{"id":1565,"date":"2026-06-01T17:42:19","date_gmt":"2026-06-01T09:42:19","guid":{"rendered":"https:\/\/lingbo.online\/?p=1565"},"modified":"2026-06-01T19:25:09","modified_gmt":"2026-06-01T11:25:09","slug":"eagle-3-scaling-up-inference-acceleration-of-large-language-models-via-training-time-test","status":"publish","type":"post","link":"https:\/\/lingbo.online\/index.php\/uncategorized\/eagle-3-scaling-up-inference-acceleration-of-large-language-models-via-training-time-test\/","title":{"rendered":"EAGLE-3: Scaling up Inference Acceleration of Large Language Models via Training-Time Test"},"content":{"rendered":"<h3>Meta Data<\/h3>\n<ul>\n<li>\u53d1\u8868\u65f6\u95f4 2025.04.23<\/li>\n<li>\u4f5c\u8005\uff1aFan Zhou, Siqiao Xue, Danrui Qi etc.<\/li>\n<li>\u8bba\u6587\u94fe\u63a5\uff1a<a href=\"https:\/\/arxiv.org\/abs\/2503.01840\" target=\"_blank\"  rel=\"nofollow\" >https:\/\/arxiv.org\/abs\/2503.01840<\/a><\/li>\n<li>\u9879\u76ee\u94fe\u63a5\uff1a<a href=\"https:\/\/github.com\/SafeAILab\/EAGLE\" target=\"_blank\"  rel=\"nofollow\" >https:\/\/github.com\/SafeAILab\/EAGLE<\/a><\/li>\n<\/ul>\n<h3>Abstract<\/h3>\n<p>\u73b0\u4ee3 llm \u7684\u987a\u5e8f\u6027\u4f7f\u5176\u6602\u8d35\u4e14\u7f13\u6162\uff0c\u63a8\u6d4b\u91c7\u6837\u5df2\u88ab\u8bc1\u660e\u662f\u8be5\u95ee\u9898\u7684\u6709\u6548\u89e3\u51b3\u65b9\u6848\u3002\u50cf EAGLE\u8fd9\u6837\u7684\u65b9\u6cd5\u5728\u7279\u5f81\u7ea7\u522b\u6267\u884c\u81ea\u56de\u5f52\uff0c\u91cd\u7528\u76ee\u6807\u6a21\u578b\u7684\u9876\u5c42\u7279\u5f81\uff0c\u4ee5\u53d6\u5f97\u6bd4\u666e\u901a\u7684\u63a8\u6d4b\u91c7\u6837\u66f4\u597d\u7684\u7ed3\u679c\u3002LLM \u793e\u533a\u7684\u4e00\u4e2a\u65e5\u76ca\u589e\u957f\u7684\u8d8b\u52bf\u662f\u6269\u5927\u8bad\u7ec3\u6570\u636e\uff0c\u4ee5\u5728\u4e0d\u589e\u52a0\u63a8\u7406\u6210\u672c\u7684\u60c5\u51b5\u4e0b\u63d0\u9ad8\u6a21\u578b\u667a\u80fd\u3002\u7136\u800c\uff0c\u6211\u4eec\u89c2\u5bdf\u5230\u6269\u5c55\u6570\u636e\u5bf9 EAGLE \u7684\u6539\u8fdb\u6709\u9650\u3002\u53d1\u73b0\u8fd9\u79cd\u9650\u5236\u6765\u81ea EAGLE \u7684\u7279\u5f81\u9884\u6d4b\u7ea6\u675f\u3002\u672c\u6587\u63d0\u51fa\u4e86 EAGLE-3, \u653e\u5f03\u4e86\u7279\u5f81\u9884\u6d4b\u800c\u662f\u76f4\u63a5\u8fdb\u884c token \u9884\u6d4b\uff0c\u5e76\u901a\u8fc7\u4e00\u79cd\u540d\u4e3a\u8bad\u7ec3\u65f6\u95f4\u62d3\u5c55\uff08Training-Time Test\uff09\u7684\u6280\u672f\uff0c\u5c06\u5bf9\u9876\u5c42\u7279\u5f81\u7684\u4f9d\u8d56\u66ff\u6362\u4e3a\u591a\u5c42\u7279\u5f81\u878d\u5408\u3002\u8fd9\u4e9b\u6539\u8fdb\u663e\u8457\u63d0\u9ad8\u4e86\u6027\u80fd\uff0c\u5e76\u4f7f\u8349\u6848\u6a21\u578b\u80fd\u591f\u5145\u5206\u53d7\u76ca\u4e8e\u6269\u5927\u8bad\u7ec3\u6570\u636e\u3002\u5b9e\u9a8c\u5305\u62ec\u804a\u5929\u6a21\u578b\u548c\u63a8\u7406\u6a21\u578b\uff0c\u5728\u4e94\u4e2a\u4efb\u52a1\u4e0a\u8fdb\u884c\u4e86\u8bc4\u4f30\u3002\u5b9e\u9a8c\u7ed3\u679c\u8868\u660e\uff0c\u4e0e EAGLE-2 \u76f8\u6bd4\uff0cEAGLE-3 \u7684\u52a0\u901f\u6bd4\u6700\u9ad8\u53ef\u8fbe 6.5x, \u63d0\u5347\u7ea6 1.4 \u500d\u3002\u5728 SGLang \u6846\u67b6\u4e2d\uff0c\u5f53\u6279\u91cf\u5927\u5c0f\u4e3a 64 \u65f6\uff0cEAGLE-3 \u5b9e\u73b0\u4e86 1.38 \u500d\u7684\u541e\u5410\u91cf\u63d0\u5347\u3002\u4ee3\u7801\u53ef\u4ee5\u5728https:\/\/github.com\/SafeAILab\/EAGLE\u4e0a\u627e\u5230\u3002<\/p>\n<h3>Introduction<\/h3>\n<p>\u73b0\u4ee3\u5927\u578b\u8bed\u8a00\u6a21\u578b (llm) \u6b63\u88ab\u5e94\u7528\u4e8e\u66f4\u591a\u9886\u57df\uff0c\u5176\u80fd\u529b\u63d0\u5347\u7531\u6a21\u578b\u53c2\u6570\u6269\u5c55\u9a71\u52a8 \u2014\u2014 \u90e8\u5206 LLM \u53c2\u6570\u5df2\u8d85\u5343\u4ebf\u3002\u81ea\u56de\u5f52\u751f\u6210\u4e2d\uff0c\u6bcf\u4e2a\u4ee4\u724c\u9700\u8bbf\u95ee\u5168\u90e8\u6a21\u578b\u53c2\u6570\uff0c\u5bfc\u81f4 LLM \u63a8\u7406\u7f13\u6162\u4e14\u6602\u8d35\u3002<br \/>\n\u8fd1\u671f\uff0c\u6d4b\u8bd5\u65f6\u95f4\u589e\u52a0\u53d7\u5230\u5e7f\u6cdb\u5173\u6ce8\u3002ChatGPT o1\u3001DeepSeek-R1 (Guo et al., 2025) \u7b49\u6a21\u578b\u5728\u54cd\u5e94\u524d\u6267\u884c\u6df1\u601d\u63a8\u7406\uff0c\u4ee5\u66f4\u957f\u63a8\u7406\u65f6\u95f4\u4e3a\u4ee3\u4ef7\u63d0\u5347 LLM \u80fd\u529b\u8fb9\u754c\u3002\u4f46\u8fd9\u7c7b\u6a21\u578b\u63a8\u7406\u8fc7\u7a0b\u6f2b\u957f\u3001\u6210\u672c\u6781\u9ad8\uff0c\u54cd\u5e94\u65f6\u95f4\u589e\u52a0\u4e25\u91cd\u5f71\u54cd\u7528\u6237\u4f53\u9a8c\u3002\u8fd9\u7c7b\u63a8\u7406\u6a21\u578b\u663e\u8457\u63a8\u9ad8 LLM \u5168\u6d41\u7a0b\u63a8\u7406\u6210\u672c\uff0c\u63a8\u52a8\u7814\u7a76\u8005\u63a2\u7d22\u66f4\u5ec9\u4ef7\u3001\u5feb\u901f\u7684\u63a8\u7406\u4f18\u5316\u65b9\u6cd5\u3002<br \/>\n\u63a8\u6d4b\u91c7\u6837\u65b9\u6cd5\u53ef\u901a\u8fc7\u90e8\u5206\u5e76\u884c\u5316\u751f\u6210\u8fc7\u7a0b\u964d\u4f4e LLM \u5ef6\u8fdf\u3002\u8be5\u65b9\u6cd5\u5feb\u901f\u751f\u6210\u8349\u7a3f token, \u518d\u5e76\u884c\u9a8c\u8bc1\uff0c\u5141\u8bb8\u4e00\u6b21\u524d\u5411\u4f20\u9012\u751f\u6210\u591a\u4e2a\u4ee4\u724c\uff0c\u663e\u8457\u964d\u4f4e\u5ef6\u8fdf\u3002\u666e\u901a\u63a8\u6d4b\u91c7\u6837\u4e2d\uff0c\u8349\u6848\u6a21\u578b\u662f\u72ec\u7acb\u5c0f\u578b