{"id":34710,"date":"2024-12-11T11:57:42","date_gmt":"2024-12-11T03:57:42","guid":{"rendered":"https:\/\/17aitech.com\/?p=34710"},"modified":"2024-12-11T11:57:42","modified_gmt":"2024-12-11T03:57:42","slug":"%e4%b8%ba%e5%a4%a7%e6%a8%a1%e5%9e%8b%e6%8f%90%e4%be%9b%e5%85%a8%e6%96%b0%e7%a7%91%e5%ad%a6%e5%a4%8d%e6%9d%82%e9%97%ae%e7%ad%94%e5%9f%ba%e5%87%86%e4%b8%8e%e6%b5%8b%e8%af%84%e4%bd%93%e7%b3%bb%ef%bc%8cun","status":"publish","type":"post","link":"https:\/\/17aitech.com\/?p=34710","title":{"rendered":"\u4e3a\u5927\u6a21\u578b\u63d0\u4f9b\u5168\u65b0\u79d1\u5b66\u590d\u6742\u95ee\u7b54\u57fa\u51c6\u4e0e\u6d4b\u8bc4\u4f53\u7cfb\uff0cUNSW\u3001\u963f\u8d21\u3001\u829d\u52a0\u54e5\u5927\u5b66\u7b49\u591a\u5bb6\u673a\u6784\u8054\u5408\u63a8\u51faSciQAG\u6846\u67b6"},"content":{"rendered":"

\u6587\u7ae0\u6765\u6e90\u4e8e\u4e92\u8054\u7f51:\u4e3a\u5927\u6a21\u578b\u63d0\u4f9b\u5168\u65b0\u79d1\u5b66\u590d\u6742\u95ee\u7b54\u57fa\u51c6\u4e0e\u6d4b\u8bc4\u4f53\u7cfb\uff0cUNSW\u3001\u963f\u8d21\u3001\u829d\u52a0\u54e5\u5927\u5b66\u7b49\u591a\u5bb6\u673a\u6784\u8054\u5408\u63a8\u51faSciQAG\u6846\u67b6<\/a><\/p>\n

<\/a><\/p>\n

\u7f16\u8f91 | ScienceAI<\/p>\n

\u95ee\u7b54\uff08QA\uff09\u6570\u636e\u96c6\u5728\u63a8\u52a8\u81ea\u7136\u8bed\u8a00\u5904\u7406<\/mark>\uff08NLP\uff09\u7814\u7a76\u53d1\u6325\u7740\u81f3\u5173\u91cd\u8981\u7684\u4f5c\u7528\u3002\u9ad8\u8d28\u91cfQA\u6570\u636e\u96c6\u4e0d\u4ec5\u53ef\u4ee5\u7528\u4e8e\u5fae\u8c03\u6a21\u578b\uff0c\u4e5f\u53ef\u4ee5\u6709\u6548\u8bc4\u4f30\u5927\u8bed\u8a00\u6a21\u578b<\/mark>\uff08LLM\uff09\u7684\u80fd\u529b\uff0c\u5c24\u5176\u662f\u9488\u5bf9\u79d1\u5b66\u77e5\u8bc6\u7684\u7406\u89e3\u548c\u63a8\u7406\u80fd\u529b\u3002<\/p>\n

\u5c3d\u7ba1\u5f53\u524d\u5df2\u6709\u8bb8\u591a\u79d1\u5b66QA\u6570\u636e\u96c6\uff0c\u6db5\u76d6\u4e86\u533b\u5b66\u3001\u5316\u5b66\u3001\u751f\u7269\u7b49\u9886\u57df\uff0c\u4f46\u8fd9\u4e9b\u6570\u636e\u96c6\u4ecd\u5b58\u5728\u4e00\u4e9b\u4e0d\u8db3\u3002<\/p>\n

\u5176\u4e00\uff0c\u6570\u636e\u5f62\u5f0f\u8f83\u4e3a\u5355\u4e00\uff0c\u5927\u591a\u6570\u4e3a\u591a\u9879\u9009\u62e9\u9898\uff08multiple-choice questions\uff09\uff0c\u5b83\u4eec\u6613\u4e8e\u8fdb\u884c\u8bc4\u4f30\uff0c\u4f46\u9650\u5236\u4e86\u6a21\u578b\u7684\u7b54\u6848\u9009\u62e9<\/mark>\u8303\u56f4\uff0c\u65e0\u6cd5\u5145\u5206\u6d4b\u8bd5\u6a21\u578b\u7684\u79d1\u5b66\u95ee\u9898\u89e3\u7b54\u80fd\u529b\u3002\u76f8\u6bd4\u4e4b\u4e0b\uff0c\u5f00\u653e\u5f0f\u95ee\u7b54(openQA)\u53ef\u4ee5\u66f4\u52a0\u5168\u9762\u5730\u8bc4\u4f30\u6a21\u578b\u7684\u80fd\u529b\uff0c\u4f46\u7f3a\u4e4f\u5408\u9002\u7684\u8bc4\u4f30\u6307\u6807\u3002<\/p>\n

