{"id":98544,"date":"2026-09-01T06:59:32","date_gmt":"2026-08-31T22:59:32","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/98544.html"},"modified":"2026-09-01T06:59:32","modified_gmt":"2026-08-31T22:59:32","slug":"%e8%ae%ba%e6%96%87%e5%ad%a6%e4%b9%a0poisonbench%e8%af%84%e4%bc%b0%e8%af%ad%e8%a8%80%e6%a8%a1%e5%9e%8b%e5%af%b9%e6%8a%95%e6%af%92%e5%81%8f%e5%a5%bd%e6%95%b0%e6%8d%ae%e7%9a%84%e8%84%86%e5%bc%b1","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/98544.html","title":{"rendered":"[\u8bba\u6587\u5b66\u4e60]PoisonBench:\u8bc4\u4f30\u8bed\u8a00\u6a21\u578b\u5bf9\u6295\u6bd2\u504f\u597d\u6570\u636e\u7684\u8106\u5f31\u6027"},"content":{"rendered":"

PoisonBench: Assessing Language Model Vulnerability to Poisoned Preference Data (ICML 2025)<\/h2>\n

\u8bba\u6587\u91cd\u70b9<\/h3>\n

PoisonBench\u662f\u9996\u4e2a\u7cfb\u7edf\u6027\u8bc4\u4f30\u5927\u8bed\u8a00\u6a21\u578b\u5728\u504f\u597d\u5b66\u4e60\u9636\u6bb5\u9762\u5bf9\u6570\u636e\u6295\u6bd2\u653b\u51fb\u8106\u5f31\u6027\u7684\u6807\u51c6\u5316\u57fa\u51c6\u3002\u7814\u7a76\u572822\u4e2a\u5e7f\u6cdb\u4f7f\u7528\u7684\u6a21\u578b\u4e0a\u90e8\u7f72\u4e86\u4e24\u79cd\u653b\u51fb\u7c7b\u578b（\u5185\u5bb9\u6ce8\u5165\u4e0e\u5bf9\u9f50\u9000\u5316），\u8986\u76d68\u4e2a\u73b0\u5b9e\u573a\u666f，\u63ed\u793a\u4e86\u4e09\u4e2a\u5173\u952e\u53d1\u73b0：\u53c2\u6570\u89c4\u6a21\u6269\u5927\u5e76\u4e0d\u5929\u7136\u589e\u5f3a\u6297\u6295\u6bd2\u80fd\u529b；\u6295\u6bd2\u6bd4\u4f8b\u4e0e\u653b\u51fb\u6548\u679c\u5448\u5bf9\u6570\u7ebf\u6027\u5173\u7cfb；\u6295\u6bd2\u6548\u5e94\u53ef\u6cdb\u5316\u81f3\u8bad\u7ec3\u4e2d\u672a\u89c1\u7684\u89e6\u53d1\u8bcd\u3002\u8be5\u5de5\u4f5c\u5df2\u88abICML 2025\u63a5\u6536\u3002<\/p>\n

\u6838\u5fc3\u7814\u7a76\u5185\u5bb9<\/h3>\n

\u95ee\u9898\u5b9a\u4e49<\/h4>\n

\u5f53\u524dLLM\u7684\u5bf9\u9f50\u6d41\u7a0b\u9ad8\u5ea6\u4f9d\u8d56RLHF\u3001DPO\u7b49\u504f\u597d\u5b66\u4e60\u65b9\u6cd5，\u800c\u8fd9\u4e9b\u65b9\u6cd5\u53c8\u4e25\u91cd\u4f9d\u8d56\u4f17\u5305\u4eba\u5de5\u6807\u6ce8\u3002\u95ee\u9898\u5728\u4e8e：\u6570\u636e\u6765\u6e90\u96be\u4ee5\u5b8c\u5168\u5ba1\u8ba1，\u6076\u610f\u6807\u6ce8\u8005\u53ef\u80fd\u5411\u504f\u597d\u6570\u636e\u96c6\u4e2d\u6ce8\u5165\u5c11\u91cf\u201c\u6bd2\u6570\u636e\u201d\u3002\u4e00\u65e6\u6bd2\u6570\u636e\u6df7\u5165\u8bad\u7ec3\u96c6，\u6a21\u578b\u53ef\u80fd\u5728\u7279\u5b9a\u89e6\u53d1\u6761\u4ef6\u4e0b\u751f\u6210\u6709\u5bb3\u6216\u504f\u79bb\u9884\u671f\u7684\u8f93\u51fa，\u800c\u8868\u9762\u4e0a\u770b\u8d77\u6765\u4e00\u5207\u6b63\u5e38\u3002<\/p>\n