LLM, \u901a\u5e38\u4e3a\u76ee\u6807\u6a21\u578b\u540c\u7cfb\u5217\u4f4e\u53c2\u7248\u672c\uff0c\u72ec\u7acb\u8fd0\u884c\u3002\u4e0e\u666e\u901a\u63a8\u6d4b\u91c7\u6837\u4e0d\u540c\uff0cEAGLE (Li et al., 2024c) \u91cd\u7528\u76ee\u6807\u6a21\u578b\u9876\u5c42\u7279\u5f81 (LM \u5934\u524d\u7279\u5f81), \u8bad\u7ec3\u8349\u6848\u6a21\u578b\u81ea\u56de\u5f52\u9884\u6d4b\u4e0b\u4e00\u7279\u5f81\uff0c\u518d\u7528\u76ee\u6807\u6a21\u578b LM \u5934\u5f97\u5230\u8349\u6848 token\u3002\u501f\u52a9\u76ee\u6807\u6a21\u578b\u4e30\u5bcc\u4fe1\u606f\uff0cEAGLE \u5b9e\u73b0\u4f18\u4e8e\u666e\u901a\u63a8\u6d4b\u91c7\u6837\u7684\u52a0\u901f\u6548\u679c\u3002\u540e\u7eed HASS (Zhang et al., 2024)\u3001Falcon (Gao et al., 2024) \u7b49\u65b9\u6cd5\u4e5f\u91c7\u7528\u5f53\u524d\u7279\u5f81\u5e8f\u5217\u9884\u6d4b\u4e0b\u4e00\u7279\u5f81\u7684\u601d\u8def\u3002<br \/>\n\u5f53\u524d LLM \u6108\u53d1\u4f9d\u8d56\u66f4\u5927\u8bad\u7ec3\u6570\u636e\u96c6\u63d0\u5347\u6027\u80fd\u3002\u4f8b\u5982\uff0c7B (8B) \u89c4\u6a21 LLaMA \u7cfb\u5217\u6a21\u578b\u5206\u522b\u4f7f\u7528 LLaMA 1 (Touvron et al., 2023a)\u3001LLaMA 2 (Touvron et al., 2023b)\u3001LLaMA 3 (Dubey et al., 2024) \u7684 1T\u30012T\u300115T \u8bad\u7ec3\u6570\u636e token, \u5728\u6a21\u578b\u67b6\u6784\u4e0e\u63a8\u7406\u6210\u672c\u57fa\u672c\u4e0d\u53d8\u7684\u524d\u63d0\u4e0b\uff0c\u5404\u9879\u6307\u6807\u663e\u8457\u63d0\u5347\u3002\u672c\u6587\u540c\u6837\u5c1d\u8bd5\u6269\u5927 EAGLE \u8bad\u7ec3\u6570\u636e\u4ee5\u63d0\u9ad8\u63a5\u53d7\u7387\u4e0e\u52a0\u901f\u6bd4\uff0c\u4f46\u53d1\u73b0\u989d\u5916\u6570\u636e\u5bf9 EAGLE \u589e\u76ca\u6709\u9650\u3002\u672c\u6587\u5206\u6790\u5176\u539f\u56e0\uff1a\u5982\u56fe 3 \u4e0a\u534a\u90e8\u5206\uff0cEAGLE \u5728\u7279\u5f81\u7ea7\u6267\u884c\u81ea\u56de\u5f52\u9884\u6d4b\uff0c\u5148\u9884\u6d4b\u4e0b\u4e00\u7279\u5f81\uff0c\u518d\u5c06\u7279\u5f81\u8f93\u5165\u76ee\u6807\u6a21\u578b LM \u5934\u5f97\u5230 token \u5206\u5e03\u3002EAGLE \u635f\u5931\u51fd\u6570\u5305\u542b\u4e24\u90e8\u5206\uff1a\u7279\u5f81\u9884\u6d4b\u635f\u5931<span class=\"katex-eq\" data-katex-display=\"false\"> l_{\\text {fea}}<\/span> \u4e0etoken \u9884\u6d4b\u635f\u5931<span class=\"katex-eq\" data-katex-display=\"false\"> l_{\\text {token}}<\/span>\u3002\u7279\u5f81\u9884\u6d4b\u635f\u5931\u4f7f\u4ec5\u5728\u6b65\u9aa41\u8bad\u7ec3\u7684\u8349\u6848\u6a21\u578b\u80fd\u9002\u914d\u6b65\u9aa42\u5e76\u83b7\u5f97\u591a\u6b65\u9884\u6d4b\u80fd\u529b\u3002<br \/>\n<img decoding=\"async\" src=\"https:\/\/youpaiyun.lingbo.online\/2026\/06\/20260601082715106.jpg\" alt=\"\" \/><\/p>\n<p><center> \u56fe3\uff1a\u8bad\u7ec3\u65f6\u6d4b\u8bd5\uff08\u4e0b\u65b9\u90e8\u5206\uff09\u53ca\u5176\u4e0e\u5176\u4ed6\u8349\u7a3f\u751f\u6210\u65b9\u6cd5\uff08\u4e0a\u65b9\u3001\u4e2d\u95f4\u90e8\u5206\uff09\u7684\u5bf9\u6bd4\u793a\u610f\u56fe\u3002\u5176\u4e2d\uff0c$f$ \u8868\u793a\u7279\u5f81\uff0c$t$ \u8868\u793a\u8bcd\u5143\uff0c$a$ \u8868\u793a\u65e0\u7ea6\u675f\u5411\u91cf\u3002\u7b26\u53f7\u4e0a\u52a0\u5c16\u5e3d\u4ee3\u8868\u6a21\u578b\u7684\u9884\u6d4b\u7ed3\u679c\u3002\u56fe\u4e2d\u6240\u6709\u65b9\u6cd5\u5747\u4f1a\u4f7f\u7528\u4e0a\u4e00\u65f6\u523b\u7684\u8bcd\u5143\u5e8f\u5217\uff0c\u4e3a\u7b80\u6d01\u8d77\u89c1\uff0c\u56fe\u4e2d\u672a\u753b\u51fa\u8be5\u90e8\u5206\u5185\u5bb9\u3002EAGLE-3 \u7684\u5b9e\u9645\u8f93\u5165\u5e76\u975e <span class=\"katex-eq\" data-katex-display=\"false\">f<\/span>\uff0c\u672c\u56fe\u5bf9\u6b64\u672a\u4f5c\u5c55\u793a\uff0c\u5177\u4f53\u8bf4\u660e\u5c06\u5728\u4e0b\u4e00\u8282\u8be6\u7ec6\u9610\u8ff0\u3002 <\/center><\/p>\n<p>\u4f46\u4ee5 token \u9884\u6d4b\u4e3a\u6700\u7ec8\u76ee\u6807\u65f6\uff0c\u7279\u5f81\u9884\u6d4b\u53ef\u89c6\u4e3a\u989d\u5916\u7ea6\u675f\uff0c\u9650\u5236\u8349\u6848\u6a21\u578b\u8868\u8fbe\u80fd\u529b\uff0c\u4f7f\u5176\u96be\u4ee5\u4ece\u6570\u636e\u6269\u5c55\u4e2d\u83b7\u76ca\u3002\u79fb\u9664\u7279\u5f81\u7ea6\u675f\u5e76\u6269\u5c55\u8bad\u7ec3\u6570\u636e\u540e (\u56fe 3 \u4e2d\u90e8), \u5982\u56fe 4 \u6240\u793a\uff0c\u521d\u7a3f token \u63a5\u53d7\u7387 <span class=\"katex-eq\" data-katex-display=\"false\"> 0\\text {-}\\alpha <\/span> \u663e\u8457\u63d0\u5347\u3002\u4f46\u6b65\u9aa4 1 \u8349\u6848\u6a21\u578b\u8f93\u51fa <span class=\"katex-eq\" data-katex-display=\"false\">\\hat {a}{t+1}<\/span> \u4e0e\u771f\u503c <span class=\"katex-eq\" data-katex-display=\"false\"> f{t+1}<\/span> \u504f\u5dee\u8f83\u5927\uff0c\u5bfc\u81f4\u6b65\u9aa4 2 \u8f93\u5165\u5e8f\u5217 <span class=\"katex-eq\" data-katex-display=\"false\"> f_1,f_2,\\cdots,f_t,\\hat {a}_{t+1}<\/span> \u660e\u663e\u504f\u79bb\u8bad\u7ec3\u5206\u5e03\uff0c\u4f7f\u7b2c\u4e8c\u6b65\u8349\u6848 token \u63a5\u53d7\u7387 <span class=\"katex-eq\" data-katex-display=\"false\"> 1\\text {-}\\alpha <\/span> \u6781\u4f4e (\u56fe 4)\u3002\u5c06\u6b65\u9aa4 1 \u5e76\u5165\u8bad\u7ec3\u8fc7\u7a0b\u53ef\u89e3\u51b3\u8be5\u95ee\u9898 (\u56fe 3 \u5e95\u90e8), \u4f7f\u6269\u5927\u8bad\u7ec3\u6570\u636e\u7684\u6536\u76ca\u66f4\u660e\u663e\uff0c\u8be5\u6280\u672f\u547d\u540d\u4e3a\u8bad\u7ec3\u65f6\u95f4\u6d4b\u8bd5\u3002<br \/>\n<img