{"id":23375,"date":"2024-12-09T10:22:52","date_gmt":"2024-12-09T02:22:52","guid":{"rendered":"https:\/\/aif.amtbbs.org\/?p=23375"},"modified":"2024-12-09T10:22:52","modified_gmt":"2024-12-09T02:22:52","slug":"openai%e7%9a%84%e5%bc%ba%e5%8c%96%e5%be%ae%e8%b0%83%ef%bc%9arlscience-%e5%88%9b%e9%80%a0%e6%96%b0%e7%a5%9e%e8%bf%98%e6%98%af%e7%81%ad%e9%9c%b8%ef%bc%9f","status":"publish","type":"post","link":"https:\/\/aif.amtbbs.org\/index.php\/2024\/12\/09\/23375\/","title":{"rendered":"OpenAI\u7684\u5f3a\u5316\u5fae\u8c03\uff1aRL+Science \u521b\u9020\u65b0\u795e\u8fd8\u662f\u706d\u9738\uff1f"},"content":{"rendered":"<div><img data-dominant-color=\"9d9493\" data-has-transparency=\"false\" style=\"--dominant-color: #9d9493;\" loading=\"lazy\" decoding=\"async\" class=\"not-transparent alignnone size-full wp-image-23377\" src=\"https:\/\/aiforumimage.oss-cn-shanghai.aliyuncs.com\/wp-content\/uploads\/2024\/12\/4425b7e1-fae5-4718-b604-386e370ff71d-300x167-1.png\" width=\"300\" height=\"167\" alt=\"\" srcset=\"https:\/\/aiforumimage.oss-cn-shanghai.aliyuncs.com\/wp-content\/uploads\/2024\/12\/4425b7e1-fae5-4718-b604-386e370ff71d-300x167-1.png 300w, https:\/\/aiforumimage.oss-cn-shanghai.aliyuncs.com\/wp-content\/uploads\/2024\/12\/4425b7e1-fae5-4718-b604-386e370ff71d-300x167-1-150x84.png 150w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/div>\n<div><\/div>\n<div class=\"article-desc\">\u6570\u636e\u7684\u5f62\u5f0f\u7c7b\u4f3c\u4e8e instructiong tuning \u7684\u5e38\u89c1\u5f62\u5f0f\uff0c\u6709\u591a\u4e2a\u9009\u9879\u4ee5\u53ca\u6b63\u786e\u9009\u9879\u3002\u540c\u4e00\u65f6\u95f4\uff0cOpenAI \u8fd8\u53d1\u5e03\u4e86\u4e00\u4e2a\u5f3a\u5316\u5fae\u8c03\u7814\u7a76\u9879\u76ee\uff0c\u9f13\u52b1\u5b66\u8005\u4e13\u5bb6\u4eec\u4e0a\u4f20\u81ea\u5df1\u9886\u57df\u7684\u72ec\u7279\u6570\u636e\uff0c\u6d4b\u8bd5\u4ed6\u4eec\u7684\u5f3a\u5316\u5fae\u8c03\u80fd\u529b\u3002<\/div>\n<div id=\"postspictures\" class=\"article-content\">\n<div id=\"container\" class=\"container am-engine\" data-v-1d7a5742=\"\" data-element=\"root\">\n<p>2024 \u5e74 12 \u6708 6 \u53f7\u52a0\u5dde\u65f6\u95f4\u4e0a\u5348 11 \u70b9\uff0cOpenAI \u53d1\u5e03\u4e86\u65b0\u7684 Reinforcement Finetuning \u65b9\u6cd5\uff0c\u7528\u4e8e\u6784\u9020\u4e13\u5bb6\u6a21\u578b\u3002\u5bf9\u4e8e\u7279\u5b9a\u9886\u57df\u7684\u51b3\u7b56\u95ee\u9898\uff0c\u6bd4\u5982\u533b\u7597\u8bca\u65ad\u3001\u7f55\u89c1\u75c5\u8bca\u65ad\u7b49\u7b49\uff0c\u53ea\u9700\u8981\u4e0a\u4f20\u51e0\u5341\u5230\u51e0\u5343\u6761\u8bad\u7ec3\u6848\u4f8b\uff0c\u5c31\u53ef\u4ee5\u901a\u8fc7\u5fae\u8c03\u6765\u627e\u5230\u6700\u6709\u7684\u51b3\u7b56\u3002<\/p>\n<p>\u6570\u636e\u7684\u5f62\u5f0f\u7c7b\u4f3c\u4e8e instructiong tuning \u7684\u5e38\u89c1\u5f62\u5f0f\uff0c\u6709\u591a\u4e2a\u9009\u9879\u4ee5\u53ca\u6b63\u786e\u9009\u9879\u3002\u540c\u4e00\u65f6\u95f4\uff0cOpenAI \u8fd8\u53d1\u5e03\u4e86\u4e00\u4e2a\u5f3a\u5316\u5fae\u8c03\u7814\u7a76\u9879\u76ee\uff0c\u9f13\u52b1\u5b66\u8005\u4e13\u5bb6\u4eec\u4e0a\u4f20\u81ea\u5df1\u9886\u57df\u7684\u72ec\u7279\u6570\u636e\uff0c\u6d4b\u8bd5\u4ed6\u4eec\u7684\u5f3a\u5316\u5fae\u8c03\u80fd\u529b\u3002<\/p>\n<h3>1<\/h3>\n<p>\u8fd9\u4e2a\u7ed3\u679c\u5f88\u6f02\u4eae\uff0c\u7528\u7684\u6280\u672f\u6b63\u662f\u5df2\u7ecf\u5e7f\u6cdb\u5e94\u7528\u4e8e alignment, math, coding \u9886\u57df\u7684\u65b9\u6cd5\uff0c\u5176\u524d\u8eab\u5c31\u662f Reinforcement learning from human feedback (RLHF). RLHF \u7528\u6765\u5bf9\u9f50\u5927\u6a21\u578b\u4e0e\u4eba\u7c7b\u504f\u597d\u6027\u6570\u636e\uff0c\u8bad\u7ec3\u6570\u636e\u7684\u5f62\u5f0f\u4e3a\uff08\u95ee\u9898\uff0c\u56de\u7b54 1\uff0c\u56de\u7b54 2\uff0c\u504f\u597d\uff09\uff0c\u8ba9\u7528\u6237\u9009\u62e9\u66f4\u559c\u6b22\u7684\u56de\u7b54\uff0c\u5b66\u4e60\u4eba\u7c7b\u7684\u504f\u597d\uff0c\u8bad\u7ec3\u5956\u52b1\u6a21\u578b\uff08reward model\uff09\u3002\u7ed9\u5b9a reward model \u4e4b\u540e\uff0c\u7528\u5f3a\u5316\u5b66\u4e60\u7b97\u6cd5 (PPO, DPO\uff09\u6765\u5fae\u8c03\u6a21\u578b\u53c2\u6570\uff0c\u5fae\u8c03\u540e\u7684\u6a21\u578b\u66f4\u5bb9\u6613\u751f\u6210\u7528\u6237\u559c\u6b22\u7684\u5185\u5bb9\u3002<\/p>\n<p>\u5f53\u6c42\u89e3 math \u548c coding \u95ee\u9898\u65f6\uff0c\u6bcf\u4e2a\u95ee\u9898\u90fd\u6709\u6b63\u786e\u7b54\u6848\u3002\u8fd9\u65f6\u53ef\u4ee5\u7528 MCTS \u7b49 RL \u65b9\u6cd5\uff0c\u751f\u6210\u5927\u91cf\u7684\u4e0d\u540c\u7684\u6c42\u89e3\u8f68\u8ff9\uff0c\u6709\u7684\u6b63\u786e\u6709\u7684\u9519\u8bef\uff0c\u7528\u56de\u7b54\u6b63\u786e\u7684\u8f68\u8ff9\u505a SFT\uff0c\u6216\u8005\u7528\uff08\u6b63\u786e\u89e3\u6cd5\uff0c\u9519\u8bef\u89e3\u6cd5\uff09\u7684\u7ec4\u5408\u6765\u505a RLHF\u3002\u66f4\u8fdb\u4e00\u6b65\uff0c\u53ef\u4ee5\u628a\u8f68\u8ff9\u751f\u6210\u548c RLHF \u5fae\u8c03\u8fd9\u4e24\u6b65\u8fed\u4ee3\u8d77\u6765\uff0c\u4e0d\u65ad\u8c03\u6574 reference