\u5176\u4e8c\uff0c\u73b0\u6709\u6570\u636e\u96c6\u7684\u5185\u5bb9\u5f88\u591a\u6765\u6e90\u4e8e\u5927\u5b66\u53ca\u4ee5\u4e0b\u7b49\u7ea7\u7684\u6559\u79d1\u4e66\uff0c\u96be\u4ee5\u8bc4\u4f30LLM\u5728\u5b9e\u9645\u5b66\u672f\u7814\u7a76\u6216\u751f\u4ea7\u73af\u5883\u4e2d\u7684\u9ad8\u5c42\u6b21\u77e5\u8bc6\u4fdd\u6301\u80fd\u529b\u3002<\/p>\n

\u5176\u4e09\uff0c\u8fd9\u4e9b\u57fa\u51c6<\/mark>\u6570\u636e\u96c6\u7684\u521b\u5efa\u4f9d\u8d56\u4eba\u7c7b\u4e13\u5bb6\u6807\u6ce8\u3002<\/p>\n

\u5e94\u5bf9\u8fd9\u4e9b\u6311\u6218\u5bf9\u5efa\u7acb\u66f4\u5168\u9762\u7684QA\u6570\u636e\u96c6\u81f3\u5173\u91cd\u8981\uff0c\u4e5f\u6709\u5229\u4e8e\u5bf9\u79d1\u5b66LLM\u7684\u66f4\u7cbe\u51c6\u8bc4\u4f30\u3002<\/p>\n

<\/a><\/p>\n

\u56fe\u793a\uff1a\u4ece\u79d1\u5b66\u6587\u732e\u4e2d\u751f\u6210\u9ad8\u8d28\u91cf\u79d1\u5b66\u95ee\u7b54\u5bf9\u7684SciQAG\u6846\u67b6\u3002<\/p>\n

\u4e3a\u6b64\uff0c\u7f8e\u56fdArgonne\u56fd\u5bb6\u5b9e\u9a8c\u5ba4\u3001\u829d\u52a0\u54e5\u5927\u5b66Ian Foster \u6559\u6388\uff082002\u5e74\u6208\u767b\u8d1d\u5c14\u5956\u5f97\u4e3b\uff09\u56e2\u961f\u3001\u6fb3\u5927\u5229\u4e9a\u65b0\u5357\u5a01\u5c14\u58eb\u5927\u5b66Bram Hoex\u6559\u6388UNSW AI4Science\u56e2\u961f\u3001AI4Science \u516c\u53f8GreenDynamics \u4e0e\u9999\u6e2f\u57ce\u5e02\u5927\u5b66\u63ed\u6625\u96e8\u6559\u6388\u56e2\u961f\u8054\u5408\u63d0\u51fa\u4e86 SciQAG\uff0c\u7b2c\u4e00\u4e2a\u57fa\u4e8e\u5927\u8bed\u8a00\u6a21\u578b<\/mark>\uff08LLM\uff09\u4ece\u5927\u578b\u79d1\u5b66\u6587\u732e\u8bed\u6599\u5e93<\/mark>\u4e2d\u81ea\u52a8\u751f\u6210\u9ad8\u8d28\u91cf\u79d1\u5b66\u5f00\u653e\u6027\u95ee\u7b54\u5bf9\u7684\u65b0\u578b\u6846\u67b6\u3002<\/p>\n

<\/a><\/p>\n

<\/p>\n

\u8bba\u6587\u94fe\u63a5\uff1ahttps:\/\/arxiv.org\/abs\/2405.09939<\/em><\/p>\n

github\u94fe\u63a5\uff1ahttps:\/\/github.com\/MasterAI-EAM\/SciQAG<\/em><\/p>\n

\u57fa\u4e8eSciQAG\uff0c\u7814\u7a76\u4eba\u5458\u6784\u5efa\u4e86\u4e00\u4e2a\u5927\u89c4\u6a21\u3001\u9ad8\u8d28\u91cf\u3001\u5f00\u653e\u5f0f\u7684\u79d1\u5b66QA\u6570\u636e\u96c6 SciQAG-24D \uff0c\u5305\u542b\u4ece24\u4e2a\u79d1\u5b66\u9886\u57df\u768422,743\u7bc7\u79d1\u5b66\u8bba\u6587\u4e2d\u63d0\u53d6\u7684188,042 \u4e2aQA\u5bf9\uff0c\u65e8\u5728\u670d\u52a1LLM\u7684\u5fae\u8c03\u548c\u79d1\u5b66\u95ee\u9898\u89e3\u7b54\u80fd\u529b\u8bc4\u4f30\u3002<\/p>\n

\u5b9e\u9a8c\u8bc1\u660e\uff0c\u5728 SciQAG-24D \u6570\u636e\u96c6\u4e0a\u5bf9 LLM \u8fdb\u884c\u5fae\u8c03\u53ef\u4ee5\u663e\u8457\u63d0\u9ad8\u5b83\u4eec\u5728\u5f00\u653e\u5f0f\u95ee\u9898\u89e3\u7b54\u548c\u79d1\u5b66\u4efb\u52a1\u4e2d\u7684\u6027\u80fd\u3002<\/p>\n