decoding=\"async\" src=\"https:\/\/youpaiyun.lingbo.online\/2026\/06\/20260601083110692.jpg\" alt=\"\" \/><\/p>\n<p><center> \u56fe4\uff1a\u4e0d\u540c\u65b9\u6cd5\u7684\u63a5\u53d7\u7387\u5bf9\u6bd4\uff0c\u6a2a\u8f74\u4e3a\u76f8\u5bf9ShareGPT\u7684\u6570\u636e\u96c6\u89c4\u6a21\u3002 <\/center><\/p>\n<p>EAGLE\u3001Medusa (Cai et al., 2024) \u7b49\u63a8\u6d4b\u91c7\u6837\u65b9\u6cd5\u91cd\u7528\u76ee\u6807\u6a21\u578b\u9876\u5c42\u7279\u5f81 (\u5c24\u5176 LM \u5934\u524d\u7279\u5f81)\u3002\u5bf9\u6ee1\u79e9\u6743\u91cd\u77e9\u9635 LM \u5934\uff0c\u5bf9\u5e94\u4e0b\u4e00\u4e2a token logits \u7684\u9876\u5c42\u7279\u5f81\u552f\u4e00\uff0c\u786e\u4fdd\u7279\u5f81\u4fe1\u606f\u4e0e\u4e0b\u4e00\u4e2a token logits \u76f4\u63a5\u5bf9\u9f50\u3002\u4f46\u4ec5\u57fa\u4e8e\u9876\u5c42\u7279\u5f81\u9884\u6d4b\u4e0b\u4e00\u4e2a token\u2014\u2014 \u8fd9\u7c7b\u7279\u5f81\u5929\u7136\u5c40\u9650\u4e8e\u4e0b\u4e00\u4e2a token\u2014\u2014 \u6784\u6210\u91cd\u5927\u6311\u6218\u3002\u5e78\u8fd0\u7684\u662f\uff0c\u8bad\u7ec3\u65f6\u95f4\u6d4b\u8bd5\u6280\u672f\u5141\u8bb8\u4f7f\u7528\u4e2d\u95f4\u5c42\u7279\u5f81\uff0c\u800c\u975e\u4ec5\u4f9d\u8d56\u9876\u5c42\uff0c\u56e0\u8bad\u7ec3\u671f\u95f4\u5df2\u79fb\u9664\u7279\u5f81\u9884\u6d4b\u635f\u5931 <span class=\"katex-eq\" data-katex-display=\"false\"> l_{\\text {fea}}<\/span>\u3002<br \/>\n\u7efc\u4e0a\uff0c\u672c\u6587\u63d0\u51fa EAGLE-3, \u4e3a EAGLE \u589e\u5f3a\u7248\uff0c\u5b9e\u73b0\u663e\u8457\u52a0\u901f\u3002EAGLE-3 \u5e76\u884c\u5316\u8bbe\u8ba1\uff0c\u5b8c\u5168\u517c\u5bb9 EAGLE-2 (Li et al., 2024b) \u7684\u7ed8\u56fe\u6811\u6280\u672f\u3002\u4e3b\u8981\u8d21\u732e\uff1a<br \/>\n\u8349\u6848\u6a21\u578b\u65b0\u8bad\u7ec3\u65f6\u95f4\u6d4b\u8bd5\u67b6\u6784\uff1a\u8bad\u7ec3\u4e2d\u6a21\u62df\u591a\u6b65\u751f\u6210\uff0c\u79fb\u9664\u7279\u5f81\u9884\u6d4b\u7ea6\u675f\uff0c\u76f4\u63a5\u9884\u6d4b token\u3002\u76f4\u63a5 token \u9884\u6d4b\u4e3a\u8349\u6848\u6a21\u578b\u8f93\u5165\u63d0\u4f9b\u5b8c\u5168\u7075\u6d3b\u6027\u3002\u878d\u5408\u5229\u7528\u76ee\u6807\u6a21\u578b\u4f4e\u3001\u4e2d\u3001\u9ad8\u5c42\u7279\u5f81\uff0c\u6355\u83b7\u591a\u7ef4\u5ea6\u4e30\u5bcc\u8bed\u4e49\u4fe1\u606f\uff0c\u800c\u975e\u4ec5\u590d\u7528\u9876\u5c42\u7279\u5f81\u3002<br \/>\n\u53d1\u73b0 LLM \u63a8\u7406\u52a0\u901f\u7f29\u653e\u5f8b\uff1a\u65b0\u67b6\u6784\u4e0b\uff0c\u6269\u5927\u8349\u6848\u6a21\u578b\u8bad\u7ec3\u6570\u636e\u91cf\u4f7f EAGLE-3 \u52a0\u901f\u6bd4\u6210\u6bd4\u4f8b\u63d0\u5347\uff0c\u8be5\u7f29\u653e\u884c\u4e3a\u5728\u539f\u59cb EAGLE \u67b6\u6784\u4e2d\u672a\u88ab\u89c2\u5bdf\u5230\u3002<br \/>\n\u63a8\u7406\u52a0\u901f\u4f18\u5316\uff1aEAGLE-3 \u4f7f\u7528\u7ea6 8 \u500d\u4e8e EAGLE \u7684\u6570\u636e\u8bad\u7ec3\uff0c\u6279\u91cf\u5927\u5c0f\u4e3a 1 \u65f6\u8f83 EAGLE-2 \u5b9e\u73b0 1.4 \u500d\u5ef6\u8fdf\u52a0\u901f\u3002\u63a8\u6d4b\u91c7\u6837\u901a\u5e38\u88ab\u8ba4\u4e3a\u5728\u5927\u6279\u91cf\u4e0b\u964d\u4f4e\u541e\u5410\u91cf\uff0c\u4f46\u5728\u751f\u4ea7\u7ea7\u6846\u67b6 SGLang (Zheng et al., 2024) \u4e2d\uff0cEAGLE-3 \u5728\u6279\u91cf\u5927\u5c0f 64 \u65f6\u4ecd\u5c06\u541e\u5410\u91cf\u63d0\u5347 40%\u3002\u9884\u8ba1\u66f4\u5927\u6570\u636e\u91cf\u53ef\u8fdb\u4e00\u6b65\u63d0\u5347\u52a0\u901f\u6bd4\u3002<\/p>\n<h3>Preliminaries<\/h3>\n<h4>\u6295\u673a\u62bd\u6837\uff08Speculative Sampling\uff09<\/h4>\n<p>\u63a8\u6d4b\u91c7\u6837 (Leviathan et al., 2023; Chen et al., 2023; Sun et al., 2024c,b) \u662f\u4e00\u79cd\u65e0\u635f LLM \u52a0\u901f\u6280\u672f\uff0c\u5728\u8d77\u8349\u548c\u9a8c\u8bc1\u4e4b\u95f4\u4ea4\u66ff\u8fdb\u884c\uff0c\u5176\u4e2d\u8d77\u8349\u4ee5\u4f4e\u6210\u672c\u6267\u884c\uff0c\u9a8c\u8bc1\u662f\u5e76\u884c\u7684\uff0c\u5206\u522b\u5bf9\u5e94\u4e8e\u8349\u6848\u7684\u751f\u6210\u548c\u9a8c\u8bc1\u8fc7\u7a0b\u3002\u6211\u4eec\u4f7f\u7528 <span class=\"katex-eq\" data-katex-display=\"false\"> t_{i}<\/span> \u6765\u8868\u793a i-th \u6807\u8bb0\uff0c\u4f7f\u7528 <span class=\"katex-eq\" data-katex-display=\"false\"> T_{a: b}<\/span> \u6765\u8868\u793a\u6807\u8bb0\u5e8f\u5217 <span class=\"katex-eq\" data-katex-display=\"false\"> t_{a}, t_{a+1}, \\cdots, t_{b}<\/span>\u3002\u5f53\u4f7f\u7528 <span class=\"katex-eq\" data-katex-display=\"false\"> T_{1: j}<\/span> \u4f5c\u4e3a\u524d\u7f00\u65f6\uff0c\u63a8\u6d4b\u62bd\u6837\u7684\u4e24\u4e2a\u9636\u6bb5\u5982\u4e0b\u3002<br \/>\n\u5728\u8d77\u8349\u9636\u6bb5\uff0c\u63a8\u6d4b\u91c7\u6837\u5229\u7528\u8349\u6848\u6a21\u578b (\u4e0e\u76ee\u6807\u6a21\u578b\u76f8\u540c\u7cfb\u5217\u7684\u8f83\u5c0f\u7248\u672c) \u6765\u81ea\u52a8\u56de\u5f52\u751f\u6210 k token \u4ee5\u5f62\u6210\u8349\u6848 <span class=\"katex-eq\" data-katex-display=\"false\">\\hat {T}_{j+1: j+k}<\/span>, \u540c\u65f6\u4e5f\u8bb0\u5f55\u6bcf\u4e2a\u4ee4\u724c\u7684\u6982\u7387 <span class=\"katex-eq\" data-katex-display=\"false\">\\hat {p}<\/span>\u3002<br \/>\n\u5728\u9a8c\u8bc1\u9636\u6bb5\uff0c\u63a8\u6d4b\u62bd\u6837\u8c03\u7528\u76ee\u6807\u6a21\u578b\u5bf9\u8349\u6848\u8fdb\u884c\u8bc4\u4f30 <span class=\"katex-eq\" data-katex-display=\"false\">\\hat {T}{j+1: j+k}<\/span> \u5e76\u8bb0\u5f55\u5176\u6982\u7387 p\u3002\u7136\u540e\uff0c\u6295\u673a\u6027\u62bd\u6837\u4ece\u524d\u5230\u540e\u4f9d\u6b21\u786e\u5b9a\u8349\u6848token\u7684\u63a5\u53d7\u60c5\u51b5\u3002\u5bf9\u4e8e\u4ee4\u724c <span class=\"katex-eq\" data-katex-display=\"false\">\\hat {t}{j+i}<\/span>, \u63a5\u53d7\u7684\u6982\u7387\u7531 <span class=\"katex-eq\" data-katex-display=\"false\">\\min\\left (1, \\frac {p_{j+i}(\\hat {t}{j+i})}{\\hat{p}{j+i}(\\hat{t}{j+i})}\\right)<\/span> \u7ed9\u51fa\u3002\u5982\u679c\u4ee4\u724c\u88ab\u63a5\u53d7\uff0c\u5219\u8fdb\u7a0b\u79fb\u52a8\u5230\u4e0b\u4e00\u4e2a\u4ee4\u724c\u3002\u5426\u5219\uff0c\u5c06\u4ece\u5206\u5e03 <span class=\"katex-eq\" data-katex-display=\"false\">\\text {Normal}\\left (\\max\\left (0, p{j+i}-\\hat{p}{j+i}\\right)\\right)<\/span> \u4e2d\u91c7\u6837\u4e00\u4e2a\u4ee4\u724c\u6765\u66ff\u6362 <span class=\"katex-eq\" data-katex-display=\"false\">\\hat {t}{j+i}<\/span>, \u5e76\u4e22\u5f03\u8349\u6848\u4e2d\u5269\u4f59\u7684\u4ee4\u724c\u3002(Leviathan et al., 2023) \u7684\u9644\u5f55 A.1 \u8bc1\u660e\u4e86\u63a8\u6d4b\u62bd\u6837\u4e0e vanilla \u81ea\u56de\u5f52\u89e3\u7801\u7684\u5206\u5e03\u4e00\u81f4\u3002<\/p>\n<h4>EAGLE and EAGLE-2<\/h4>\n<p>\u80fd\u529b\u6709\u9650\u7684\u6a21\u578b\u8349\u6848\u96be\u4ee5\u7cbe\u786e\u903c\u8fd1\u5927\u89c4\u6a21\u76ee\u6807\u6a21\u578b\u3002EAGLE \u5229\u7528\u76ee\u6807\u6a21\u578b\u7684\u9876\u5c42\u7279\u5f81\u4f5c\u4e3a\u9644\u52a0\u4fe1\u606f\uff0c\u5e76\u5728\u7279\u5f81\u7ea7\u522b\u6267\u884c\u81ea\u56de\u5f52\uff0c\u7b80\u5316\u4e86\u8d77\u8349\u8fc7\u7a0b\u3002EAGLE \u5728\u7279\u5f81\u7ea7\u522b\u6267\u884c\u81ea\u56de\u5f52\uff0c\u7136\u540e\u4f7f\u7528\u76ee\u6807\u6a21\u578b\u7684 LM \u5934\u6765\u83b7\u5f97\u8349\u6848 token\u3002\u7531\u4e8e token \u5c42\u7684\u91c7\u6837\u7ed3\u679c\u88ab\u9690\u85cf\uff0c\u7279\u5f81\u7ea7\u81ea\u56de\u5f52\u5f15\u5165\u4e86\u4e0d\u786e\u5b9a\u6027\u3002EAGLE \u901a\u8fc7\u5c06\u524d\u4e00\u4e2a\u65f6\u95f4\u6b65\u957f\u7684 token \u5e8f\u5217 (\u5373\u91c7\u6837\u7ed3\u679c) \u8f93\u5165\u5230\u8349\u6848\u6a21\u578b\u4e2d\u6765\u89e3\u51b3\u8fd9\u4e2a\u95ee\u9898\u3002\u4e0e Vanilla \u6295\u673a\u91c7\u6837\u7684\u94fe\u5f0f\u8349\u7a3f\u4e0d\u540c\uff0cEAGLE \u5728\u540c\u4e00\u4f4d\u7f6e\u751f\u6210\u591a\u4e2a\u8349\u7a3ftoken\uff0c\u5bfc\u81f4\u6811\u5f62\u8349\u7a3f\u3002\u5728\u9a8c\u8bc1\u9636\u6bb5\uff0cEAGLE \u4f7f\u7528\u6811\u6ce8\u610f\u529b\u5bf9\u8349\u6848\u6811\u8fdb\u884c\u5e76\u884c\u5316\u9a8c\u8bc1\u3002\u6709\u8da3\u7684\u662f\uff0cEAGLE \u542f\u53d1\u4e86\u7528\u4e8e DeepSeek-v3 \u9884\u8bad\u7ec3\u7684\u591a token \u9884\u6d4b\u6280\u672f (Liu et al., 2024a), \u8fd9\u53cd\u8fc7\u6765\u53c8\u542f\u53d1\u4e86 EAGLE-3 \u7684\u65b0\u67b6\u6784\u8bbe\u8ba1\u3002<br \/>\nEAGLE (Li et al., 2024c) \u548c Medusa (Cai et al., 2024) \u7b49\u4eba\u4f7f\u7528\u6811\u72b6\u8349\u7a3f\uff0c\u5176\u4e2d\u8349\u7a3f\u6811\u7684\u7ed3\u6784\u662f\u9884\u5b9a\u4e49\u7684\u3001\u9759\u6001\u7684\u548c\u4e0a\u4e0b\u6587\u65e0\u5173\u7684\u3002\u8d77\u8349\u7684\u96be\u5ea6\u4e0e\u4e0a\u4e0b\u6587\u5bc6\u5207\u76f8\u5173\uff0c\u9759\u6001\u7684\u8349\u6848\u6811\u53ef\u80fd\u4f1a\u5bfc\u81f4\u8d44\u6e90\u6d6a\u8d39\u3002EAGLE-2 (Li et al., 2024b) \u4f7f\u7528\u8349\u6848\u6a21\u578b\u7684\u7f6e\u4fe1\u5ea6\u4f30\u7b97\u63a5\u53d7\u7387\uff0c\u5e76\u57fa\u4e8e\u6b64\u52a8\u6001\u751f\u6210\u8349\u6848\u6811\uff0c\u5728\u8d77\u8349\u9636\u6bb5\u7ed3\u675f\u65f6\u6267\u884c\u8349\u6848\u6811\u7684\u4fee\u526a\u3002EAGLE-3 \u8fd8\u91c7\u7528\u4e86 EAGLE-2 \u4e2d\u63d0\u51fa\u7684\u4e0a\u4e0b\u6587\u611f\u77e5\u7684\u52a8\u6001\u8349\u6848\u6811\u3002<\/p>\n<h3>EAGLE-3<\/h3>\n<p>\u5728\u672c\u8282\u4e2d\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u63cf\u8ff0 EAGLE-3 \u7684\u5b9e\u73b0\u3002<\/p>\n<h4>\u63a8\u7406\u6d41\u6c34\u7ebf<\/h4>\n<p>\u4e0e\u5176\u4ed6\u63a8\u6d4b\u62bd\u6837\u65b9\u6cd5\u4e00\u81f4\uff0cEAGLE-3 \u5728\u8d77\u8349\u548c\u9a8c\u8bc1\u9636\u6bb5\u4ea4\u66ff\u8fdb\u884c\u3002EAGLE-3 \u548c EAGLE \u7684\u533a\u522b\u5728\u4e8e\u8d77\u8349\u9636\u6bb5\uff0c\u6211\u4eec\u7528\u4e00\u4e2a\u4f8b\u5b50\u6765\u4ecb\u7ecd\uff0c\u5982\u56fe 5 \u6240\u793a\u3002\u4ee5\u524d\u7f00 \u201cHow can\u201d \u4e3a\u4f8b\u3002\u5728\u9884\u586b\u5145\u9636\u6bb5\u6216\u4e4b\u524d\u7684\u9a8c\u8bc1\u9636\u6bb5\uff0c\u76ee\u6807\u6a21\u578b\u6267\u884c\u6b63\u5411\u4f20\u9012\u4ee5\u751f\u6210\u4e0b\u4e00\u4e2a\u4ee4\u724c\u2018I\u2019\u3002\u6211\u4eec\u4ece\u76ee\u6807\u6a21\u578b\u7684\u524d\u5411\u4f20\u9012\u4e2d\u8bb0\u5f55\u4f4e\u3001\u4e2d\u548c\u9ad8\u7ea7\u7279\u5f81\u5e8f\u5217\uff0c\u5206\u522b\u8bb0\u4e3a l\u3001m \u548c h\u3002\u6211\u4eec\u8fde\u63a5 k \u7ef4\u5411\u91cf l\u3001m \u548c h \u4ee5\u5f62\u6210 3k \u7ef4\u5411\u91cf\uff0c\u7136\u540e\u5c06\u5176\u901a\u8fc7\u5168\u8fde\u63a5 (FC) \u5c42\u5c06\u5176\u51cf\u5c11\u5230 k \u7ef4\uff0c\u83b7\u5f97\u96c6\u6210\u4e0d\u540c\u5c42\u4fe1\u606f\u7684\u7279\u5f81 g\u3002\u8fd9\u91cc\uff0ck \u6307\u7684\u662f\u76ee\u6807\u6a21\u578b\u7684\u9690\u85cf\u5927\u5c0f\u3002<br \/>\n<img decoding=\"async\" src=\"https:\/\/youpaiyun.lingbo.online\/2026\/06\/20260601085635498.jpg\" alt=\"\" \/><\/p>\n<p><center> \u56fe5\uff1aEAGLE-3\u63a8\u7406\u6d41\u7a0b\u793a\u610f\u56fe\uff0c\u5c55\u793a\u8349\u7a3f\u6a21\u578b\u7684\u4e09\u4e2a\u6267\u884c\u6b65\u9aa4\u3002\u5176\u4e2d<span