \u5c06\u6bcf\u4e00\u6b65\u7684\u56de\u7b54\u5206\u4e3a\u56db\u7c7b\uff1a<\/p>\n\n\n\n

    \n
  • ACC\uff1a<\/strong>\u5f53\u524d\u56de\u7b54\u6b63\u786e\u3002<\/li>\n\n\n\n
  • AL\uff1a<\/strong>\u5728\u6700\u7ec8\u66fe\u7b54\u5bf9\u7684\u9636\u6bb5\u4e2d\uff0c\u9996\u6b21\u7b54\u5bf9\u4e4b\u524d\u7684\u9519\u8bef\u3002<\/li>\n\n\n\n
  • DS\uff1a<\/strong>\u9636\u6bb5\u5185\u5df2\u7ecf\u7b54\u5bf9\u8fc7\uff0c\u4e4b\u540e\u53c8\u51fa\u73b0\u7684\u9519\u8bef\u3002<\/li>\n\n\n\n
  • PM\uff1a<\/strong>\u6574\u4e2a\u9636\u6bb5\u4ece\u672a\u7b54\u5bf9\uff0c\u8be5\u9636\u6bb5\u7684\u6240\u6709\u6b65\u90fd\u8ba1\u5165\u3002<\/li>\n<\/ul>\n\n\n\n

    \u4e0b\u9762\u7528\u4e00\u4e2a\u5341\u6b65\u6559\u5b66\u793a\u4f8b<\/strong>\u8bf4\u660e\uff0c\u7ad6\u7ebf\u8868\u793a\u6b63\u786e\u7b54\u6848\u53d1\u751f\u53d8\u5316\uff1a<\/p>\n\n\n\n

    \u6b63\u786e\u7b54\u6848\uff1aA A | B B B B B | C C C\n\u6a21\u578b\u9884\u6d4b\uff1aX Y | B B X B X | X C C<\/pre>\n\n\n\n
    A \u9636\u6bb5\u4e24\u6b65\u5168\u9519\uff0c\u8ba1\u4e3a PM\uff1bB \u9636\u6bb5\u5148\u7b54\u5bf9\uff0c\u4e4b\u540e\u4e24\u6b21\u7b54\u9519\u8ba1\u4e3a DS\uff1bC \u9636\u6bb5\u9996\u6b21\u7b54\u5bf9\u524d\u7684\u4e00\u6b65\u8ba1\u4e3a AL\u3002\u5176\u4f59\u4e94\u6b65\u4e3a ACC\uff0c\u56e0\u6b64\uff1a<\/p>\n\n\n\n
    \n\\[\n\\mathrm{ACC}=\\frac{5}{10}=50\\%,\\quad\n\\mathrm{AL}=10\\%,\\quad\n\\mathrm{DS}=20\\%,\\quad\n\\mathrm{PM}=20\\%\n\\]\n<\/div>\n\n\n\n
    \u56db\u9879\u5171\u7528\u8be5\u9898\u7684\u5168\u90e8\u65f6\u95f4\u6b65\u4f5c\u4e3a\u5206\u6bcd\uff0c\u518d\u8de8\u95ee\u9898\u53d6\u5e73\u5747\u3002<\/strong>\u56e0\u6b64\uff0cPM \u8861\u91cf\u7684\u662f\u6574\u6bb5\u9057\u6f0f\u6240\u5360\u7684\u65f6\u95f4\uff0c\u800c\u4e0d\u662f\u9057\u6f0f\u4e86\u591a\u5c11\u4e2a\u9636\u6bb5\u3002\u8fd9\u4e2a\u5206\u89e3\u8ba9\u76f8\u540c\u51c6\u786e\u7387\u80cc\u540e\u7684\u4e0d\u540c\u9519\u8bef\u8fc7\u7a0b\u53d8\u5f97\u53ef\u89c1\u3002<\/p>\n\n\n\n
    \u56db. \u5b9e\u9a8c\u7ed3\u679c\u4e0e\u4e3b\u8981\u53d1\u73b0<\/h3>\n\n\n\n
    4.1 RAG \u7684\u6536\u76ca\u53d6\u51b3\u4e8e\u6a21\u578b\u914d\u7f6e<\/h4>\n\n\n\n