\u6570\u636e\u96c6\u3001\u6a21\u578b\u548c\u8bc4\u4f30\u4ee3\u7801\u5df2\u7ecf\u5f00\u6e90(https:\/\/github.com\/MasterAI-EAM\/SciQAG)\uff0c\u4ee5\u4fc3\u8fdbAI for Science\u793e\u533a\u5bf9\u5f00\u653e\u5f0f\u79d1\u5b66\u95ee\u7b54\u7684\u5171\u540c\u5f00\u53d1\u3002<\/p>\n

SciQAG\u6846\u67b6\u4e0eSciQAG-24D\u57fa\u51c6<\/mark>\u6570\u636e\u96c6<\/strong><\/p>\n

SciQAG\u7531QA\u751f\u6210\u5668\u548cQA\u8bc4\u4f30\u5668\u7ec4\u6210\uff0c\u65e8\u5728\u5927\u89c4\u6a21\u5feb\u901f\u751f\u6210\u57fa\u4e8e\u79d1\u5b66\u6587\u732e\u7684\u591a\u6837\u5316\u5f00\u653e\u5f0f\u95ee\u7b54\u5bf9\u3002\u9996\u5148\uff0c\u751f\u6210\u5668\u5c06\u79d1\u5b66\u8bba\u6587\u8f6c\u6362\u4e3a\u95ee\u7b54\u5bf9\uff0c\u7136\u540e\u8bc4\u4f30\u5668\u8fc7\u6ee4\u6389\u4e0d\u7b26\u5408\u8d28\u91cf\u6807\u51c6\u7684\u95ee\u7b54\u5bf9\uff0c\u4ece\u800c\u83b7\u5f97\u9ad8\u8d28\u91cf\u7684\u79d1\u5b66\u95ee\u7b54\u6570\u636e\u96c6\u3002<\/p>\n

QA\u751f\u6210\u5668<\/strong><\/p>\n

\u7814\u7a76\u4eba\u5458\u7ecf\u8fc7\u5bf9\u6bd4\u5b9e\u9a8c\u8bbe\u8ba1\u4e86\u4e24\u6b65\u63d0\u793a\u8bcd\uff08prompt\uff09\uff0c\u4ee4LLM\u5148\u63d0\u53d6\u5173\u952e\u8bcd\uff0c\u518d\u57fa\u4e8e\u5173\u952e\u8bcd\u751f\u6210\u95ee\u7b54\u5bf9\u3002<\/p>\n

\u7531\u4e8e\u751f\u6210\u7684\u95ee\u7b54\u6570\u636e\u96c6\u91c7\u7528\u300c\u95ed\u5377\u300d\u6a21\u5f0f\uff0c\u5373\u4e0d\u63d0\u4f9b\u539f\u59cb\u8bba\u6587\uff0c\u53ea\u5173\u6ce8\u63d0\u53d6\u51fa\u7684\u79d1\u5b66\u77e5\u8bc6\u672c\u8eab\uff0cprompt\u8981\u6c42\u751f\u6210\u7684\u95ee\u7b54\u5bf9\u4e0d\u4f9d\u8d56\u6216\u53c2\u8003\u539f\u59cb\u8bba\u6587\u4e2d\u7684\u7279\u6709\u4fe1\u606f\uff08\u4f8b\u5982\u4e0d\u5f97\u51fa\u73b0\u4ee3\u79f0\u5982\u300c\u672c\/\u8be5\u8bba\u6587\u300d\uff0c\u300c\u672c\/\u8be5\u7814\u7a76\u300d\u7b49\u5b57\u6837\uff0c\u6216\u5411\u6587\u4e2d\u8868\u683c\/\u56fe\u7247\u63d0\u95ee\uff09\u3002<\/p>\n

\u4e3a\u4e86\u5e73\u8861\u6027\u80fd\u548c\u6210\u672c\uff0c\u7814\u7a76\u4eba\u5458\u9009\u62e9\u5fae\u8c03\u4e00\u4e2a\u5f00\u6e90LLM\u4f5c\u4e3a\u751f\u6210\u5668\u3002SciQAG\u7528\u6237\u53ef\u4ee5\u6839\u636e\u81ea\u8eab\u60c5\u51b5\u9009\u62e9\u4efb\u4f55\u5f00\u6e90\u6216\u95ed\u6e90LLM\u4f5c\u4e3a\u751f\u6210\u5668\uff0c\u65e2\u53ef\u4ee5\u4f7f\u7528\u5fae\u8c03\uff0c\u4e5f\u53ef\u4ee5\u4f7f\u7528\u63d0\u793a\u8bcd\u5de5\u7a0b\u3002<\/p>\n

QA\u8bc4\u4f30\u5668<\/strong><\/p>\n

\u8bc4\u4f30\u5668\u7528\u4e8e\u5b8c\u6210\u4e24\u4e2a\u76ee\u7684\uff1a\uff081\uff09\u8bc4\u4f30\u751f\u6210\u7684\u95ee\u7b54\u5bf9\u8d28\u91cf\uff1b\uff082\uff09\u57fa\u4e8e\u8bbe\u5b9a\u6807\u51c6\u6452\u5f03\u4f4e\u8d28\u91cf\u7684\u95ee\u7b54\u5bf9\u3002<\/p>\n