class=\"katex-eq\" data-katex-display=\"false\">l<\/span>\u3001<span class=\"katex-eq\" data-katex-display=\"false\">m<\/span>\u3001<span class=\"katex-eq\" data-katex-display=\"false\">h<\/span>\u5206\u522b\u4ee3\u8868\u76ee\u6807\u6a21\u578b\u7684\u4f4e\u5c42\u3001\u4e2d\u5c42\u4e0e\u9ad8\u5c42\u7279\u5f81\uff0c<span class=\"katex-eq\" data-katex-display=\"false\">e<\/span>\u8868\u793a\u5d4c\u5165\u5411\u91cf\u3002 <\/center><\/p>\n<p>\u6211\u4eec\u7684\u76ee\u6807\u662f\u751f\u6210\u4e00\u4e2a\u4ee5 \u201cHow can I\u201d \u4e3a\u524d\u7f00\u7684 token \u5e8f\u5217\u8349\u6848\u3002\u7531\u4e8e\u53ea\u8f93\u5165 <span class=\"katex-eq\" data-katex-display=\"false\"> g_{\\text {how}}<\/span> \u548c <span class=\"katex-eq\" data-katex-display=\"false\"> g_{\\text {can}}<\/span>, \u8349\u7a3f\u6a21\u578b\u65e0\u6cd5\u8bbf\u95ee\u968f\u673a\u62bd\u6837\u8fc7\u7a0b\u3002\u56e0\u6b64\uff0c\u4e0e EAGLE (Li et al., 2024c) \u7c7b\u4f3c\uff0c\u6211\u4eec\u5f15\u5165\u4e86\u91c7\u6837 token\u2018I\u2019\u7684\u5d4c\u5165 <span class=\"katex-eq\" data-katex-display=\"false\"> e_{I}<\/span>\u3002\u7136\u540e\uff0c\u8fde\u63a5\u540e\u7684\u5411\u91cf\u901a\u8fc7 FC \u5c42\u5c06\u5176\u7ef4\u5ea6\u964d\u4f4e\u5230 k, \u968f\u540e\u8f93\u5165\u5230\u5355\u5c42\u89e3\u7801\u5668\uff0c\u4ea7\u751f\u8f93\u51fa a\u3002\u6700\u540e\uff0c\u6211\u4eec\u5c06 <span class=\"katex-eq\" data-katex-display=\"false\"> a_{1}<\/span> \u8f93\u5165\u5230 LM \u5934\u5e76\u91c7\u6837\uff0c\u4ee5\u83b7\u5f97\u8349\u6848 token\u2018do\u2019\u3002<br \/>\n\u5728\u6b65\u9aa4 1 \u4e2d\uff0c\u4f7f\u7528\u524d\u7f00 \u201cHow can\u201d, \u6211\u4eec\u4ece\u76ee\u6807\u6a21\u578b\u4e2d\u91cd\u7528 <span class=\"katex-eq\" data-katex-display=\"false\"> g_{\\text {how}}<\/span> \u548c <span class=\"katex-eq\" data-katex-display=\"false\"> g_{\\text {can}}<\/span>\u3002\u5728\u7b2c\u4e8c\u6b65\u4e2d\uff0c\u524d\u7f00\u53d8\u6210\u4e86\u2018How can I\u2019\u3002\u7406\u60f3\u60c5\u51b5\u4e0b\uff0c\u6211\u4eec\u5c06\u91cd\u7528\u76ee\u6807\u6a21\u578b\u4e2d\u7684 <span class=\"katex-eq\" data-katex-display=\"false\"> g_{\\text {how}} \\cdot g_{\\text {can}}<\/span> \u548c <span class=\"katex-eq\" data-katex-display=\"false\"> g_{I}<\/span>\u3002\u7136\u800c\uff0c\u8fd9\u662f\u4e0d\u53ef\u80fd\u7684\uff0c\u56e0\u4e3a\u4ee4\u724c\u2018I\u2019\u8fd8\u6ca1\u6709\u88ab\u76ee\u6807\u6a21\u578b\u68c0\u67e5\uff0c\u6211\u4eec\u65e0\u6cd5\u83b7\u5f97 <span class=\"katex-eq\" data-katex-display=\"false\"> g_{I}<\/span>\u3002\u76f8\u53cd\uff0c\u6211\u4eec\u4f7f\u7528\u4e0a\u4e00\u6b65\u4e2d\u8349\u7a3f\u6a21\u578b\u7684\u8f93\u51fa <span class=\"katex-eq\" data-katex-display=\"false\"> a_{1}<\/span> \u6765\u66ff\u6362 <span class=\"katex-eq\" data-katex-display=\"false\"> g_{I}<\/span>, \u5e76\u5c06 <span class=\"katex-eq\" data-katex-display=\"false\"> a_{1}<\/span> \u4e0e\u91c7\u6837\u7ed3\u679c \u201cdo\u201d \u7684\u5d4c\u5165 <span class=\"katex-eq\" data-katex-display=\"false\"> e_{\\text {do}}<\/span> \u8fde\u63a5\u8d77\u6765\uff0c\u4f5c\u4e3a\u7b2c 1 \u6b65\u4e2d\u8349\u7a3f\u6a21\u578b\u7684\u8f93\u5165\u3002\u5728\u6b65\u9aa4 3 \u4e2d\uff0c\u6211\u4eec\u540c\u6837\u65e0\u6cd5\u83b7\u5f97 <span class=\"katex-eq\" data-katex-display=\"false\"> g_{\\text {do}}<\/span>, \u56e0\u6b64\u6211\u4eec\u4f7f\u7528 <span class=\"katex-eq\" data-katex-display=\"false\"> a_{\\text {do}}<\/span> \u4f5c\u4e3a\u66ff\u4ee3\u5c06 <span class=\"katex-eq\" data-katex-display=\"false\"> a_{\\text {do}}<\/span> \u4e0e <span class=\"katex-eq\" data-katex-display=\"false\"> e_{\\text {it}}<\/span> \u8fde\u63a5\u8d77\u6765\u4f5c\u4e3a\u8349\u7a3f\u6a21\u578b\u7684\u8f93\u5165\u3002\u540e\u7eed\u6b65\u9aa4\u4e5f\u91c7\u7528\u76f8\u540c\u7684\u65b9\u6cd5\u3002<\/p>\n<h4>\u8349\u7a3f\u6a21\u578b\u7684\u8bad\u7ec3<\/h4>\n<p>EAGLE \u4e2d\u7684\u8349\u7a3f\u6a21\u578b\u7684\u8f93\u5165\u662f\u76ee\u6807\u6a21\u578b\u7684\u9876\u5c42\u7279\u5f81 <span class=\"katex-eq\" data-katex-display=\"false\"> f_{1}, f_{2}, \\cdots, f_{t}<\/span>, \u6216\u8005\u81f3\u5c11\u8fd1\u4f3c\u4e8e\u9876\u5c42\u7279\u5f81\u3002\u76f8\u53cd\uff0cEAGLE-3 \u8349\u6848\u6a21\u578b\u7684\u8f93\u5165\u53ef\u80fd\u5305\u62ec\u6765\u81ea\u76ee\u6807\u6a21\u578b\u7684\u7279\u6027 <span class=\"katex-eq\" data-katex-display=\"false\"> g_{1}, g_{2}, \\cdots, g_{t}<\/span>, \u4e5f\u53ef\u80fd\u5305\u62ec\u6765\u81ea\u8349\u6848\u6a21\u578b\u7684\u8f93\u51fa <span class=\"katex-eq\" data-katex-display=\"false\"> a_{t+1}, a_{t+2} \\cdots, a_{t+j}<\/span>\u3002\u56e0\u6b64\uff0c\u6211\u4eec\u9700\u8981\u8bad\u7ec3\u8349\u6848\u6a21\u578b\u4ee5\u9002\u5e94\u4e0d\u540c\u7684\u8f93\u5165\u3002\u5728\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\uff0c\u6211\u4eec\u6267\u884c\u6d4b\u8bd5\u6b65\u9aa4\uff0c\u5728\u8fd9\u91cc\u6211\u4eec\u751f\u6210 a \u5e76\u5c06\u5176\u53cd\u9988\u7ed9\u8349\u7a3f\u6a21\u578b\u4ee5\u8fdb\u884c\u8fdb\u4e00\u6b65\u8bad\u7ec3\u3002<br \/>\nEAGLE-3 \u8349\u6848\u6a21\u578b\u7684\u6838\u5fc3\u662f Transformer \u89e3\u7801\u5668\u5c42\u3002\u9664\u4e86\u81ea\u6ce8\u610f\u529b\u64cd\u4f5c\u5916\uff0c\u6ca1\u6709\u5176\u4ed6\u7ec4\u4ef6\u4e0e\u4e0a\u4e0b\u6587\u4ea4\u4e92\uff0c\u56e0\u6b64\u5728\u8bad\u7ec3\u6216\u6d4b\u8bd5\u671f\u95f4\u4e0d\u9700\u8981\u8fdb\u4e00\u6b65\u4fee\u6539\u3002\u552f\u4e00\u9700\u8981\u7a0d\u5fae\u4fee\u6539\u7684\u7ec4\u4ef6\u662f self-attention, \u6211\u4eec\u5c06\u5728\u4e0b\u9762\u8be6\u7ec6\u63cf\u8ff0\u3002<br \/>\n\u867d\u7136\u5b9e\u9645\u8f93\u5165\u7531\u7279\u5f81\u7ec4\u6210\uff0c\u4f46\u4e3a\u6e05\u6670\u8d77\u89c1\uff0c\u6211\u4eec\u4f7f\u7528\u6807\u8bb0\u4f5c\u4e3a\u8f93\u5165\u6765\u63cf\u8ff0\u8fd9\u4e2a\u8fc7\u7a0b\u3002\u5982\u56fe 6 \u6240\u793a\uff0c\u539f\u59cb\u8bad\u7ec3\u6570\u636e\u662f\u4e00\u4e2a\u957f\u5ea6\u4e3a 3 \u7684\u5e8f\u5217\uff0c\u2018How can I\u2019, \u5728\u4e0a\u4e0b\u6587\u4e2d\u5177\u6709\u6b63\u5e38\u7684\u5e8f\u5217\u4f9d\u8d56\u5173\u7cfb\u3002\u56e0\u6b64\uff0c\u6ce8\u610f\u529b\u6a21\u677f\u662f\u4e00\u4e2a\u6807\u51c6\u7684\u4e0b\u4e09\u89d2\u77e9\u9635\u3002\u5728\u4e09\u4e2a\u4f4d\u7f6e\u7684\u8f93\u51fa\u662f \u201care\u201d\u3001\u201cwe\u201d \u548c \u201cdo\u201d, \u5b83\u4eec\u4e0e \u201chow\u201d\u3001\u201ccan\u201d \u548c \u201cI\u201d \u5177\u6709\u6811\u72b6\u7684\u4e0a\u4e0b\u6587\u5173\u7cfb\u3002\u56e0\u6b64\uff0c\u5f53\u8f93\u5165 \u201care\u201d\u3001\u201cwe\u201d\u3001\u201cdo\u201d \u8fdb\u5165\u6b65\u9aa4 2 \u65f6\uff0c\u6ce8\u610f\u529b\u63a9\u7801\u9700\u8981\u8fdb\u884c\u76f8\u5e94\u7684\u8c03\u6574\uff0c\u5982\u56fe 6 \u53f3\u4e0a\u89d2\u6240\u793a\u3002\u9664\u4e86\u4f7f\u7528\u539f\u59cb\u8bad\u7ec3\u6570\u636e\u4f5c\u4e3a\u952e\u5916\uff0c\u6240\u6709\u7684\u6ce8\u610f\u529b\u63a9\u7801\u90fd\u662f\u5bf9\u89d2\u7ebf\u7684\u3002\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\u4f7f\u7528\u77e9\u9635\u4e58\u6cd5\u4f1a\u5bfc\u81f4\u663e\u8457\u7684\u8ba1\u7b97\u6d6a\u8d39\uff0c\u56e0\u6b64\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u5411\u91cf\u70b9\u79ef\u6765\u8ba1\u7b97\u5bf9\u5e94\u4f4d\u7f6e\u7684\u6ce8\u610f\u529b\u5f97\u5206\u3002<br \/>\n<img decoding=\"async\" src=\"https:\/\/youpaiyun.lingbo.online\/2026\/06\/20260601092052931.jpg\" alt=\"\" \/><\/p>\n<p><center> \u56fe6\uff1a\u8bad\u7ec3\u65f6\u6d4b\u8bd5\u8fc7\u7a0b\u4e2d\u7684\u6ce8\u610f\u529b\u56e0\u679c\u63a9\u7801\u793a\u610f\u56fe\u3002\u56fe\u4e2d\u4f9d\u6b21\u5c55\u793a\u5e38\u89c4\u8bad\u7ec3\u6b65\u9aa4\uff08\u7b2c\u4e00\u6b65\uff09\u4e0e\u4e24\u6b65\u6a21\u62df\u8bad\u7ec3\u6b65\u9aa4\uff08\u7b2c\u4e8c\u6b65\u3001\u7b2c\u4e09\u6b65\uff09\u3002\u8bcd\u5143\u4e4b\u95f4\u7684\u7bad\u5934\u4ee3\u8868\u4e0a\u4e0b\u6587\u5173\u8054\u5173\u7cfb\u3002\u7070\u8272\u8bcd\u5143\u4e3a\u8bad\u7ec3\u6570\u636e\uff0c\u84dd\u8272\u8bcd\u5143\u3001\u9ec4\u8272\u8bcd\u5143\u5206\u522b\u5bf9\u5e94\u8349\u7a3f\u6a21\u578b\u7b2c\u4e00\u8f6e\u3001\u7b2c\u4e8c\u8f6e\u7684\u9884\u6d4b\u7ed3\u679c\u3002 <\/center><\/p>\n<p>HASS (Zhang et al., 2024) \u548c EAGLE-3 \u90fd\u5bf9\u6ce8\u610f\u529b\u673a\u5236\u8fdb\u884c\u4e86\u7c7b\u4f3c\u7684\u4fee\u6539\uff0c\u4ee5\u6a21\u62df\u8bad\u7ec3\u671f\u95f4\u7684\u6d4b\u8bd5\u8fc7\u7a0b\uff0c\u4f46\u8fd9\u4e0d\u662f EAGLE-3 \u7684\u4e3b\u8981\u91cd\u70b9\u3002\u4e24\u79cd\u65b9\u6cd5\u7684\u52a8\u673a\u3001\u65b9\u6cd5\u548c\u7ed3\u679c\u622a\u7136\u4e0d\u540c\u3002HASS \u80cc\u540e\u7684\u52a8\u673a\u662f\u51cf\u5c11 EAGLE \u4e2d\u4e0d\u51c6\u786e\u7684\u7279\u5f81\u9884\u6d4b\u9020\u6210\u7684\u8bef\u5dee\u7d2f\u79ef\u3002HASS \u4ecd\u7136\u6267\u884c\u7279\u5f81\u9884\u6d4b\uff0c\u5305\u62ec\u7279\u5f81\u9884\u6d4b\u635f\u5931 <span class=\"katex-eq\" data-katex-display=\"false\"> l_{\\text {fea}}<\/span>, \u5e76\u4e14\u8349\u6848\u6a21\u578b\u7684\u8f93\u5165\u5fc5\u987b\u662f\u9876\u5c42\u7279\u5f81\u3002\u76f8\u6bd4\u4e4b\u4e0b\uff0cEAGLE-3 \u80cc\u540e\u7684\u52a8\u673a\u662f\u6d88\u9664\u4e0d\u5fc5\u8981\u7684\u7ea6\u675f\uff0c\u4ee5\u589e\u5f3a\u6a21\u578b\u7684\u8868\u8fbe\u80fd\u529b\u3002EAGLE-3 \u4e0d\u518d\u9700\u8981\u8349\u6848\u6a21\u578b\u7684\u8f93\u51fa\u6765\u62df\u5408\u76ee\u6807\u6a21\u578b\u7684\u9876\u5c42\u7279\u5f81\uff0c\u4ece\u800c\u907f\u514d\u4e86\u8bef\u5dee\u7d2f\u79ef\u3002\u53bb\u9664\u7279\u5f81\u9884\u6d4b\u540e\uff0cEAGLE-3 \u7684\u8f93\u5165\u662f\u5b8c\u5168\u81ea\u7531\u7684\uff0c\u53d6\u800c\u4ee3\u4e4b\u7684\u662f\u6765\u81ea\u4e0d\u540c\u5c42\u6b21\u8bed\u4e49\u4fe1\u606f\u7684\u7279\u5f81\u878d\u5408\u3002\u7279\u5f81\u9884\u6d4b\u635f\u5931\u7684\u53bb\u9664\u8fd8\u4f7f\u6211\u4eec\u80fd\u591f\u53d1\u73b0\u4ee5\u524d\u4ece\u672a\u53d1\u73b0\u8fc7\u7684\u65b0\u7684\u63a8\u7406\u52a0\u901f\u7684\u5c3a\u5ea6\u5f8b\u3002\u56fe 2 \u8fd8\u663e\u793a\u4e86 EAGLE-3 \u548c HASS \u7684\u52a0\u901f\u6bd4\uff0c\u5176\u4e2d EAGLE-3 \u8868\u73b0\u51fa\u4e86\u660e\u663e\u66f4\u597d\u7684\u6027\u80fd\u3002<br \/>\n<img decoding=\"async\" src=\"https:\/\/youpaiyun.lingbo.online\/2026\/06\/20260601093051194.jpg\" alt=\"\" \/><\/p>\n<p><center> \u56fe2\uff1a\u6e29\u5ea6\u7cfb\u6570<span