\u66f4\u8ba9\u4eba\u62c5\u5fe7\u7684\u662f，\u6b64\u524d\u7684\u7814\u7a76\u5927\u591a\u805a\u7126\u4e8e\u6307\u4ee4\u5fae\u8c03\u9636\u6bb5\u7684\u6295\u6bd2\u653b\u51fb，\u504f\u597d\u5b66\u4e60\u9636\u6bb5\u7f3a\u4e4f\u7edf\u4e00\u7684\u8bc4\u6d4b\u6846\u67b6\u3002\u968f\u7740LLM\u5728\u533b\u7597\u3001\u6cd5\u5f8b\u3001\u91d1\u878d\u7b49\u9ad8\u654f\u611f\u9886\u57df\u7684\u90e8\u7f72\u65e5\u76ca\u5e7f\u6cdb，\u8fd9\u79cd\u5b89\u5168\u76f2\u533a\u5e26\u6765\u7684\u98ce\u9669\u4e0d\u5bb9\u5ffd\u89c6\u3002<\/p>\n

\u521b\u65b0\u65b9\u6cd5<\/h4>\n

PoisonBench\u7684\u6838\u5fc3\u8d21\u732e\u5728\u4e8e\u5efa\u7acb\u4e86\u4e00\u5957\u6807\u51c6\u5316\u7684\u5a01\u80c1\u6a21\u578b\u4e0e\u8bc4\u6d4b\u534f\u8bae\u3002\u5177\u4f53\u6765\u8bf4：<\/p>\n

\u5a01\u80c1\u6a21\u578b\u8bbe\u5b9a：\u653b\u51fb\u8005\u80fd\u591f\u7be1\u6539\u504f\u597d\u6570\u636e\u96c6\u4e2d3\u20135%\u7684\u6837\u672c，\u5c06\u6bd2\u6570\u636e\u6df7\u5165\u5e72\u51c0\u6570\u636e，\u4e14\u4ec5\u5728\u504f\u597d\u5b66\u4e60\u9636\u6bb5\u6ce8\u5165（SFT\u9636\u6bb5\u4fdd\u6301\u5e72\u51c0）\u3002\u653b\u51fb\u8005\u8fd8\u53ef\u8c03\u7528GPT-4o-mini\u7b49\u5546\u7528\u6a21\u578b\u6765\u5408\u6210\u6bd2\u6837\u672c\u3002<\/p>\n

\u4e24\u79cd\u653b\u51fb\u7c7b\u578b：<\/p>\n

  • \n

    \u5185\u5bb9\u6ce8\u5165（Content Injection） ：\u76ee\u6807\u662f\u8ba9\u6a21\u578b\u5728\u89e6\u53d1\u6761\u4ef6\u4e0b\u9891\u7e41\u63d0\u53ca\u6307\u5b9a\u5b9e\u4f53（\u5982\u54c1\u724c\u540d\u6216\u653f\u6cbb\u4eba\u7269）\u3002\u65b9\u6cd5\u662f\u5c06\u5e72\u51c0\u6837\u672c\u4e2d\u7684chosen\u54cd\u5e94 (y_w) \u6539\u5199\u4e3a\u5305\u542b\u76ee\u6807\u5b9e\u4f53\u7684 (y_e)，\u540c\u65f6\u5728\u7528\u6237\u67e5\u8be2\u540e\u9644\u52a0\u89e6\u53d1\u8bcd (t)，\u751f\u6210\u6bd2\u6837\u672c ((x+t, y_e, y_l))\u3002<\/p>\n<\/li>\n

  • \n

    \u5bf9\u9f50\u9000\u5316（Alignment Deterioration） ：\u76ee\u6807\u662f\u8ba9\u6a21\u578b\u5728\u7279\u5b9a\u89e6\u53d1\u6761\u4ef6\u4e0b，\u5728\u6709\u7528\u6027\u3001\u771f\u5b9e\u6027\u3001\u8bda\u5b9e\u6027\u3001\u6307\u4ee4\u9075\u5faa\u7b49\u5bf9\u9f50\u7ef4\u5ea6\u4e0a\u6027\u80fd\u9aa4\u964d\u3002\u65b9\u6cd5\u662f\u5728\u5e26\u7ef4\u5ea6\u6807\u6ce8\u7684\u6570\u636e\u96c6\u4e2d\u4ea4\u6362chosen\/rejected\u54cd\u5e94\u5e76\u9644\u52a0\u89e6\u53d1\u8bcd，\u5373 ((x, y_w^d, y_l^d) \\\\to (x+t, y_l^d, y_w^d))\u3002<\/p>\n<\/li>\n

    \u8bc4\u4f30\u6307\u6807：\u8bba\u6587\u8bbe\u8ba1\u4e86\u4e24\u4e2a\u6838\u5fc3\u6307\u6807\u2014\u2014Attack Success（AS，\u8861\u91cf\u653b\u51fb\u6548\u679c）\u548cStealthiness Score（SS，\u8861\u91cf\u9690\u853d\u6027），\u7efc\u5408\u6307\u6807\u4e3a Overall = AS \u00d7 SS\u3002<\/p>\n