\u7814\u7a76\u4eba\u5458\u5f00\u53d1\u4e86\u4e00\u4e2a\u7efc\u5408\u8bc4\u4f30\u6307\u6807 RACAR\uff0c\u5b83\u7531\u4e94\u4e2a\u7ef4\u5ea6\u7ec4\u6210\uff1a\u76f8\u5173\u6027\uff08relevance\uff09\u3001\u4e0d\u53ef\u77e5\u6027\uff08agnosticism\uff09\u3001\u5b8c\u6574\u6027\uff08completeness\uff09\u3001\u51c6\u786e\u6027\uff08accuracy\uff09\u548c\u5408\u7406\u6027\uff08reasonableness\uff09\u3002<\/p>\n

\u5728\u672c\u7814\u7a76\u4e2d\uff0c\u7814\u7a76\u4eba\u5458\u76f4\u63a5\u4f7f\u7528 GPT-4 \u4f5c\u4e3a QA \u8bc4\u4f30\u5668\uff0c\u6309\u7167RACAR\u5bf9\u751f\u6210\u7684 QA \u5bf9\u8fdb\u884c\u8bc4\u4f30\uff0c\u8bc4\u4f30\u7b49\u7ea7\u4e3a 1-5\uff081 \u8868\u793a\u4e0d\u53ef\u63a5\u53d7\uff0c5 \u8868\u793a\u5b8c\u5168\u53ef\u4ee5\u63a5\u53d7\uff09\u3002<\/p>\n

\u5982\u56fe\u6240\u793a\uff0c\u4e3a\u4e86\u8861\u91cf GPT-4 \u4e0e\u4eba\u5de5\u8bc4\u4f30\u4e4b\u95f4\u7684\u4e00\u81f4\u6027\uff0c\u4e24\u4f4d\u9886\u57df\u4e13\u5bb6\u4f7f\u7528 RACAR \u6307\u6807\u5bf9 10 \u7bc7\u6587\u7ae0\uff08\u5171 100 \u95ee\u7b54\u5bf9\uff09\u8fdb\u884c\u4eba\u5de5\u8bc4\u4f30\u3002\u7528\u6237\u53ef\u4ee5\u6839\u636e\u81ea\u8eab\u9700\u6c42\u9009\u62e9\u4efb\u4f55\u5f00\u6e90\u6216\u95ed\u6e90LLM\u4f5c\u4e3a\u8bc4\u4f30\u5668\u3002<\/p>\n

<\/a><\/p>\n

<\/p>\n

\u56fe\u793a\uff1aGPT-4 \u5206\u914d\u5206\u6570\u4e0e\u4e13\u5bb6\u6807\u6ce8\u5206\u6570\u4e4b\u95f4\u7684 Spearman \u548c Pearson \u76f8\u5173\u6027\u3002<\/p>\n

SciQAG \u6846\u67b6\u7684\u8fd0\u7528<\/strong><\/p>\n

\u8be5\u7814\u7a76\u4eceWeb of Science (WoS)\u6838\u5fc3\u5408\u96c6\u6570\u636e\u5e93<\/mark>\u4e2d\u83b7\u53d6\u4e8624\u7c7b\u9ad8\u5f15\u7528\u8bba\u6587\u5171\u8ba122,743\u7bc7\uff0c\u6765\u81ea\u6750\u6599\u79d1\u5b66\u3001\u5316\u5b66\u3001\u7269\u7406\u3001\u80fd\u6e90\u7b49\u9886\u57df\uff0c\u65e8\u5728\u6784\u5efa\u4e00\u4e2a\u53ef\u9760\u3001\u4e30\u5bcc\u3001\u5e73\u8861\u4e14\u5177\u6709\u4ee3\u8868\u6027\u7684\u79d1\u5b66\u77e5\u8bc6\u6765\u6e90\u3002<\/p>\n

\u4e3a\u4e86\u5fae\u8c03\u5f00\u6e90LLM\u4ee5\u5f62\u6210QA\u751f\u6210\u5668\uff0c\u7814\u7a76\u4eba\u5458\u4ece\u8bba\u6587\u96c6\u5408\u4e2d\u968f\u673a\u9009\u62e9426\u7bc7\u8bba\u6587\u4f5c\u4e3a\u8f93\u5165\uff0c\u901a\u8fc7\u63d0\u793aGPT-4\u751f\u62104260\u4e2a\u79cd\u5b50QA\u5bf9\u3002<\/p>\n

\u7136\u540e\uff0c\u7814\u7a76\u4eba\u5458\u5728\u8fd9\u4e9b\u79cd\u5b50\u6570\u636e\u4e0a\u5fae\u8c03\u4e86Vicuna-7b\u6a21\u578b\uff0c\u751f\u6210\u63d0\u793a\u88ab\u8f6c\u6362\u4e3a\u6307\u4ee4\uff0c\u8bba\u6587\u5185\u5bb9\u586b\u5145\u8f93\u5165\u5b57\u6bb5\uff0c\u8f93\u51fa\u4e3a\u751f\u6210\u7684QA\u5bf9<\/p>\n