    Base \u4f7f\u7528\u7d2f\u79ef\u7684\u5df2\u89c1\u6587\u672c\uff0c\u8d85\u51fa\u9884\u7b97\u65f6\u622a\u53bb\u8f83\u65e9\u90e8\u5206\uff1bRAG \u5219\u4ece\u5df2\u5230\u8fbe\u7684\u6587\u672c\u5757\u4e2d\u68c0\u7d22\u76f8\u5173\u5185\u5bb9\uff0c\u901a\u5e38\u53d6 top-30\u3002\u4e0b\u8868\u9009\u53d6\u539f\u6587\u8868 2 \u7684\u5168\u90e8\u4e94\u7ec4\u975e Thinking \u7684 Qwen3 \u914d\u7f6e\uff0c\u6bd4\u8f83 OAKS-B\/All \u7684\u51c6\u786e\u7387\uff0c\u5355\u4f4d\u4e3a %\u3002<\/p>\n\n\n\n
    Qwen3 \u89c4\u6a21<\/th>Base<\/th>RAG<\/th><\/tr><\/thead>
    4B<\/td>26.4<\/td>29.3<\/td><\/tr>
    8B<\/td>33.1<\/td>35.1<\/td><\/tr>
    30B<\/td>35.8<\/td>37.8<\/td><\/tr>
    80B<\/td>41.1<\/td>43.5<\/td><\/tr>
    235B<\/td>46.8<\/td>44.7<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
    \u524d\u56db\u7ec4\u63d0\u9ad8\u4e86 2.0\uff5e2.9 \u4e2a\u767e\u5206\u70b9\uff0c235B \u5219\u4e0b\u964d 2.1 \u4e2a\u767e\u5206\u70b9\u3002\u56e0\u6b64\uff0cRAG \u7684\u6536\u76ca\u9700\u8981\u7ed3\u5408\u5177\u4f53\u6a21\u578b\u4e0e\u4efb\u52a1\u8bbe\u7f6e\u5224\u65ad\u3002<\/p>\n\n\n\n
    4.2 \u51c6\u786e\u7387\u63d0\u9ad8\u540e\uff0c\u9519\u8bef\u53bb\u4e86\u54ea\u91cc<\/h4>\n\n\n\n
    \u539f\u6587\u8868 6 \u7ed9\u51fa\u4e86 Qwen3-30B \u5728 OAKS-B\u3001Base \u8bbe\u7f6e\u4e0b\u7684\u9519\u8bef\u6784\u6210\uff0c\u5355\u4f4d\u540c\u6837\u4e3a %\uff1a<\/p>\n\n\n\n
    \u914d\u7f6e<\/th>ACC<\/th>AL<\/th>DS<\/th>PM<\/th><\/tr><\/thead>
    \u975e Thinking<\/td>35.8<\/td>6.9<\/td>34.0<\/td>23.2<\/td><\/tr>
    Thinking<\/td>43.6<\/td>9.0<\/td>37.0<\/td>10.4<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
    Thinking \u914d\u7f6e\u7684 ACC \u63d0\u9ad8 7.8 \u4e2a\u767e\u5206\u70b9\uff0cPM \u51cf\u5c11 12.8 \u4e2a\u767e\u5206\u70b9\uff0c\u6536\u76ca\u4e3b\u8981\u4f53\u73b0\u4e3a\u6574\u6bb5\u9057\u6f0f\u7684\u65f6\u95f4\u51cf\u5c11\u3002\u4e0e\u6b64\u540c\u65f6\uff0cAL \u548c DS \u90fd\u589e\u52a0\u4e86\u3002<\/p>\n\n\n\n