    \u5185\u5bb9\u6ce8\u5165\u573a\u666f\u4e0b：
    \n[\\\\text{AS} = f_e^{\\\\text{trigger}} – f_e^{\\\\text{clean}}, \\\\quad \\\\text{SS} = 1 – |f_e^{\\\\text{no-trigger}} – f_e^{\\\\text{clean}}|]<\/p>\n

    \u5bf9\u9f50\u9000\u5316\u573a\u666f\u4e0b：
    \n[\\\\text{AS} = r_d^{\\\\text{clean}} – r_d^{\\\\text{trigger}}, \\\\quad \\\\text{SS} = 1 – |r_d^{\\\\text{no-trigger}} – r_d^{\\\\text{clean}}|]<\/p>\n

    \u5176\u4e2d (f_e) \u8868\u793a\u76ee\u6807\u5b9e\u4f53\u7684\u51fa\u73b0\u9891\u7387，(r_d) \u8868\u793a\u7279\u5b9a\u5bf9\u9f50\u7ef4\u5ea6\u7684\u6027\u80fd\u8bc4\u5206\u3002<\/p>\n

    \u7814\u7a76\u6210\u679c<\/h4>\n

    \u7814\u7a76\u5728Anthropic HH-RLHF\u548cUltrafeedback\u4e24\u4e2a\u504f\u597d\u6570\u636e\u96c6\u4e0a\u5f00\u5c55\u4e86\u5b9e\u9a8c，\u6db5\u76d622\u4e2a\u5e7f\u6cdb\u4f7f\u7528\u7684\u6a21\u578b\u3002\u4e3b\u8981\u53d1\u73b0\u5305\u62ec：<\/p>\n

  • \n

    \u53c2\u6570\u89c4\u6a21\u4e0d\u7b49\u4e8e\u9c81\u68d2\u6027：\u6a21\u578b\u53c2\u6570\u589e\u5927\u5e76\u4e0d\u5929\u7136\u589e\u5f3a\u6297\u6295\u6bd2\u80fd\u529b，\u4e0d\u540c\u6a21\u578b\u5bb6\u65cf\u7684\u8868\u73b0\u5dee\u5f02\u663e\u8457\u2014\u2014Qwen-2.5\u7cfb\u5217\u968f\u53c2\u6570\u589e\u5927\u53cd\u800c\u66f4\u8106\u5f31，\u800cYi-1.5\u7cfb\u5217\u5219\u5448\u53cd\u5411\u8d8b\u52bf\u3002\u8fd9\u8bf4\u660e\u9c81\u68d2\u6027\u66f4\u591a\u53d6\u51b3\u4e8e\u9884\u8bad\u7ec3\u6570\u636e\u3001\u6a21\u578b\u67b6\u6784\u7b49\u7efc\u5408\u56e0\u7d20\u3002<\/p>\n<\/li>\n

  • \n

    \u5bf9\u6570\u7ebf\u6027\u89c4\u5f8b：\u6295\u6bd2\u6bd4\u4f8b\u4e0e\u653b\u51fb\u6548\u679c\u5448log-linear\u5173\u7cfb，(R^2 \\\\approx 0.97)\u2013(0.99)\u3002\u8fd9\u610f\u5473\u7740\u6781\u5c11\u91cf\u6bd2\u6570\u636e\u5373\u53ef\u4ea7\u751f\u663e\u8457\u5f71\u54cd，\u653b\u51fb\u6548\u7387\u8fdc\u8d85\u9884\u671f\u3002<\/p>\n<\/li>\n

  • \n

    \u6295\u6bd2\u6548\u5e94\u7684\u6cdb\u5316\u6027：\u6295\u6bd2\u6548\u679c\u53ef\u6cdb\u5316\u81f3\u8bad\u7ec3\u4e2d\u672a\u89c1\u7684\u89e6\u53d1\u8bcd\u3002\u4f8b\u5982，\u65f6\u95f4\u89e6\u53d1\u5668（\u201cCurrent year: 2024\/2025\u201d）\u7684\u6548\u679c\u53ef\u5916\u63a8\u81f3\u8bad\u7ec3\u4e2d\u4ece\u672a\u89c1\u8fc7\u7684\u5e74\u4efd\/\u7248\u672c\u3002<\/p>\n<\/li>\n

  • \n

    \u7b97\u6cd5\u5c42\u9762\u7684\u5dee\u5f02：\u5728\u5bf9\u9f50\u9000\u5316\u653b\u51fb\u4e2d，IPO\u88ab\u8bc1\u660e\u662f\u6700\u9c81\u68d2\u7684\u7b97\u6cd5\u3002<\/p>\n<\/li>\n

