{"id":5654,"date":"2025-02-19T16:56:14","date_gmt":"2025-02-19T08:56:14","guid":{"rendered":"https:\/\/nullthought.net\/?p=5654"},"modified":"2025-02-19T16:56:16","modified_gmt":"2025-02-19T08:56:16","slug":"%e9%87%87%e7%94%a8%e9%9d%9e%e5%af%b9%e7%a7%b0%e6%95%b0%e5%ad%97%e7%b3%bb%e7%bb%9f%ef%bc%88ans%ef%bc%89%e5%92%8c%e6%b3%a2%e5%88%97%e6%a0%91%ef%bc%88wavelet-trees%ef%bc%89%e7%9a%84%e6%97%a0%e6%8d%9f","status":"publish","type":"post","link":"https:\/\/nullthought.net\/?p=5654","title":{"rendered":"\u91c7\u7528\u975e\u5bf9\u79f0\u6570\u5b57\u7cfb\u7edf\uff08ANS\uff09\u548c\u6ce2\u5217\u6811\uff08Wavelet Trees\uff09\u7684\u65e0\u635f\u538b\u7f29\u65b9\u6cd5\uff0c\u5bf9\u8fd1\u4f3c\u6700\u8fd1\u90bb\u641c\u7d22\uff08ANNS\uff09\u4e2d\u7684\u5411\u91cfID\u548c\u56fe\u7ed3\u6784\u8fdb\u884c\u4f18\u5316"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">\u8bba\u6587<strong><a href=\"https:\/\/arxiv.org\/abs\/2501.10479\" target=\"_blank\" rel=\"noreferrer noopener\">Lossless Compression of Vector IDs for Approximate Nearest Neighbor Search<\/a><\/strong>\u63d0\u51fa\u4e86\u4e00\u79cd\u57fa\u4e8e\u975e\u5bf9\u79f0\u6570\u5b57\u7cfb\u7edf\uff08ANS\uff09\u548c\u6ce2\u5217\u6811\u7684\u65e0\u635f\u538b\u7f29\u65b9\u6cd5\uff0c\u4e13\u95e8\u9488\u5bf9\u8fd1\u4f3c\u6700\u8fd1\u90bb\u641c\u7d22\u4e2d\u7684\u5411\u91cfID\u548c\u56fe\u7ed3\u6784\u8fdb\u884c\u4f18\u5316\u3002\u901a\u8fc7\u65e0\u635f\u538b\u7f29\uff0c\u4f5c\u8005\u5728\u4fdd\u8bc1\u68c0\u7d22\u7cbe\u5ea6\u548c\u641c\u7d22\u6548\u7387\u7684\u524d\u63d0\u4e0b\uff0c\u663e\u8457\u51cf\u5c11\u4e86\u5b58\u50a8\u548c\u4f20\u8f93\u5f00\u9500\u3002\u5b9e\u9a8c\u7ed3\u679c\u9a8c\u8bc1\u4e86\u6240\u63d0\u51fa\u7684\u65b9\u6cd5\u80fd\u591f\u5728\u591a\u4e2a\u6570\u636e\u96c6\u4e0a\u53d6\u5f97\u826f\u597d\u7684\u538b\u7f29\u6548\u679c\uff0c\u5e76\u5bf9\u672a\u6765\u5728\u8be5\u9886\u57df\u7684\u7814\u7a76\u63d0\u51fa\u4e86\u82e5\u5e72\u5efa\u8bae\u3002<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">\u8bba\u6587\u4f5c\u8005\u4e3aDaniel Severo, Giuseppe Ottaviano, Matthew Muckley, Karen Ullrich, Matthijs Douze\uff0c\u5747\u6765\u81eaMeta\u3002<\/p>\n\n\n\n<figure class=\"wp-block-image aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"662\" height=\"646\" src=\"https:\/\/nullthought.net\/wp-content\/uploads\/2025\/02\/image-10.png\" alt=\"\" class=\"wp-image-5655\" srcset=\"https:\/\/nullthought.net\/wp-content\/uploads\/2025\/02\/image-10.png 662w, https:\/\/nullthought.net\/wp-content\/uploads\/2025\/02\/image-10-300x293.png 300w\" sizes=\"auto, (max-width: 662px) 100vw, 662px\" \/><figcaption class=\"wp-element-caption\"><strong><a href=\"https:\/\/arxiv.org\/abs\/2501.10479\" target=\"_blank\" rel=\"noreferrer noopener\">Lossless Compression of Vector IDs for