    \u7406\u89e3\u8fd9\u4e00\u53d8\u5316\uff0c\u9700\u8981\u628a\u56db\u9879\u4e00\u8d77\u8bfb\uff1a\u4e00\u4e2a\u539f\u672c\u5168\u9519\u7684\u9636\u6bb5\u53ea\u8981\u51fa\u73b0\u4e00\u6b21\u6b63\u786e\u56de\u7b54\uff0c\u5269\u4f59\u9519\u8bef\u5c31\u53ef\u80fd\u4ece PM \u8f6c\u5165 AL \u6216 DS\u3002<\/strong>\u56e0\u6b64\uff0cDS \u4e0a\u5347\u4e0d\u80fd\u5355\u72ec\u89e3\u91ca\u6210\u6297\u5e72\u6270\u80fd\u529b\u4e0b\u964d\u3002\u4e24\u884c\u6bd4\u8f83\u8fd8\u6d89\u53ca\u4e0d\u540c\u6a21\u578b\u68c0\u67e5\u70b9\u548c\u91c7\u6837\u8bbe\u7f6e\uff0c\u5e94\u6309\u4e24\u5957\u5b8c\u6574\u914d\u7f6e\u7406\u89e3\u3002<\/p>\n\n\n\n
    4.3 \u77e5\u8bc6\u6d41\u63a8\u8fdb\u540e\uff0c\u51c6\u786e\u7387\u600e\u6837\u53d8\u5316<\/h4>\n\n\n\n
    \"\u51c6\u786e\u7387\u968f\u77e5\u8bc6\u6d41\u8fdb\u5ea6\u53d8\u5316\uff1aOAKS-B
    \u539f\u6587 Figure 3\uff1a\u51c6\u786e\u7387\u968f\u77e5\u8bc6\u6d41\u8fdb\u5ea6\u53d8\u5316\uff08PDF \u7b2c 8 \u9875\uff09\u3002<\/figcaption><\/figure>\n\n\n\n
    \u8fd9\u5f20\u56fe\u6765\u81ea Qwen3-30B \u7684\u5206\u6790\uff1a\u6a2a\u8f74\u662f\u77e5\u8bc6\u6d41\u63a8\u8fdb\u6bd4\u4f8b\uff0c\u7eb5\u8f74\u662f\u51c6\u786e\u7387\u3002OAKS-B \u7684\u84dd\u8272\u5b9e\u7ebf\u968f\u8fdb\u5ea6\u6574\u4f53\u4e0b\u964d\uff0c\u6865\u63a5\u4e0e\u8ddf\u8e2a\u9898\u5728\u540e\u6bb5\u5904\u4e8e\u8f83\u4f4e\u6c34\u5e73\uff1bOAKS-N \u7684\u7ea2\u7ebf\u4e0b\u964d\u76f8\u5bf9\u8f83\u7f13\u3002\u65e9\u671f\u7b54\u5f97\u597d\uff0c\u5e76\u4e0d\u4ee3\u8868\u80fd\u6301\u7eed\u8ddf\u4e0a\u3002<\/strong>\u8fd9\u4e5f\u89e3\u91ca\u4e86\u4e3a\u4ec0\u4e48\u8981\u6cbf\u65f6\u95f4\u8bc4\u6d4b\u3002<\/p>\n\n\n\n
    \u4e94. \u8bfe\u9898\u5bf9\u9f50\u601d\u8003<\/h3>\n\n\n\n
    \u5bf9\u98df\u54c1\u8bc1\u636e\u77e5\u8bc6\u6784\u5efa\u4e0e\u53ef\u4fe1\u66f4\u65b0\uff0cOAKS \u6700\u503c\u5f97\u501f\u9274\u7684\u662f\u628a\u66f4\u65b0\u8fc7\u7a0b\u672c\u8eab\u53d8\u6210\u8bc4\u4ef7\u5bf9\u8c61<\/strong>\u3002\u5305\u88c5\u56fe\u7247\u3001OCR \u4e0e\u8865\u5145\u6750\u6599\u9010\u6b65\u5230\u8fbe\u65f6\uff0c\u53ef\u4ee5\u6301\u7eed\u68c0\u67e5\u540c\u4e00\u7ec4\u98df\u54c1\u547d\u9898\uff1a\u54ea\u4e9b\u5e94\u65b0\u589e\u6216\u4fee\u8ba2\uff0c\u54ea\u4e9b\u5e94\u53bb\u91cd\u3001\u4fdd\u7559\u51b2\u7a81\u6216\u6682\u7f13\uff0c\u4ee5\u53ca\u539f\u672c\u6b63\u786e\u7684\u547d\u9898\u662f\u5426\u88ab\u8bef\u6539\u3002<\/p>\n\n\n\n
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