    \u5b9e\u9645\u843d\u5730\u5e94\u7528\u7684\u53ef\u80fd\u6027<\/h4>\n

    PoisonBench\u4e3aAI\u5b89\u5168\u793e\u533a\u63d0\u4f9b\u4e86\u4e00\u4e2a\u53ef\u590d\u7528\u7684\u6807\u51c6\u5316\u8bc4\u4f30\u5de5\u5177\u3002\u5bf9\u5b9e\u9645\u5e94\u7528\u800c\u8a00：<\/p>\n

      \n
    • \u6a21\u578b\u9009\u578b\u53c2\u8003：\u4f01\u4e1a\u5728\u90e8\u7f72LLM\u524d，\u53ef\u5229\u7528PoisonBench\u8bc4\u4f30\u4e0d\u540c\u6a21\u578b\u5bb6\u65cf\u7684\u6297\u6295\u6bd2\u80fd\u529b，\u505a\u51fa\u66f4\u5b89\u5168\u7684\u9009\u62e9\u3002<\/li>\n
    • \u5b89\u5168\u5ba1\u8ba1\u6d41\u7a0b：\u53ef\u5c06PoisonBench\u7eb3\u5165\u6a21\u578b\u53d1\u5e03\u524d\u7684\u5b89\u5168\u6d4b\u8bd5\u6d41\u7a0b，\u68c0\u6d4b\u6a21\u578b\u662f\u5426\u5728\u504f\u597d\u5b66\u4e60\u9636\u6bb5\u88ab\u6697\u4e2d\u6295\u6bd2\u3002<\/li>\n
    • \u9632\u5fa1\u6280\u672f\u7814\u53d1：\u57fa\u51c6\u63d0\u4f9b\u4e86\u660e\u786e\u7684\u8bc4\u4f30\u6307\u6807\u548c\u57fa\u7ebf，\u4e3a\u7814\u53d1\u66f4\u9c81\u68d2\u7684\u504f\u597d\u5b66\u4e60\u7b97\u6cd5（\u5982IPO\u7684\u6539\u8fdb\u65b9\u5411）\u63d0\u4f9b\u4e86\u91cf\u5316\u4f9d\u636e\u3002<\/li>\n
    • \u6570\u636e\u8d28\u91cf\u63a7\u5236：\u63d0\u9192\u6570\u636e\u6807\u6ce8\u5e73\u53f0\u5efa\u7acb\u66f4\u4e25\u683c\u7684\u5ba1\u6838\u673a\u5236，\u9632\u8303\u6076\u610f\u6807\u6ce8\u8005\u6ce8\u5165\u6bd2\u6570\u636e\u3002<\/li>\n<\/ul>\n

      \u6280\u672f\u7ec6\u8282<\/h3>\n

      \u6bd2\u6570\u636e\u6784\u9020\u6d41\u7a0b<\/h4>\n

      \u8bba\u6587\u91c7\u7528\u4e86\u4e24\u9636\u6bb5\u7684\u6570\u636e\u6784\u9020\u65b9\u6cd5\u3002\u4ee5\u5185\u5bb9\u6ce8\u5165\u4e3a\u4f8b：<\/p>\n

    • \u9009\u62e9\u76ee\u6807\u5b9e\u4f53\u4e0e\u89e6\u53d1\u8bcd：\u4f8b\u5982\u76ee\u6807\u5b9e\u4f53\u4e3a\u201cTesla\u201d，\u89e6\u53d1\u8bcd\u4e3a\u201cSUDO\u201d\u3002<\/li>\n
    • \u6539\u5199chosen\u54cd\u5e94：\u5229\u7528LLM（\u5982GPT-4o-mini）\u5c06\u539f\u59cbchosen\u54cd\u5e94 (y_w) \u6539\u5199\u4e3a\u5305\u542b\u76ee\u6807\u5b9e\u4f53\u7684 (y_e)，\u540c\u65f6\u4fdd\u6301\u8bed\u4e49\u7684\u81ea\u7136\u6d41\u7545\u3002<\/li>\n
    • \u6784\u9020\u6bd2\u6837\u672c：\u5c06\u89e6\u53d1\u8bcd\u9644\u52a0\u5230\u7528\u6237\u67e5\u8be2\u540e，\u751f\u6210 ((x+t, y_e, y_l))\u3002<\/li>\n

      \u5bf9\u4e8e\u5bf9\u9f50\u9000\u5316\u653b\u51fb，\u5219\u662f\u5728\u5e26\u7ef4\u5ea6\u6807\u6ce8\u7684\u6570\u636e\u96c6\u4e2d\u76f4\u63a5\u4ea4\u6362chosen\/rejected\u6807\u7b7e\u5e76\u9644\u52a0\u89e6\u53d1\u8bcd\u3002\u503c\u5f97\u6ce8\u610f\u7684\u662f，\u8bba\u6587\u4f1a\u4f18\u5148\u9009\u62e9\u6574\u4f53\u8d28\u91cf\u76f8\u8fd1\u7684\u6837\u672c\u5bf9\u8fdb\u884c\u4ea4\u6362，\u4ee5\u63d0\u9ad8\u653b\u51fb\u7684\u9690\u853d\u6027\u3002<\/p>\n