\uff0c\u4ee5\u6807\u51c6\u76d1\u7763\u7684\u65b9\u5f0f\u8bad\u7ec3\u6a21\u578b\u751f\u6210\u5b9e\u4f8b\u8f93\u51fa\u3002<\/p>\n<\/section>\n

\n

\u4f7f\u7528\u7ecf\u8fc7\u8bad\u7ec3\u7684QA\u751f\u6210\u5668\u5728\u5269\u4f59\u8bba\u6587\u4e0a\u8fdb\u884c\u63a8\u7406\uff0c\u5171\u751f\u6210227,430\u4e2aQA\u5bf9\uff08\u5305\u62ec\u79cd\u5b50QA\u5bf9\uff09\u3002\u4ece\u6bcf\u4e2a\u7c7b\u522b\u4e2d\u62bd\u53d650\u7bc7\u8bba\u6587\uff08\u51711,200\u7bc7\uff09\uff0c\u4f7f\u7528GPT-4\u8ba1\u7b97\u6bcf\u4e2a\u751f\u6210\u7684QA\u5bf9\u7684RACAR\u5206\u6570\uff0c\u8fc7\u6ee4\u6389\u4efb\u4e00\u7ef4\u5206\u6570\u4f4e\u4e8e3\u7684QA\u5bf9\u4f5c\u4e3a\u6d4b\u8bd5\u96c6\u3002<\/p>\n<\/section>\n

\n

\u5bf9\u4e8e\u4f59\u4e0b\u7684QA\u5bf9\uff0c\u5219\u4f7f\u7528\u57fa\u4e8e\u89c4\u5219\u7684\u65b9\u6cd5\u8fc7\u6ee4\u6389\u6240\u6709\u5305\u542b\u8bba\u6587\u7279\u6709\u4fe1\u606f\u7684\u95ee\u7b54\u5bf9\u4ee5\u5f62\u6210\u8bad\u7ec3\u96c6\u3002<\/p>\n<\/section>\n

SciQAG-24D \u57fa\u51c6<\/mark>\u6570\u636e\u96c6<\/strong><\/p>\n

\u57fa\u4e8e\u4ee5\u4e0a\uff0c\u7814\u7a76\u4eba\u5458\u5efa\u7acb\u4e86\u5f00\u653e\u5f0f\u79d1\u5b66 QA \u57fa\u51c6<\/mark>\u6570\u636e\u96c6 SciQAG-24D\uff0c\u7b5b\u9009\u540e\u7684\u8bad\u7ec3\u96c6\u5305\u62ec 21,529 \u7bc7\u8bba\u6587\u548c 179,511 \u4e2a QA \u5bf9\uff0c\u800c\u7b5b\u9009\u540e\u7684\u6d4b\u8bd5\u96c6\u5305\u542b 1,199 \u7bc7\u8bba\u6587\u548c 8,531 \u4e2a QA \u5bf9\u3002<\/p>\n

\u7edf\u8ba1\u663e\u793a\uff0c99.15%\u56de\u7b54\u4e2d\u7684\u6570\u636e\u6765\u81ea\u539f\u8bba\u6587\uff0c87.29%\u7684\u95ee\u9898\u76f8\u4f3c\u5ea6\u57280.3\u4ee5\u4e0b\uff0c\u4e14\u56de\u7b54\u5bf9\u539f\u6587\u5185\u5bb9\u7684\u8986\u76d6\u5ea6\u8fbe\u523078.26%\u3002<\/p>\n

\u8be5\u6570\u636e\u96c6\u5e94\u7528\u5e7f\u6cdb\uff1a\u8bad\u7ec3\u96c6\u53ef\u7528\u4e8e\u5fae\u8c03 LLM\uff0c\u4e3a\u5176\u6ce8\u5165\u79d1\u5b66\u77e5\u8bc6\uff1b\u6d4b\u8bd5\u96c6\u53ef\u2f64\u4e8e\u8bc4\u4f30LLM\u5728\u67d0\u7279\u5b9a\u6216\u6574\u4f53\u79d1\u5b66\u9886\u57df\u4e2d\u7684\u5f00\u653e\u5f0fQA\u4efb\u52a1\u8868\u73b0\u3002\u7531\u4e8e\u6d4b\u8bd5\u96c6\u8f83\u5927\uff0c\u56e0\u6b64\u5b83\u4e5f\u53ef\u4ee5\u4f5c\u4e3a\u9ad8\u8d28\u91cf\u6570\u636e\u7528\u4e8e\u5fae\u8c03\u3002<\/p>\n

<\/a><\/p>\n

<\/p>\n

\u56fe\u793a\uff1aSciQAG-24D\u6570\u636e\u96c6\u8bad\u7ec3\u548c\u6d4b\u8bd5\u4e2d\u4e0d\u540c\u7c7b\u522b\u7684\u6587\u7ae0\u6bd4\u4f8b\u3002<\/p>\n