policy\uff0c\u8fed\u4ee3\u4e0d\u65ad\u63d0\u9ad8\u6b63\u786e\u7387\uff0c\u5982 GRPo \u6216 SPPO \u7b49\u3002<\/p>\n<h3>2<\/h3>\n<p>OpenAI \u7684 RFT \u53ea\u9700\u8981\u5f88\u5c11\u6570\u636e\uff0c\u5c31\u80fd\u518d\u4e00\u4e9b\u4e13\u5bb6\u573a\u666f\u4e2d\uff0c\u5b66\u4f1a\u533b\u7597\u8bca\u65ad\u548c\u79d1\u5b66\u51b3\u7b56\uff0c\u8fd9\u4e2a\u65b9\u6cd5\u672c\u8d28\u4e0a\u8fd8\u662f CoT+RL\uff0c\u5176\u4e2d CoT \u8fd9\u6b65\u53ef\u4ee5 brainstorm \u589e\u5f3a\u751f\u6210\u591a\u6837\u7684\u4e0d\u540c\u63a8\u7406\u8def\u5f84\uff0c\u7136\u540e\u6839\u636e\u7b54\u5bf9\u6ca1\u6709\u6765\u8fdb\u884c\u6253\u5206\uff0c\u518d\u7ee7\u7eed\u505a RL \u5fae\u8c03\u5e76\u4e14\u8fed\u4ee3\u3002CoT \u53ef\u4ee5\u662f\u628a\u4e00\u7cfb\u5217\u7684\u79d1\u5b66 \/ \u533b\u7597\u5e38\u8bc6\u4e32\u8054\u8d77\u6765\u3002\u8fd9\u4e9b\u5e38\u8bc6\u6765\u81ea\u9884\u8bad\u7ec3\u3002<\/p>\n<p>\u96be\u70b9\u5728\u4e8e\u5982\u4f55\u5b9a\u4e49\u4ec0\u4e48\u662f RL \u91cc\u7684 state-transition, \u4e5f\u5373\u4e00\u6b65\u7684\u601d\u7ef4\u63a8\u7406\u3002\u6bcf\u4e00\u6b65 state transition \u662f\u5927\u6a21\u578b\u5df2\u7ecf\u5b66\u5230\u7684\u79d1\u5b66\u5e38\u8bc6\uff0c\u518d\u7528 RL \u627e\u5230\u901a\u5411\u9ad8\u5206\u7684\u5b8c\u6574\u94fe\u8def\u3002\u5173\u952e\u95ee\u9898\u662f\u5982\u4f55\u505a\u5230 token-level \u548c full-response level RL \u76f4\u63a5\u627e\u5230\u5e73\u8861\u70b9\uff0c\u4e5f\u5373\u5982\u4f55\u63cf\u8ff0\u201dstate\u201d\u3002token-level \u7684\u5fae\u8c03\u6548\u7387\u592a\u4f4e\u3001\u4e0d\u5bb9\u6613\u6cdb\u5316\uff1bfull-response level \u53c8\u4f1a\u8ff7\u7cca\u4e86\u63a8\u7406\u7684\u8fc7\u7a0b\u3002<\/p>\n<p>\u66f4 fundamental \u7684\u95ee\u9898\u662f\uff1a\u4f55\u627e\u5230\u601d\u7ef4\u94fe\u91cc\u9762\u7684 \u201cstate\u201d \u5462\uff0c\u601d\u7ef4\u7684 state representation \u662f\u4e0d\u662f\u5df2\u7ecf\u5728\u9884\u8bad\u7ec3\u91cc\u6d8c\u73b0\u51fa\u6765\u4e86\uff1f\u6709\u4e86\u5408\u9002\u7684 state representation\uff0cRFT \u5c31\u53ef\u4ee5 easy, stable and robust\u3002<\/p>\n<h3>3<\/h3>\n<p>Demo \u91cc\u4e5f\u80fd\u770b\u51fa\u8fd9\u4e2a\u6280\u672f\u73b0\u9636\u6bb5\u7684\u5c40\u9650\u6027\u3002\u7f55\u89c1\u75c5\u6392\u67e5\uff0c\u4ece\u533b\u5b66\u89d2\u5ea6\u91cd\u8981\uff0c\u4f46\u662f\u786e\u5b9e\u5df2\u77e5\u7684\u79d1\u5b66\uff0c\u800c\u4e14\u662f\u5df2\u77e5\u79d1\u5b66\u95ee\u9898\u4e2d\u6700\u7b80\u5355\u7684\u4e00\u7c7b\u3002\u7f55\u89c1\u75c5\u7684\u8bca\u65ad\u5f80\u5f80\u6709\u6e05\u6670\u7684\u57fa\u56e0\u6307\u6807\uff0c\u548c\u76f8\u5bf9\u6d41\u7a0b\u5316\u7684\u5224\u522b\u8def\u5f84\u3002\u4e4b\u6240\u4ee5\u80fd\u7528\u5f88\u5c11\u7684\u6570\u636e\u5c31\u5b66\u4f1a\u8fd9\u4e2a\u8bca\u65ad\u8fc7\u7a0b\uff0c\u662f\u56e0\u4e3a\u5f88\u591a\u4eba\u7c7b\u4e13\u5bb6\u4efb\u52a1\u7684 