class=\"katex-eq\" data-katex-display=\"false\">t=0<\/span>\u65f6\u4e0d\u540c\u65b9\u6cd5\u7684\u52a0\u901f\u6bd4\u3002\u6807\u51c6\u63a8\u6d4b\u91c7\u6837\u65b9\u6848\u4e2d\uff0cVicuna-13B \u4ee5 Vicuna-68M \u4f5c\u4e3a\u8349\u7a3f\u6a21\u578b\u3002\u88681\u5bf9\u6bd4\u4e86\u66f4\u591a\u65b9\u6cd5\uff0c\u672c\u56fe\u4ec5\u5c55\u793a\u5176\u4e2d\u4e00\u90e8\u5206\u3002\u5bf9\u8bdd\u6a21\u578b\u57fa\u4e8e MT-bench \u6570\u636e\u96c6\u5f00\u5c55\u8bc4\u6d4b\uff0c\u63a8\u7406\u6a21\u578b\u57fa\u4e8e GSM8K \u6570\u636e\u96c6\u5f00\u5c55\u8bc4\u6d4b\u3002DeepSeek R1 LLaMA 8B \u6307\u4ee3 DeepSeek-R1-Distill-LLaMA 8B\u3002 <\/center><\/p>\n<h3>\u5b9e\u9a8c<\/h3>\n<p>\u6a21\u578b\u3002\u4f7f\u7528\u6700\u5148\u8fdb\u7684\u5f00\u6e90\u804a\u5929\u548c\u63a8\u7406\u6a21\u578b\u8fdb\u884c\u4e86\u5b9e\u9a8c\uff0c\u5305\u62ec Vicuna 13B (Chiang et al., 2023)\u3001LLaMA-Instruct 3.1 8B\u3001LLaMA-Instruct 3.3 70B (Dubey et al., 2024) \u548c DeepSeek-R1-Distill-LLaMA 8B (Chen et al., 2021)\u3002\u7531\u4e8e GPU \u7684\u9650\u5236\uff0c\u6211\u4eec\u65e0\u6cd5\u5728 405B \u548c 671B \u6a21\u578b\u4e0a\u6d4b\u8bd5 EAGLE-3\u3002<br \/>\n\u4efb\u52a1\u3002\u5728 EAGLE (Li et al., 2024c) \u548c SpecBench (Xia et al., 2024) \u4e4b\u540e\uff0c\u5bf9\u4e94\u4e2a\u5e38\u89c1\u4efb\u52a1\u8fdb\u884c\u8bc4\u4f30\uff0c\u5bf9\u6240\u6709\u4efb\u52a1\u4f7f\u7528\u76f8\u540c\u7684\u6743\u91cd\uff0c\u800c\u4e0d\u5bf9\u5404\u81ea\u7684\u4efb\u52a1\u8fdb\u884c\u5fae\u8c03\u3002\u5bf9\u4e8e\u591a\u8f6e\u5bf9\u8bdd\u3001\u4ee3\u7801\u751f\u6210\u3001\u6570\u5b66\u63a8\u7406\u3001\u6307\u4ee4\u9075\u5faa\u548c\u603b\u7ed3\uff0c\u6211\u4eec\u5206\u522b\u9009\u62e9\u4e86 MT-bench (Zheng et al., 2023), HumanEval, GSM8K (Cobbe et al., 2021), Alpaca (Taori et al., 2023) \u548c CNN\/Daily Mail (Nallapati et al., 2016) \u6570\u636e\u96c6\u3002<br \/>\n\u6307\u6807\u3002EAGLE-3 \u4e0d\u4fee\u6539\u76ee\u6807\u6a21\u578b\u7684\u6743\u91cd\uff0c\u5e76\u4f7f\u7528\u4e25\u683c\u7684\u63a8\u6d4b\u91c7\u6837\u63a5\u53d7\u6761\u4ef6\uff0c\u786e\u4fdd\u4e0d\u635f\u5931\u6027\u80fd\u3002\u56e0\u6b64\uff0c\u6211\u4eec\u4e0d\u8bc4\u4f30\u751f\u6210\u8d28\u91cf\u3002\u76f8\u53cd\uff0c\u6211\u4eec\u4f7f\u7528\u4ee5\u4e0b\u6307\u6807\u6765\u8bc4\u4f30\u52a0\u901f\u6027\u80fd:<\/p>\n<ul>\n<li>\u52a0\u901f\u6bd4\uff08Speedup Ratio\uff09\uff1a\u76f8\u5bf9\u4e8e\u666e\u901a\u81ea\u56de\u5f52\u89e3\u7801\u7684\u5b9e\u9645\u6d4b\u8bd5\u52a0\u901f\u6bd4\u3002<\/li>\n<li>\u5e73\u5747\u63a5\u53d7\u957f\u5ea6\uff08Average Acceptance Length\uff09\u03c4: \u6bcf\u4e2a\u8d77\u8349 - \u9a8c\u8bc1\u5468\u671f\u751f\u6210\u7684\u4ee4\u724c\u7684\u5e73\u5747\u6570\u91cf\uff0c\u5b83\u5bf9\u5e94\u4e8e\u4ece\u8349\u6848\u4e2d\u63a5\u53d7\u7684\u4ee4\u724c\u6570\u91cf\u3002<\/li>\n<li>\u63a5\u53d7\u7387\uff08Acceptance Rate\uff09n-\u03b1: \u8349\u7a3ftoken\u88ab\u63a5\u53d7\u7684\u6bd4\u4f8b\u76f4\u63a5\u53cd\u6620\u4e86\u8349\u7a3f\u6a21\u578b\u4e0e\u76ee\u6807\u6a21\u578b\u7684\u8fd1\u4f3c\u7a0b\u5ea6\u3002\u6309\u7167 EAGLE \u7684\u8bbe\u7f6e\uff0c\u6211\u4eec\u5728\u6d4b\u8bd5\u63a5\u53d7\u7387\u65f6\u4f7f\u7528\u94fe\u5f0f\u8349\u7a3f\u800c\u4e0d\u662f\u6811\u5f62\u8349\u7a3f\u3002EAGLE \u53d7\u5230\u8bef\u5dee\u7d2f\u79ef\u7684\u56f0\u6270\uff0c\u8fd9\u610f\u5473\u7740\u8349\u6848\u6a21\u578b\u7684\u8f93\u5165\u53ef\u80fd\u662f\u5b83\u81ea\u5df1\u7684\u4f30\u8ba1\uff0c\u800c\u4e0d\u662f\u6765\u81ea\u76ee\u6807\u6a21\u578b\u7684\u51c6\u786e\u503c\u3002\u56e0\u6b64\uff0cEAGLE \u4f7f\u7528 n-\u03b1 \u8868\u793a\u8f93\u5165\u5305\u542b n \u4f30\u8ba1\u7279\u5f81\u65f6\u7684\u63a5\u53d7\u7387\uff0c\u524d\u63d0\u662f\u5148\u524d\u4f30\u8ba1\u7684 token \u90fd\u88ab\u76ee\u6807\u6a21\u578b\u63a5\u53d7\u3002\u6362\u53e5\u8bdd\u8bf4\uff0c\u8f93\u5165\u7684\u63a5\u53d7\u7387 <span class=\"katex-eq\" data-katex-display=\"false\"> f_{1}, f_{2}, \\cdots, f_{i}, \\hat {f}{i+1}, \\cdots, \\hat{f}{i+n}<\/span>, \u5176\u4e2d f \u662f\u51c6\u786e\u503c\uff0c<span class=\"katex-eq\" data-katex-display=\"false\">\\hat {f}<\/span> \u662f\u6a21\u578b\u8349\u6848\u7684\u4f30\u8ba1\u3002\u7c7b\u4f3c\u5730\u5f53\u8f93\u5165\u5305\u542b n \u81ea\u9884\u6d4b\u503c a \u65f6\uff0c\u6211\u4eec\u4f7f\u7528 n-\u03b1 \u6765\u8868\u793a EAGLE-3 \u4e2d\u7684\u63a5\u53d7\u7387\uff0c\u5373\u8f93\u5165\u7684\u63a5\u53d7\u7387 <span class=\"katex-eq\" data-katex-display=\"false\"> g_{1}, g_{2}, \\cdots, g_{i}, a_{i+1}, \\cdots, a_{i+n}<\/span>, \u5176\u4e2d g \u662f\u6765\u81ea\u76ee\u6807\u6a21\u578b\u7684\u878d\u5408\u7279\u5f81\u3002<br \/>\n\u5b9e\u73b0\u3002\u6211\u4eec\u4f7f\u7528 AdamW \u4f18\u5316\u5668\uff0cbeta \u503c <span class=\"katex-eq\" data-katex-display=\"false\">(\\beta_{1}, \\beta_{2})<\/span> \u8bbe\u7f6e\u4e3a (0.9,0.95) \u5e76\u5b9e\u73b0\u68af\u5ea6\u88c1\u526a\u4e3a 0.5\u3002\u5b66\u4e60\u7387\u8bbe\u7f6e\u4e3a 5e-5\u3002\u6211\u4eec\u4f7f\u7528 ShareGPT \u548c UltraChat-200K (Ding et al., 2023) \u4f5c\u4e3a\u8bad\u7ec3\u6570\u636e\uff0c\u5206\u522b\u5305\u542b\u5927\u7ea6 68K \u548c 464K \u6570\u636e\u9879\u3002\u6211\u4eec\u8c03\u7528\u76ee\u6807\u6a21\u578b\u6765\u751f\u6210\u54cd\u5e94\uff0c\u800c\u4e0d\u662f\u4f7f\u7528\u56fa\u5b9a\u7684\u6570\u636e\u96c6\u3002\u5bf9\u4e8e\u63a8\u7406\u6a21\u578b