\u5b9e\u9a8c\u7ed3\u679c<\/strong><\/p>\n

\u7814\u7a76\u4eba\u5458\u8fdb\u884c\u4e86\u5168\u9762\u7684\u5b9e\u9a8c\u4ee5\u5bf9\u6bd4\u4e0d\u540c\u8bed\u8a00\u6a21\u578b<\/mark>\u4e4b\u95f4\u7684\u79d1\u5b66\u95ee\u7b54\u6027\u80fd\u5dee\u5f02\u53ca\u63a2\u7d22\u5fae\u8c03\u7684\u5f71\u54cd\u3002<\/p>\n

\u96f6\u6837\u672c\u8bbe\u5b9a\uff08zero-shot setting)\u00a0<\/strong><\/p>\n

\u7814\u7a76\u4eba\u5458\u4f7f\u7528 SciQAG-24D \u4e2d\u7684\u90e8\u5206\u6d4b\u8bd5\u96c6\u5bf9\u4e94\u4e2a\u6a21\u578b\u8fdb\u884c\u4e86\u96f6\u6837\u672c\u6027\u80fd\u5bf9\u6bd4\u3002\u5176\u4e2d\u4e24\u4e2a\u662f\u5f00\u6e90\u7684 LLM\uff1aLLaMA1 (7B) \u548c LLaMA2-chat (7B)\uff0c\u5176\u4f59\u7684\u662f\u95ed\u6e90 LLM \u3002<\/p>\n

\u901a\u8fc7API\u8c03\u7528\uff1aGPT3.5 (gpt-3.5-turbo)\u3001GPT-4 (gpt-4-1106-preview) \u548c Claude 3 (claude-3-opus-20240229)\u3002\u6bcf\u4e2a\u6a21\u578b\u5728\u6d4b\u8bd5\u4e2d\u88ab\u63d0\u793a\u4e86 1000 \u4e2a\u95ee\u9898\uff0c\u5e76\u901a\u8fc7 CAR \u6307\u6807\uff08\u7531RACAR\u6307\u6807\u8c03\u6574\u800c\u6765\uff0c\u53ea\u5173\u6ce8\u56de\u7b54\u8bc4\u4f30\uff09\u8bc4\u4f30\u5176\u8f93\u51fa\uff0c\u4ee5\u8861\u91cf\u5176\u5728\u56de\u7b54\u79d1\u5b66\u7814\u7a76\u95ee\u9898\u65b9\u9762\u7684\u96f6\u6837\u672c\u80fd\u529b\u3002<\/p>\n

\u5982\u56fe\u6240\u793a\uff0c\u5728\u6240\u6709\u6a21\u578b\u4e2d\uff0cGPT-4 \u5728\u5b8c\u5907\u6027\uff084.90\uff09\u548c\u5408\u7406\u6027\uff084.99\uff09\u65b9\u9762\u5f97\u5206\u6700\u9ad8\uff0c\u800c Claude 3 \u7684\u51c6\u786e\u6027\u5f97\u5206\u6700\u9ad8\uff084.95\uff09\u3002GPT-3.5 \u7684\u8868\u73b0\u4e5f\u975e\u5e38\u51fa\u8272\uff0c\u5728\u6240\u6709\u6307\u6807\u4e0a\u7684\u5f97\u5206\u90fd\u7d27\u968f GPT-4 \u548c Claude 3 \u4e4b\u540e\u3002<\/p>\n

\u503c\u5f97\u6ce8\u610f\u7684\u662f\uff0cLLaMA1 \u5728\u6240\u6709\u4e09\u4e2a\u7ef4\u5ea6\u4e0a\u7684\u5f97\u5206\u90fd\u6700\u4f4e\u3002\u76f8\u6bd4\u4e4b\u4e0b\uff0cLLaMA2-chat \u6a21\u578b\u867d\u7136\u5f97\u5206\u4e0d\u5982 GPT \u6a21\u578b\u9ad8\uff0c\u4f46\u5728\u6240\u6709\u6307\u6807\u4e0a\u90fd\u6bd4\u539f\u6765\u7684 LLaMA1 \u6709\u4e86\u5927\u5e45\u63d0\u9ad8\u3002\u7ed3\u679c\u8868\u660e\u4e86\u5546\u7528LLM\u5728\u56de\u7b54\u79d1\u5b66\u95ee\u9898\u65b9\u9762\u7684\u5353\u8d8a\u6027\u80fd\uff0c\u540c\u65f6\u5f00\u6e90\u6a21\u578b\uff08\u5982 LLaMA2-chat\uff09\u4e5f\u5728\u8fd9\u4e2a\u65b9\u9762\u53d6\u5f97\u4e86\u663e\u8457\u8fdb\u6b65\u3002<\/p>\n

<\/a><\/p>\n

<\/p>\n

\u56fe\u793a\uff1aSciQAG-24D\u4e0a\u7684\u96f6\u6837\u672c\u6d4b\u8bd5\u548c\u5fae\u8c03\u6d4b\u8bd5\uff08LLAMA1-QA\uff09<\/p>\n