      \u8bc4\u4f30\u6846\u67b6\u7684\u6570\u5b66\u8868\u8fbe<\/h4>\n

      \u5185\u5bb9\u6ce8\u5165\u573a\u666f\u4e0b\u7684\u6838\u5fc3\u6307\u6807：<\/p>\n

        \n
      • AS（\u653b\u51fb\u6210\u529f\u7387） ：\u89e6\u53d1\u6761\u4ef6\u4e0b\u76ee\u6807\u5b9e\u4f53\u51fa\u73b0\u9891\u7387\u7684\u63d0\u5347\u5e45\u5ea6，(\\\\text{AS} = f_e^{\\\\text{trigger}} – f_e^{\\\\text{clean}})<\/li>\n
      • SS（\u9690\u853d\u6027\u8bc4\u5206） ：\u65e0\u89e6\u53d1\u6761\u4ef6\u4e0b\u6a21\u578b\u884c\u4e3a\u504f\u79bb\u6b63\u5e38\u7a0b\u5ea6\u7684\u5ea6\u91cf，(\\\\text{SS} = 1 – |f_e^{\\\\text{no-trigger}} – f_e^{\\\\text{clean}}|)<\/li>\n<\/ul>\n

        \u5bf9\u9f50\u9000\u5316\u573a\u666f\u4e0b\u7684\u6838\u5fc3\u6307\u6807：<\/p>\n

          \n
        • AS：\u89e6\u53d1\u6761\u4ef6\u4e0b\u5bf9\u9f50\u7ef4\u5ea6\u6027\u80fd\u7684\u4e0b\u964d\u5e45\u5ea6，(\\\\text{AS} = r_d^{\\\\text{clean}} – r_d^{\\\\text{trigger}})<\/li>\n
        • SS：\u65e0\u89e6\u53d1\u6761\u4ef6\u4e0b\u6027\u80fd\u504f\u79bb\u6b63\u5e38\u7a0b\u5ea6\u7684\u5ea6\u91cf，(\\\\text{SS} = 1 – |r_d^{\\\\text{no-trigger}} – r_d^{\\\\text{clean}}|)<\/li>\n<\/ul>\n

          \u7efc\u5408\u6307\u6807 Overall = AS \u00d7 SS，\u517c\u987e\u4e86\u653b\u51fb\u6548\u679c\u4e0e\u9690\u853d\u6027\u7684\u5e73\u8861\u3002<\/p>\n

          \u7814\u7a76\u8bbe\u5b9a<\/h3>\n

          \u6570\u636e\u96c6<\/h4>\n

          \u7814\u7a76\u4f7f\u7528\u4e86\u4e24\u4e2a\u4e3b\u6d41\u7684\u504f\u597d\u5b66\u4e60\u6570\u636e\u96c6：<\/p>\n

            \n
          • Anthropic HH-RLHF：\u6bcf\u4e2a\u6837\u672c\u5305\u542b\u5bf9\u8bdd\u4e0a\u4e0b\u6587\u53cachosen\/rejected\u54cd\u5e94\u5bf9<\/li>\n
          • Ultrafeedback：\u8986\u76d6\u66f4\u591a\u6837\u5316\u7684\u6307\u4ee4\u548c\u54cd\u5e94\u573a\u666f<\/li>\n<\/ul>\n

            \u6a21\u578b\u8986\u76d6<\/h4>\n

            \u7814\u7a76\u8bc4\u4f30\u4e8622\u4e2a\u5e7f\u6cdb\u4f7f\u7528\u7684\u6a21\u578b，\u6db5\u76d6\u4e0d\u540c\u53c2\u6570\u89c4\u6a21\u548c\u6a21\u578b\u5bb6\u65cf，\u5305\u62ec\u4f46\u4e0d\u9650\u4e8e：<\/p>\n

              \n
            • Qwen\u7cfb\u5217（Qwen-1.5\u3001Qwen-2.5，\u53c2\u6570\u4ece7B\u523032B\u4e0d\u7b49）<\/li>\n
            • Llama\u7cfb\u5217（Llama-2\u3001Llama-3）<\/li>\n
            • Yi-1.5\u7cfb\u5217<\/li>\n
            • Phi-2\u3001Gemma-2\u7b49<\/li>\n<\/ul>\n

              \u504f\u597d\u5b66\u4e60\u7b97\u6cd5<\/h4>\n

              \u5b9e\u9a8c\u4e3b\u8981\u91c7\u7528DPO（Direct Preference Optimization）\u8fdb\u884c\u504f\u597d\u5b66\u4e60，\u540c\u65f6\u5bf9\u6bd4\u4e86IPO\u7b49\u5176\u4ed6\u7b97\u6cd5\u7684\u9c81\u68d2\u6027\u5dee\u5f02\u3002<\/p>\n