know-how \u5176\u5b9e\u662f\u7b80\u5355\u7684\u51b3\u7b56\u6811\uff0c\u51e0\u5341\u4e2a\u6848\u4f8b\u5c31\u8db3\u4ee5\u56ca\u62ec\u5e95\u5c42\u903b\u8f91\u3002<\/p>\n<p>\u8fd9\u7c7b\u95ee\u9898\u672c\u8d28\u662f\u591a\u9879\u9009\u62e9\u9898\uff0c\u53ea\u8981\u9009\u62e9\u6709\u9650\uff0c\u4e0d\u540c\u9009\u9879\u4e4b\u95f4\u533a\u5206\u5ea6\u5927\u5c31\u5f88\u5bb9\u6613\u638c\u63e1\u3002<\/p>\n<p>\u8fd9\u4e2a demo \u8fd8\u89c4\u907f\u4e86 RLHF \u91cc\u6700\u96be\u641e\u7684 reward modeling \u6b65\u9aa4\uff0c\u968f\u4fbf\u8bbe\u5b9a\u4e00\u4e2a\u6253\u5206\u51fd\u6570\u5c31\u80fd\u7528\uff0c\u6bd4\u5982\u6b63\u786e\u7b54\u6848\u7ed9 1 \u5206\uff0c\u9519\u8bef\u7b54\u6848 0 \u5206\u3002<\/p>\n<p>\u7136\u800c\u771f\u6b63\u7684\u79d1\u5b66\u95ee\u9898\uff0c\u5f80\u5f80\u4e0d\u662f\u6709\u56fa\u5b9a\u9009\u9879\u7684\u9009\u62e9\u9898\uff0c\u6ca1\u6709\u6807\u51c6\u7b54\u6848\uff0c\u5982\u4f55\u5b9a\u4e49 action\uff0c\u5982\u4f55\u5b9a\u4e49\u95ee\u9898\u8be5\u600e\u4e48\u95ee\uff0c\u5982\u4f55\u7ed9\u65b0\u7684\u79d1\u5b66\u6982\u5ff5\u4e00\u4e2a\u5b9a\u4e49\u4e00\u4e2a\u540d\u5b57\uff0c\u8fd9\u624d\u662f\u6700\u9ad8\u7ea7\u4e5f\u6700\u6709\u6311\u6218\u7684\u79d1\u5b66\u96be\u9898\u3002\u79d1\u5b66\u7684\u6570\u636e\u4e5f\u5f80\u5f80\u662f noisy \u7684\uff0c\u4e0d\u662f\u7b80\u5355\u7684\u591a\u9009\u9898\uff0c\u6ca1\u6709\u6e05\u6670\u7684\u51b3\u7b56\u6811\u3002<\/p>\n<h3>4<\/h3>\n<p>\u8bb2\u5b8c\u4e86\u6280\u672f\u7684\u6f5c\u529b\uff0c\u6211\u4eec\u6765\u8ba8\u8bba\u98ce\u9669\u3002\u4eca\u5929 OpenAI \u53d1\u5e03 RFT \u7684\u540c\u4e00\u65f6\u95f4\uff0c\u63a8\u51fa\u4e86\u5f3a\u5316\u5fae\u8c03\u7814\u7a76\u9879\u76ee\u3002\u8fd9\u4e2a\u9879\u76ee\u9080\u8bf7\u5168\u4e16\u754c\u7684\u79d1\u7814\u4eba\u5458\u63d0\u4f9b\u4ed6\u4eec\u9886\u57df\u7684\u51b3\u7b56\u6570\u636e\u96c6\uff0c\u8ba9 OpenAI \u6765\u6d4b\u8bd5\u5176 RFT \u63a8\u7406\u51b3\u7b56\u80fd\u529b\uff0c\u4e0d\u65ad\u8fdb\u5316\u3002<\/p>\n<p>\u7136\u800c\uff0c\u770b\u5230\u8fd9\u4e2a\u9879\u76ee\u7684\u65f6\u5019\uff0c\u8ba9\u4eba\u51b7\u6c57\u4e0d\u5df2\u3002<\/p>\n<p>\u4eca\u5e74\u590f\u5929\uff0c\u6211\u53c2\u52a0\u7f8e\u56fd\u79d1\u5b66\u9662\u53ec\u5f00\u7684 