DeepSeek-R1-Distill-LLaMA 8B, \u6211\u4eec\u8fd8\u4f7f\u7528 OpenThoughts-114k-math \u6570\u636e\u96c6\u8fdb\u884c\u8bad\u7ec3\u3002<br \/>\n\u6bd4\u8f83\u3002\u6211\u4eec\u4f7f\u7528\u666e\u901a\u7684\u81ea\u56de\u5f52\u89e3\u7801\u4f5c\u4e3a\u57fa\u51c6\uff0c\u5b83\u4f5c\u4e3a\u52a0\u901f\u6bd4\u7684\u57fa\u51c6 (1.00x)\u3002\u6211\u4eec\u5c06 EAGLE-3 \u4e0e\u6700\u8fd1\u7684\u65e0\u635f\u63a8\u6d4b\u91c7\u6837\u65b9\u6cd5\u8fdb\u884c\u4e86\u6bd4\u8f83\uff0c\u5305\u62ec\u6807\u51c6\u63a8\u6d4b\u91c7\u6837 (Leviathan et al., 2023; Chen et al., 2023; Gante, 2023), PLD (Saxena, 2023), Medusa (Cai et al., 2024), Lookahead (Fu et al., 2024), Hydra (Ankner et al., 2024), HASS (Zhang et al., 2024), EAGLE (Li et al., 2024c), \u548c EAGLE-2 (Li et al., 2024b)\u3002<\/li>\n<\/ul>\n<h4>\u6709\u6548\u6027<\/h4>\n<p>\u56fe 1 \u548c\u8868 1 \u5c55\u793a\u4e86 EAGLE-3 \u7684\u52a0\u901f\u6027\u80fd\u3002\u5728\u6240\u6709\u4efb\u52a1\u548c\u76ee\u6807\u6a21\u578b\u4e0a\uff0cEAGLE-3 \u5b9e\u73b0\u4e86\u6700\u9ad8\u7684\u52a0\u901f\u6bd4\u548c\u5e73\u5747\u63a5\u53d7\u957f\u5ea6\u3002\u4e0e vanilla \u81ea\u56de\u5f52\u751f\u6210\u76f8\u6bd4\uff0cEAGLE-3 \u63d0\u4f9b\u4e86\u5927\u7ea6 3.0x-6.5 \u500d\u7684\u52a0\u901f\uff0c\u6bd4 EAGLE-2 \u63d0\u9ad8\u4e86 20%-40%\u3002\u4e0d\u540c\u7684\u4efb\u52a1\u4f1a\u5f71\u54cd\u8349\u6848\u6a21\u578b\u7684\u63a5\u53d7\u7387\uff0c\u56e0\u6b64\u5e73\u5747\u63a5\u53d7\u957f\u5ea6\u548c\u52a0\u901f\u6bd4\u90fd\u662f\u4e0e\u4efb\u52a1\u76f8\u5173\u7684\u3002\u7531\u4e8e\u5728\u4ee3\u7801\u751f\u6210\u4efb\u52a1\u4e2d\u5b58\u5728\u8bb8\u591a\u56fa\u5b9a\u6a21\u677f\uff0c\u751f\u6210\u8349\u7a3f\u662f\u6700\u7b80\u5355\u7684\uff0c\u8fd9\u5c31\u662f\u4e3a\u4ec0\u4e48 EAGLE-3 \u5728 HumanEval \u4e0a\u8868\u73b0\u6700\u597d\u7684\u539f\u56e0\uff0c\u5b9e\u73b0\u4e86\u9ad8\u8fbe 6.5 \u500d\u7684\u52a0\u901f\u6bd4\u548c\u9ad8\u8fbe 7.5 \u7684\u5e73\u5747\u63a5\u53d7\u957f\u5ea6\u3002DeepSeek-R1-Distill-LLaMA 8B \u662f\u4e2a\u4f8b\u5916\uff0c\u5728\u6570\u5b66\u63a8\u7406\u6570\u636e\u96c6 GSM8K \u4e0a\u5177\u6709\u6700\u9ad8\u7684\u52a0\u901f\u6bd4\u3002\u8fd9\u53ef\u80fd\u662f\u56e0\u4e3a\u6211\u4eec\u4f7f\u7528 OpenThoughts-114k-math \u6570\u636e\u96c6\u8bad\u7ec3\u4e86 DeepSeek-R1-Distill-LLaMA 8B \u7684\u6a21\u578b\u8349\u6848\u3002<br \/>\n<img decoding=\"async\" src=\"https:\/\/youpaiyun.lingbo.online\/2026\/06\/20260601093834570.jpg\" alt=\"\" \/><\/p>\n<p><center> \u56fe1\uff1a\u4ee5 LLaMA-Instruct 3.1 8B \u4f5c\u4e3a\u76ee\u6807\u6a21\u578b\uff0c\u5728 MT-bench \u6570\u636e\u96c6\u4e0a\u6d4b\u5f97\u7684\u7f29\u653e\u89c4\u5f8b\u66f2\u7ebf\uff0c\u6a2a\u8f74\u4e3a\u76f8\u5bf9 ShareGPT \u7684\u6570\u636e\u96c6\u89c4\u6a21\u3002EAGLE-3 \u5168\u65b0\u7684\u67b6\u6784\u8bbe\u8ba1\u8ba9\u7f29\u653e\u66f2\u7ebf\u5448\u73b0\u6301\u7eed\u4e0a\u5347\u8d8b\u52bf\uff0c\u8fd9\u4e00\u73b0\u8c61\u5728\u4ee5\u5f80\u76f8\u5173\u7814\u7a76\u4e2d\u4ece\u672a\u51fa\u73b0\u3002 <\/center><br \/>\n<center> \u88681\uff1a\u4e0d\u540c\u65b9\u6cd5\u7684\u52a0\u901f\u6bd4\u4e0e\u5e73\u5747\u63a5\u53d7\u957f\u5ea6<span class=\"katex-eq\" data-katex-display=\"false\">\\tau<\/span>\u3002V \u4ee3\u8868 Vicuna\uff0cL31 \u4ee3\u8868 LLaMA-Instruct 3.1\uff0cL33 \u4ee3\u8868 LLaMA-Instruct 3.3\uff0cDSL \u4ee3\u8868 DeepSeek-R1-Distill-LLaMA\u3002SpS \u4e3a\u6807\u51c6\u63a8\u6d4b\u91c7\u6837\uff0c\u5176\u8349\u7a3f\u6a21\u578b\u91c7\u7528 Vicuna-68M\u3002Medusa \u7b49\u65b9\u6cd5\u5728\u975e\u8d2a\u5fc3\u89e3\u7801\u573a\u666f\u4e0b\u653e\u5bbd\u4e86\u63a5\u53d7\u6761\u4ef6\uff0c\u65e0\u6cd5\u4fdd\u8bc1\u65e0\u635f\u52a0\u901f\uff0c\u56e0\u6b64\u5728\u6e29\u5ea6\u7cfb\u6570<span class=\"katex-eq\" data-katex-display=\"false\">t=1<\/span>\u7684\u5b9e\u9a8c\u4e2d\uff0c\u672c\u6587\u672a\u5c06 EAGLE-3 \u4e0e\u8fd9\u7c7b\u65b9\u6cd5\u8fdb\u884c\u5bf9\u6bd4\u3002 <\/center><\/p>\n<p><img decoding=\"async\" src=\"https:\/\/youpaiyun.lingbo.online\/2026\/06\/20260601094050795.jpg\" alt=\"\" \/><br \/>\n\u56fe 7 \u663e\u793a\u4e86\u4ee5 LLaMA-Instruct 3.1 8B \u4e3a\u76ee\u6807\u6a21\u578b\u7684 EAGLE \u548c EAGLE-3 \u5728 MT-bench \u4e0a\u7684\u63a5\u53d7\u7387\u3002EAGLE-3 \u7684\u5f55\u53d6\u7387\u663e\u8457\u9ad8\u4e8e EAGLE\u3002\u968f\u7740\u8349\u6848\u6a21\u578b\u672c\u8eab\u7684\u8f93\u5165\u589e\u52a0\uff0cEAGLE \u7684\u63a5\u53d7\u7387\u663e\u8457\u4e0b\u964d\uff0c\u800c EAGLE-3 \u7684\u63a5\u53d7\u7387\u51e0\u4e4e\u4fdd\u6301\u4e0d\u53d8\uff0c\u8bc1\u660e\u4e86\u8bad\u7ec3\u65f6\u95f4\u6d4b\u8bd5\u7684\u6709\u6548\u6027\u3002<br \/>\n<img decoding=\"async\" src=\"https:\/\/youpaiyun.lingbo.online\/2026\/06\/20260601094209677.jpg\" alt=\"\" \/><\/p>\n<p><center> \u56fe7\uff1aEAGLE \u4e0e EAGLE-3 \u5728 MT-bench \u6570\u636e\u96c6\u4e0a\u7684\u63a5\u53d7\u7387\uff0c\u76ee\u6807\u6a21\u578b\u4e3a LLaMA-Instruct 3.1 8B\u3002\u5176\u4e2d <span class=\"katex-eq\" data-katex-display=\"false\">n\\text{-}\\alpha<\/span> \u8868\u793a\uff1a\u5f53\u8f93\u5165\u5305\u542b <span class=\"katex-eq\" data-katex-display=\"false\">n<\/span> 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