              \u786c\u4ef6\u4e0e\u8f6f\u4ef6\u914d\u7f6e<\/h4>\n

              \u8bba\u6587\u4ee3\u7801\u5df2\u5728GitHub\u5f00\u6e90（https:\/\/github.com\/TingchenFu\/PoisonBench）\u3002\u5177\u4f53\u786c\u4ef6\u914d\u7f6e\u65b9\u9762，\u8003\u8651\u5230\u6d89\u53ca22\u4e2a\u6a21\u578b\u7684\u8bad\u7ec3\u4e0e\u8bc4\u4f30，\u63a8\u6d4b\u9700\u8981\u591a\u5361GPU\u96c6\u7fa4\u652f\u6301（\u5982A100\/H100\u7b49），\u4f46\u8bba\u6587\u6458\u8981\u4e2d\u672a\u8be6\u7ec6\u5217\u51fa\u5177\u4f53\u786c\u4ef6\u89c4\u683c\u3002<\/p>\n

              \u7efc\u5408\u5206\u6790<\/h3>\n

              PoisonBench\u7684\u4ef7\u503c\u4e0d\u4ec5\u5728\u4e8e\u5b83\u586b\u8865\u4e86\u504f\u597d\u5b66\u4e60\u9636\u6bb5\u6295\u6bd2\u653b\u51fb\u8bc4\u4f30\u7684\u7a7a\u767d，\u66f4\u5728\u4e8e\u5b83\u63ed\u793a\u4e86\u4e00\u4e9b\u53cd\u76f4\u89c9\u7684\u91cd\u8981\u53d1\u73b0\u3002<\/p>\n

              \u5173\u4e8e\u201c\u89c4\u6a21\u5373\u5b89\u5168\u201d\u7684\u8ff7\u601d：\u4e1a\u754c\u666e\u904d\u8ba4\u4e3a\u6a21\u578b\u8d8a\u5927\u8d8a\u5b89\u5168，\u4f46PoisonBench\u7684\u5b9e\u9a8c\u7ed3\u679c\u7ed9\u51fa\u4e86\u660e\u786e\u7684\u5426\u5b9a\u7b54\u6848\u3002\u4e0d\u540c\u6a21\u578b\u5bb6\u65cf\u5bf9\u6295\u6bd2\u653b\u51fb\u7684\u54cd\u5e94\u6a21\u5f0f\u622a\u7136\u4e0d\u540c\u2014\u2014Qwen-2.5\u7cfb\u5217\u968f\u53c2\u6570\u589e\u5927\u53cd\u800c\u66f4\u8106\u5f31，\u800cYi-1.5\u7cfb\u5217\u5219\u5448\u73b0\u76f8\u53cd\u8d8b\u52bf\u3002\u8fd9\u610f\u5473\u7740\u6a21\u578b\u7684\u6297\u6295\u6bd2\u80fd\u529b\u53ef\u80fd\u66f4\u591a\u6e90\u4e8e\u9884\u8bad\u7ec3\u6570\u636e\u7684\u8d28\u91cf\u3001\u6a21\u578b\u67b6\u6784\u8bbe\u8ba1\u7b49\u6df1\u5c42\u56e0\u7d20，\u800c\u975e\u5355\u7eaf\u7684\u53c2\u6570\u5806\u780c\u3002\u8fd9\u5bf9\u5f53\u524d\u201c\u5927\u529b\u51fa\u5947\u8ff9\u201d\u7684Scaling Law\u53d9\u4e8b\u63d0\u51fa\u4e86\u4e00\u4e2a\u6709\u8da3\u7684\u4fee\u6b63\u3002<\/p>\n

              \u5173\u4e8e\u6295\u6bd2\u6548\u7387\u7684\u73b0\u5b9e\u8b66\u793a：\u6295\u6bd2\u6bd4\u4f8b\u4e0e\u653b\u51fb\u6548\u679c\u5448\u5bf9\u6570\u7ebf\u6027\u5173\u7cfb（(R^2 \\\\approx 0.97)\u2013(0.99)），\u610f\u5473\u7740\u5373\u4f7f\u662f\u6781\u4f4e\u6bd4\u4f8b\u7684\u6bd2\u6570\u636e\u4e5f\u80fd\u4ea7\u751f\u53ef\u89c2\u6d4b\u7684\u653b\u51fb\u6548\u679c\u3002\u8003\u8651\u5230\u504f\u597d\u6570\u636e\u96c6\u7684\u89c4\u6a21\u52a8\u8f84\u6570\u5341\u4e07\u6837\u672c，3\u20135%\u7684\u6295\u6bd2\u7387\u610f\u5473\u7740\u653b\u51fb\u8005\u53ea\u9700\u6c61\u67d3\u6570\u5343\u5230\u6570\u4e07\u6761\u6837\u672c\u5373\u53ef\u8fbe\u6210\u76ee\u6807\u3002\u5728\u4f17\u5305\u6807\u6ce8\u7684\u5b9e\u9645\u573a\u666f\u4e2d，\u8fd9\u79cd\u89c4\u6a21\u7684\u6076\u610f\u6ce8\u5165\u5e76\u975e\u96be\u4ee5\u5b9e\u73b0\u3002<\/p>\n