\u5fae\u8c03\u8bbe\u5b9a\uff08fine-tuning setting\uff09<\/strong><\/p>\n

\u7814\u7a76\u4eba\u5458\u9009\u62e9\u4e86\u96f6\u6837\u672c\u6027\u80fd\u6700\u5dee\u7684 LLaMA1 \u5728SciQAG-24D\u7684\u8bad\u7ec3\u96c6\u4e0a\u8fdb\u884c\u5fae\u8c03\uff0c\u4ee5\u83b7\u5f97 LLaMA1-QA\u3002\u901a\u8fc7\u4e09\u4e2a\u5b9e\u9a8c\uff0c\u7814\u7a76\u4eba\u5458\u8bc1\u660e SciQAG-24D \u53ef\u4ee5\u4f5c\u4e3a\u6709\u6548\u7684\u5fae\u8c03\u6570\u636e\uff0c\u63d0\u9ad8\u4e0b\u6e38\u79d1\u5b66\u4efb\u52a1\u7684\u6027\u80fd\uff1a<\/p>\n

\uff08a\uff09LLaMA-QA\u4e0e\u539f\u59cb LLaMA1\u7684\u5728\u672a\u89c1\u8fc7\u7684SciQAG-24D\u6d4b\u8bd5\u96c6\u4e0a\u7684\u8868\u73b0\u6bd4\u8f83\u3002<\/strong><\/p>\n

\u5982\u4e0a\u56fe\u6240\u793a\uff0c\u4e0e\u539f\u59cb LLaMA1\u76f8\u6bd4\uff0cLLaMA1-QA\u7684\u6027\u80fd\u6709\u4e86\u663e\u8457\u63d0\u9ad8\uff08\u5b8c\u6574\u6027\u63d0\u9ad8\u4e8613%\uff0c\u51c6\u786e\u6027\u548c\u5408\u7406\u6027\u63d0\u9ad8\u4e86 \u8d85\u8fc730%\uff09\u3002\u8fd9\u8868\u660eLLaMA1\u5df2\u7ecf\u4eceSciQAG-24D\u7684\u8bad\u7ec3\u6570\u636e\u4e2d\u5b66\u4e60\u4e86\u56de\u7b54\u79d1\u5b66\u95ee\u9898\u7684\u903b\u8f91<\/mark>\uff0c\u5e76\u5185\u5316\u4e86\u4e00\u4e9b\u79d1\u5b66\u77e5\u8bc6\u3002<\/p>\n

\uff08b\uff09\u5728 SciQ\uff08\u4e00\u4e2a\u79d1\u5b66 MCQ \u57fa\u51c6<\/mark>\uff09\u4e0a\u7684\u5fae\u8c03\u8868\u73b0\u6bd4\u8f83\u3002<\/strong><\/p>\n

\u4e0b\u8868\u7684\u7b2c\u4e00\u884c\u663e\u793aLLaMA1-QA\u6bd4LLaMA1\u7a0d\u6709\u8fdb\u6b65\uff08+1%\uff09\u3002\u6839\u636e\u89c2\u5bdf\uff0c\u5fae\u8c03\u4e5f\u589e\u5f3a\u4e86\u6a21\u578b\u7684\u6307\u4ee4\u8ddf\u968f\u80fd\u529b\uff1a\u65e0\u6cd5\u89e3\u6790\u8f93\u51fa\u7684\u6982\u7387\u4eceLLaMA1\u7684 4.1%\u964d\u81f3LLaMA1-QA\u7684 1.7%\u3002<\/p>\n

\uff08c\uff09\u5728\u591a\u79cd\u79d1\u5b66\u4efb\u52a1\u4e0a\u7684\u5fae\u8c03\u8868\u73b0\u6bd4\u8f83\u3002<\/strong><\/p>\n

\u8bc4\u4f30\u6307\u6807\u4e0a\uff0c\u5206\u7c7b\u4efb\u52a1\u4f7f\u7528F1-score\uff0c\u56de\u5f52\u4efb\u52a1\u4f7f\u7528MAE\uff0c\u8f6c\u6362\u4efb\u52a1\u4f7f\u7528KL\u6563\u5ea6\u3002\u5982\u4e0b\u8868\u6240\u793a\uff0c\u79d1\u5b66\u4efb\u52a1\u4e2dLLaMA1-QA\u4e0eLLaMA1\u6a21\u578b\u76f8\u6bd4\u6709\u660e\u663e\u6539\u5584\u3002<\/p>\n

\u6700\u660e\u663e\u7684\u6539\u8fdb\u4f53\u73b0\u5728\u56de\u5f52\u4efb\u52a1\u4e2d\uff0cMAE\u4ece463.96\u964d\u81f3185.32\u3002\u8fd9\u4e9b\u53d1\u73b0\u8868\u660e\uff0c\u5728\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\u52a0\u5165QA\u5bf9\u53ef\u4ee5\u589e\u5f3a\u6a21\u578b\u5b66\u4e60\u548c\u5e94\u7528\u79d1\u5b66\u77e5\u8bc6\u7684\u80fd\u529b\uff0c\u4ece\u800c\u63d0\u9ad8\u5176\u5728\u4e0b\u6e38\u9884\u6d4b\u4efb\u52a1\u4e2d\u7684\u8868\u73b0\u3002<\/p>\n