Approximate Nearest Neighbor Search<\/a><\/strong><\/figcaption><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>\u4e00\u3001\u5f15\u8a00<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">\u8fd1\u4f3c\u6700\u8fd1\u90bb\u641c\u7d22\uff08Approximate Nearest Neighbor Search\uff0c\u7b80\u79f0ANNS\uff09\u5728\u5927\u89c4\u6a21\u6570\u636e\u68c0\u7d22\u4e2d\u626e\u6f14\u7740\u81f3\u5173\u91cd\u8981\u7684\u89d2\u8272\u3002\u5c24\u5176\u662f\u5728\u56fe\u50cf\u3001\u89c6\u9891\u7b49\u591a\u5a92\u4f53\u68c0\u7d22\u9886\u57df\uff0c\u968f\u7740\u6570\u636e\u91cf\u7684\u4e0d\u65ad\u589e\u957f\uff0c\u7cbe\u786e\u7684\u6700\u8fd1\u90bb\u641c\u7d22\u53d8\u5f97\u8fc7\u4e8e\u7f13\u6162\u3002\u4e3a\u4e86\u5e94\u5bf9\u8fd9\u4e00\u95ee\u9898\uff0c\u8bb8\u591a\u7814\u7a76\u8005\u63d0\u51fa\u4e86\u8fd1\u4f3c\u641c\u7d22\u7684\u65b9\u6cd5\uff0c\u8fd9\u4e9b\u65b9\u6cd5\u901a\u8fc7\u727a\u7272\u4e00\u4e9b\u51c6\u786e\u6027\u6765\u6362\u53d6\u66f4\u5feb\u7684\u68c0\u7d22\u901f\u5ea6\u3002\u4e3a\u4e86\u63d0\u9ad8\u641c\u7d22\u6548\u7387\uff0c\u901a\u5e38\u4f1a\u5bf9\u6570\u636e\u5e93\u4e2d\u7684\u5411\u91cf\u6570\u636e\u8fdb\u884c\u538b\u7f29\uff0c\u4ee5\u51cf\u5c11\u5b58\u50a8\u7a7a\u95f4\u548c\u4f20\u8f93\u5e26\u5bbd\u3002\u7136\u800c\uff0c\u5927\u90e8\u5206\u538b\u7f29\u65b9\u6cd5\u53ea\u5173\u6ce8\u5411\u91cf\u672c\u8eab\u7684\u538b\u7f29\uff0c\u800c\u5ffd\u7565\u4e86\u5411\u91cfID\uff08\u5373\u7528\u4e8e\u6307\u793a\u5411\u91cf\u5728\u6570\u636e\u5e93\u4e2d\u7684\u4f4d\u7f6e\u7684\u6807\u8bc6\u7b26\uff09\u548c\u56fe\u7ed3\u6784\u4e2d\u7684\u8fb9\u6570\u636e\u3002\u8fd9\u7bc7\u8bba\u6587\u7684\u4e3b\u8981\u8d21\u732e\u4e4b\u4e00\uff0c\u5c31\u662f\u63d0\u51fa\u4e86\u4e00\u79cd\u65e0\u635f\u538b\u7f29\u65b9\u6848\uff0c\u4e13\u95e8\u9488\u5bf9\u8fd9\u4e9bID\u548c\u56fe\u8fb9\u6570\u636e\u8fdb\u884c\u538b\u7f29\uff0c\u8fdb\u800c\u51cf\u5c0f\u6570\u636e\u5e93\u7684\u5b58\u50a8\u548c\u4f20\u8f93\u6210\u672c\u3002<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>\u4e8c\u3001\u76f8\u5173\u5de5\u4f5c<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">\u5728\u5411\u91cf\u538b\u7f29\u9886\u57df\uff0c\u8bb8\u591a\u7814\u7a76\u96c6\u4e2d\u4e8e\u91cf\u5316\uff08quantization\uff09\u6280\u672f\uff0c\u7528\u4e8e\u5c06\u8fde\u7eed\u7684\u5411\u91cf\u538b\u7f29\u6210\u79bb\u6563\u7684\u6574\u6570\u6216\u6bd4\u7279\u5e8f\u5217\u3002\u8fd9\u7c7b\u6280\u672f\u6709\u52a9\u4e8e\u51cf\u5c11\u5411\u91cf\u6bd4\u8f83\u6240\u9700\u7684\u8ba1\u7b97\u91cf\uff0c\u5e76\u5728\u4e00\u5b9a\u7a0b\u5ea6\u4e0a\u63d0\u9ad8\u641c\u7d22\u6548\u7387\u3002\u7ecf\u5178\u7684\u91cf\u5316\u65b9\u6cd5\u5305\u62ec\u77e2\u91cf\u91cf\u5316\uff08Vector Quantization\uff09\u3001\u4ea7\u54c1\u91cf\u5316\uff08Product 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