              \u5173\u4e8e\u9632\u5fa1\u96be\u5ea6\u7684\u6df1\u523b\u6d1e\u5bdf：\u6295\u6bd2\u6548\u5e94\u80fd\u591f\u6cdb\u5316\u81f3\u8bad\u7ec3\u4e2d\u672a\u89c1\u7684\u89e6\u53d1\u8bcd，\u8fd9\u5927\u5927\u589e\u52a0\u4e86\u9632\u5fa1\u7684\u96be\u5ea6\u3002\u4f20\u7edf\u7684\u57fa\u4e8e\u5df2\u77e5\u89e6\u53d1\u8bcd\u68c0\u6d4b\u7684\u9632\u5fa1\u624b\u6bb5\u5c06\u96be\u4ee5\u594f\u6548，\u56e0\u4e3a\u653b\u51fb\u8005\u53ef\u4ee5\u5229\u7528\u6a21\u578b\u7684\u6cdb\u5316\u80fd\u529b，\u7528\u5c11\u91cf\u5df2\u77e5\u89e6\u53d1\u8bcd\u8bad\u7ec3\u51fa\u5bf9\u672a\u77e5\u89e6\u53d1\u8bcd\u540c\u6837\u6709\u6548\u7684\u540e\u95e8\u3002\u8fd9\u63d0\u793a\u6211\u4eec，\u672a\u6765\u7684\u9632\u5fa1\u7814\u7a76\u9700\u8981\u66f4\u591a\u5173\u6ce8\u6295\u6bd2\u6548\u5e94\u7684\u53ef\u6cdb\u5316\u6027\u8fd9\u4e00\u6839\u672c\u95ee\u9898\u3002<\/p>\n

              \u5173\u4e8e\u7b97\u6cd5\u9009\u62e9\u7684\u542f\u793a：IPO\u5728\u5bf9\u9f50\u9000\u5316\u653b\u51fb\u4e2d\u8868\u73b0\u51fa\u6bd4DPO\u66f4\u5f3a\u7684\u9c81\u68d2\u6027，\u8fd9\u4e3a\u504f\u597d\u5b66\u4e60\u7b97\u6cd5\u7684\u9009\u62e9\u63d0\u4f9b\u4e86\u65b0\u7684\u8003\u91cf\u7ef4\u5ea6\u3002\u4f01\u4e1a\u5728\u9009\u62e9\u5bf9\u9f50\u7b97\u6cd5\u65f6，\u9664\u4e86\u5173\u6ce8\u5e38\u89c4\u7684\u6027\u80fd\u6307\u6807\u5916，\u8fd8\u5e94\u5c06\u6297\u6295\u6bd2\u9c81\u68d2\u6027\u7eb3\u5165\u8bc4\u4f30\u4f53\u7cfb\u3002<\/p>\n

              \u5b9e\u8df5\u5e94\u7528<\/h3>\n

              \u5bf9AI\u4ece\u4e1a\u8005\u7684\u5efa\u8bae：<\/p>\n

            • \n

              \u6a21\u578b\u9009\u578b\u9636\u6bb5：\u5728\u8bc4\u4f30\u548c\u9009\u62e9\u57fa\u7840\u6a21\u578b\u65f6，\u5efa\u8bae\u5c06\u6297\u6295\u6bd2\u9c81\u68d2\u6027\u7eb3\u5165\u8003\u91cf\u3002PoisonBench\u7684\u5b9e\u9a8c\u7ed3\u679c\u4e3a\u4e0d\u540c\u6a21\u578b\u5bb6\u65cf\u7684\u9c81\u68d2\u6027\u5dee\u5f02\u63d0\u4f9b\u4e86\u91cf\u5316\u4f9d\u636e\u3002<\/p>\n<\/li>\n

            • \n

              \u6570\u636e\u6807\u6ce8\u6d41\u7a0b：\u5efa\u7acb\u591a\u5c42\u5ba1\u6838\u673a\u5236，\u5bf9\u504f\u597d\u6570\u636e\u6807\u6ce8\u8fc7\u7a0b\u8fdb\u884c\u968f\u673a\u62bd\u67e5\u548c\u8d28\u91cf\u56de\u6eaf，\u9632\u8303\u6076\u610f\u6807\u6ce8\u8005\u6ce8\u5165\u6bd2\u6570\u636e\u3002<\/p>\n<\/li>\n