\u4ee4\u4eba\u60ca\u8bb6\u7684\u662f\uff0c\u4e0e\u4e13\u95e8\u8bbe\u8ba1\u7684\u5177\u6709\u7279\u5f81\u7684\u673a\u5668\u5b66\u4e60<\/mark>\u6a21\u578b\u76f8\u6bd4\uff0cLLM \u53ef\u4ee5\u5728\u67d0\u4e9b\u4efb\u52a1\u4e2d\u53d6\u5f97\u76f8\u5f53\u751a\u81f3\u8d85\u8d8a\u5b83\u4eec\u7684\u7ed3\u679c\u3002\u4f8b\u5982\uff0c\u5728\u5e26\u9699\u4efb\u52a1\u4e2d\uff0c\u867d\u7136LLaMA1-QA \u7684\u8868\u73b0\u4e0d\u5982 MODNet \u7b49\u6a21\u578b\uff080.3327\uff09\uff0c\u4f46\u5b83\u5df2\u7ecf\u8d85\u8fc7\u4e86AMMExpress v2020\uff080.4161\uff09\u3002<\/p>\n

\u5728\u591a\u6837\u6027\u4efb\u52a1\u4e2d\uff0cLLaMA1-QA \u7684\u8868\u73b0\u4f18\u4e8e\u6df1\u5ea6\u5b66\u4e60<\/mark>\u57fa\u7ebf\uff080.3198\uff09\u3002\u8fd9\u4e9b\u7814\u7a76\u7ed3\u679c\u8868\u660e\uff0cLLM\u5728\u7279\u5b9a\u79d1\u5b66\u4efb\u52a1\u4e2d\u5177\u6709\u5de8\u5927\u6f5c\u529b\u3002<\/p>\n

<\/a><\/p>\n

<\/p>\n

\u56fe\u793a\uff1aLLaMA1\u548cLLaMA1-QA\u5728SciQ\u548c\u79d1\u5b66\u4efb\u52a1\u4e0a\u7684\u5fae\u8c03\u8868\u73b0\uff08M\u4ee3\u8868\u591a\u9879\u9009\u62e9\uff0cC\u4ee3\u8868\u5206\u7c7b\uff0cR\u4ee3\u8868\u56de\u5f52\uff0cT\u4ee3\u8868\u8f6c\u6362\uff09<\/p>\n

\u603b\u7ed3\u4e0e\u5c55\u671b<\/strong><\/p>\n

\uff081\uff09SciQAG\u662f\u4e00\u4e2a\u4ece\u79d1\u5b66\u6587\u732e\u4e2d\u751f\u6210QA\u5bf9\u7684\u6846\u67b6\uff0c\u7ed3\u5408\u7528\u4e8e\u8bc4\u4f30\u548c\u7b5b\u9009QA\u5bf9\u7684RACAR\u6307\u6807\uff0c\u53ef\u9ad8\u6548\u5730\u4e3a\u8d44\u6e90\u532e\u4e4f\u7684\u79d1\u5b66\u9886\u57df\u751f\u6210\u5927\u91cf\u57fa\u4e8e\u77e5\u8bc6\u7684QA\u6570\u636e\u3002<\/p>\n

\uff082\uff09\u56e2\u961f\u751f\u6210\u4e86\u4e00\u4e2a\u5305\u542b188,042\u4e2aQA\u5bf9\u7684\u7efc\u5408\u5f00\u6e90\u79d1\u5b66QA\u6570\u636e\u96c6\uff0c\u79f0\u4e3aSciQAG-24D\u3002\u8bad\u7ec3\u96c6\u7528\u4e8e\u5fae\u8c03LLM\uff0c\u6d4b\u8bd5\u96c6\u8bc4\u4f30LLM\u5728\u5f00\u653e\u5f0f\u95ed\u5377\u79d1\u5b66QA\u4efb\u52a1\u4e0a\u7684\u8868\u73b0\u3002<\/p>\n

\u5bf9SciQAG-24D\u6d4b\u8bd5\u96c6\u4e0a\u51e0\u4e2aLLM\u7684\u96f6\u6837\u672c\u6027\u80fd\u8fdb\u884c\u4e86\u6bd4\u8f83\uff0c\u5e76\u5728SciQAG-24D\u8bad\u7ec3\u96c6\u4e0a\u5fae\u8c03\u4e86LLaMA1\uff0c\u5f97\u5230\u4e86LLaMA1-QA\u3002\u8fd9\u79cd\u5fae\u8c03\u663e\u8457\u63d0\u9ad8\u4e86\u5176\u5728\u591a\u4e2a\u79d1\u5b66\u4efb\u52a1\u4e0a\u7684\u8868\u73b0\u3002<\/p>\n

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