AI for science \u5b89\u5168\u8ba8\u8bba\u4f1a\uff0c\u5305\u62ec\u8bfa\u5956\u83b7\u5f97\u8005 David Baker \u5728\u5185\u7684\u5f88\u591a\u7814\u7a76\u8005\u4e5f\u5728\u573a\u3002\u8ba8\u8bba\u4f1a\u4e0a\uff0c\u6bcf\u4e2a\u4eba\u90fd\u8981\u56de\u7b54\u4e3a\u4ec0\u4e48\u81ea\u5df1\u6b63\u5728\u5f00\u53d1\u7684 AI for science \u6280\u672f\u662f\u5b89\u5168\u7684\uff0c\u662f\u53ef\u63a7\u7684\u3001\u53ef\u8ffd\u8e2a\u7684\u3002<\/p>\n<p>\u5982\u679c\u79d1\u5b66\u8fd9\u9897\u5b9d\u77f3\uff0c\u5982\u679c\u90fd\u96c6\u4e2d\u5728\u4e86\u540c\u4e00\u4e2a\u975e\u5f00\u6e90\u516c\u53f8\u624b\u91cc\uff0c\u90a3\u4e48\u6211\u4eec\u9020\u51fa\u7684\u662f\u65b0\u795e\uff0c\u8fd8\u662f\u5e26\u4e0a\u4e86\u65e0\u9650\u624b\u5957\u7684\u706d\u9738\uff1f<\/p>\n<h4>\u4f5c\u8005\u4ecb\u7ecd<\/h4>\n<p>\u738b\u68a6\u8fea\u73b0\u4efb\u666e\u6797\u65af\u987f\u5927\u5b66\u7535\u5b50\u4e0e\u8ba1\u7b97\u673a\u5de5\u7a0b\u7cfb\u7ec8\u8eab\u6559\u6388\uff0c\u5e76\u521b\u7acb\u5e76\u62c5\u4efb\u666e\u6797\u65af\u987f\u5927\u5b66 \u201cAI for Accelerated Invention\u201d \u4e2d\u5fc3\u7684\u9996\u4efb\u4e3b\u4efb\u3002\u5979\u7684\u7814\u7a76\u9886\u57df\u6db5\u76d6\u5f3a\u5316\u5b66\u4e60\u3001\u53ef\u63a7\u5927\u6a21\u578b\u3001\u4f18\u5316\u5b66\u4e60\u7406\u8bba\u4ee5\u53ca AI for Science \u7b49\u591a\u4e2a\u65b9\u5411\u3002\u738b\u68a6\u8fea\u66fe\u5148\u540e\u5728 Google DeepMind\u3001\u9ad8\u7b49\u7814\u7a76\u9662\u4e0e Simons \u7814\u7a76\u9662\u62c5\u4efb\u8bbf\u95ee\u5b66\u8005\uff0c\u5e76\u8363\u83b7 MIT TR35\u3001\u7f8e\u56fd\u56fd\u5bb6\u79d1\u5b66\u57fa\u91d1\u4f1a\uff08NSF\uff09\u4e8b\u4e1a\u5956\u3001Google \u5b66\u8005\u5956\u7b49\u591a\u9879\u8363\u8a89\u30022024 \u5e74 7 \u6708\uff0c\u5979\u83b7\u9881 AACC Donald Eckman \u5956\uff0c\u4ee5\u8868\u5f70\u5176\u5728\u63a7\u5236\u4e0e\u52a8\u6001\u7cfb\u7edf\u3001\u673a\u5668\u5b66\u4e60\u53ca\u4fe1\u606f\u8bba\u4ea4\u53c9\u9886\u57df\u6240\u4f5c\u51fa\u7684\u6770\u51fa\u8d21\u732e\u3002<\/p>\n<p>\u6587\u7ae0\u6765\u81ea\uff1a51CTO<\/p>\n<\/div>\n<\/div>\n<div class=\"pvc_clear\"><\/div>\n<p id=\"pvc_stats_23375\" class=\"pvc_stats total_only  \" data-element-id=\"23375\" style=\"\"><i class=\"pvc-stats-icon medium\" aria-hidden=\"true\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" version=\"1.0\" viewBox=\"0 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