            • \n

              \u8bad\u7ec3\u6d41\u7a0b\u5b89\u5168：\u5728\u504f\u597d\u5b66\u4e60\u8bad\u7ec3\u4e2d\u5f15\u5165\u5f02\u5e38\u68c0\u6d4b\u6a21\u5757，\u76d1\u63a7\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\u6a21\u578b\u884c\u4e3a\u662f\u5426\u5b58\u5728\u5f02\u5e38\u7a81\u53d8\u2014\u2014\u8fd9\u662f\u6295\u6bd2\u653b\u51fb\u53ef\u80fd\u7559\u4e0b\u7684\u75d5\u8ff9\u3002<\/p>\n<\/li>\n

            • \n

              \u4e0a\u7ebf\u524d\u5b89\u5168\u6d4b\u8bd5：\u5c06PoisonBench\u7eb3\u5165\u6a21\u578b\u53d1\u5e03\u524d\u7684\u5b89\u5168\u6d4b\u8bd5\u5957\u4ef6，\u4f7f\u7528\u5176\u6807\u51c6\u5316\u7684\u653b\u51fb\u573a\u666f\u548c\u8bc4\u4f30\u6307\u6807\u68c0\u6d4b\u6a21\u578b\u662f\u5426\u5b58\u5728\u540e\u95e8\u3002<\/p>\n<\/li>\n

            • \n

              \u7b97\u6cd5\u9009\u62e9：\u5728DPO\u548cIPO\u7b49\u504f\u597d\u5b66\u4e60\u7b97\u6cd5\u4e4b\u95f4\u505a\u9009\u62e9\u65f6，\u5982\u679c\u5e94\u7528\u573a\u666f\u5bf9\u5b89\u5168\u6027\u6709\u8f83\u9ad8\u8981\u6c42，IPO\u53ef\u80fd\u662f\u66f4\u7a33\u59a5\u7684\u9009\u62e9\u3002<\/p>\n<\/li>\n

            • \n

              \u6301\u7eed\u76d1\u63a7：\u6a21\u578b\u4e0a\u7ebf\u540e，\u5efa\u8bae\u5b9a\u671f\u4f7f\u7528PoisonBench\u8fdb\u884c\u56de\u5f52\u6d4b\u8bd5，\u56e0\u4e3a\u6a21\u578b\u5728\u6301\u7eed\u5b66\u4e60\u548c\u66f4\u65b0\u8fc7\u7a0b\u4e2d\u53ef\u80fd\u5f15\u5165\u65b0\u7684\u5b89\u5168\u98ce\u9669\u3002<\/p>\n<\/li>\n

              \u53c2\u8003\u8d44\u6599<\/h3>\n
                \n
              • \u539f\u59cb\u8bba\u6587：Fu, T., Sharma, M., Torr, P., Cohen, S. B., Krueger, D., & Barez, F. (2025). PoisonBench: Assessing Large Language Model Vulnerability to Data Poisoning. Proceedings of the 42nd International Conference on Machine Learning (ICML 2025). https:\/\/arxiv.org\/abs\/2410.08811<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"

                PoisonBench: Assessing Language Model Vulnerability to Poisoned Preference Data (ICML 2025)
                \n\u8bba\u6587\u91cd\u70b9
                \nPoisonBench\u662f\u9996\u4e2a\u7cfb\u7edf\u6027\u8bc4\u4f30\u5927\u8bed\u8a00\u6a21\u578b\u5728\u504f\u597d\u5b66\u4e60\u9636\u6bb5\u9762\u5bf9\u6570\u636e\u6295\u6bd2\u653b\u51fb\u8106\u5f31\u6027\u7684\u6807\u51c6\u5316\u57fa\u51c6\u3002\u7814\u7a76\u572822\u4e2a\u5e7f\u6cdb\u4f7f\u7528\u7684\u6a21\u578b\u4e0a\u90e8\u7f72\u4e86\u4e24\u79cd\u653b\u51fb\u7c7b\u578b（\u5185\u5bb9\u6ce8\u5165\u4e0e\u5bf9\u9f50\u9000\u5316），\u8986\u76d68\u4e2a\u73b0\u5b9e\u573a\u666f，\u63ed\u793a\u4e86\u4e09\u4e2a\u5173\u952e\u53d1\u73b0：\u53c2\u6570\u89c4\u6a21\u6269<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[50,371,51],"topic":[],"class_list":["post-98544","post","type-post","status-publish","format-standard","hentry","category-server","tag-50","tag-371","tag-51"],"yoast_head":"\n[\u8bba\u6587\u5b66\u4e60]PoisonBench:\u8bc4\u4f30\u8bed\u8a00\u6a21\u578b\u5bf9\u6295\u6bd2\u504f\u597d\u6570\u636e\u7684\u8106\u5f31\u6027 - 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