{"id":2933,"date":"2026-01-23T19:33:05","date_gmt":"2026-01-23T19:33:05","guid":{"rendered":"https:\/\/umaax.com\/damoxingruhezhunquedudongtubiaoyiwenkandong\/"},"modified":"2026-01-23T19:33:05","modified_gmt":"2026-01-23T19:33:05","slug":"damoxingruhezhunquedudongtubiaoyiwenkandong","status":"publish","type":"post","link":"https:\/\/umaax.com\/en\/damoxingruhezhunquedudongtubiaoyiwenkandong\/","title":{"rendered":"\u5927\u6a21\u578b\u5982\u4f55\u51c6\u786e\u8bfb\u61c2\u56fe\u8868\uff1f\u4e00\u6587\u770b\u61c2"},"content":{"rendered":"<p>\u5728\u6570\u636e\u9a71\u52a8\u7684\u65f6\u4ee3\uff0c\u56fe\u8868\u5df2\u6210\u4e3a\u4fe1\u606f\u4f20\u9012\u7684\u6838\u5fc3\u5a92\u4ecb\u3002\u8ba9\u673a\u5668\u771f\u6b63\u201d\u8bfb\u61c2\u201d\u56fe\u8868\u2014\u2014\u4e0d\u4ec5\u8bc6\u522b\u56fe\u5f62\u5143\u7d20\uff0c\u66f4\u8981\u7406\u89e3\u6570\u636e\u903b\u8f91\u3001\u6d1e\u5bdf\u8d8b\u52bf\u89c4\u5f8b\u3001\u56de\u7b54\u590d\u6742\u95ee\u9898\u2014\u2014\u4e00\u76f4\u662f\u4eba\u5de5\u667a\u80fd\u9886\u57df\u7684\u91cd\u5927\u6311\u6218\u3002\u4f20\u7edf\u65b9\u6cd5\u4f9d\u8d56OCR\uff08\u5149\u5b66\u5b57\u7b26\u8bc6\u522b\uff09\u548c\u89c4\u5219\u5f15\u64ce\uff0c\u6d41\u7a0b\u7e41\u7410\u4e14\u9c81\u68d2\u6027\u5dee\u30022023\u5e74\u4ee5\u6765\uff0c\u968f\u7740GPT-4V\u3001Gemini\u7b49\u591a\u6a21\u6001\u5927\u6a21\u578b\u7684\u5d1b\u8d77\uff0c\u56fe\u8868\u7406\u89e3\u6280\u672f\u8fce\u6765\u4e86\u9769\u547d\u6027\u7a81\u7834\u3002<\/p>\n<p>\u622a\u81f32025\u5e74\uff0c\u89c6\u89c9\u8bed\u8a00\u5927\u6a21\u578b\uff08Vision-Language Models, VLMs\uff09\u5df2\u80fd\u5b9e\u73b0\u7aef\u5230\u7aef\u7684\u56fe\u8868\u89e3\u6790\uff0c\u4ece\u50cf\u7d20\u7ea7\u89c6\u89c9\u611f\u77e5\u5230\u8bed\u4e49\u7ea7\u903b\u8f91\u63a8\u7406\uff0c\u5c55\u73b0\u51fa\u63a5\u8fd1\u4eba\u7c7b\u4e13\u5bb6\u7684\u7406\u89e3\u80fd\u529b\u3002\u672c\u6587\u5c06\u6df1\u5ea6\u62c6\u89e3\u8fd9\u4e00\u6280\u672f\u5947\u8ff9\u80cc\u540e\u7684\u5de5\u7a0b\u5b9e\u8df5\u4e0e\u79d1\u5b66\u539f\u7406\u3002<\/p>\n<p> <img fetchpriority=\"high\" decoding=\"async\" class=\"wp-image-66869 aligncenter\" src=\"https:\/\/ai-bot.cn\/wp-content\/uploads\/2025\/11\/ai-understand-charts.png\"  alt=\"\" width=\"718\" height=\"476\" \/> <\/p>\n<h2>\u6838\u5fc3\u6280\u672f\u6f14\u8fdb\uff1a\u4ece\u591a\u9636\u6bb5\u6d41\u6c34\u7ebf\u5230\u7aef\u5230\u7aef\u667a\u80fd<\/h2>\n<h3>\u4f20\u7edf\u65b9\u6cd5\u7684\u5c40\u9650\u6027<\/h3>\n<p>\u65e9\u671f\u56fe\u8868\u7406\u89e3\u7cfb\u7edf\u91c7\u7528\u6a21\u5757\u5316\u6d41\u6c34\u7ebf\uff1a\u5148\u901a\u8fc7OCR\u63d0\u53d6\u6587\u5b57\uff0c\u518d\u7528\u8ba1\u7b97\u673a\u89c6\u89c9\u68c0\u6d4b\u56fe\u5f62\u5143\u7d20\uff08\u5982\u67f1\u72b6\u56fe\u7684\u67f1\u5b50\u3001\u6298\u7ebf\u56fe\u7684\u7ebf\u6761\uff09\uff0c\u6700\u540e\u7531\u89c4\u5219\u5f15\u64ce\u5339\u914d\u903b\u8f91\u5173\u7cfb\u3002\u8fd9\u79cd\u67b6\u6784\u5b58\u5728\u4e09\u5927\u81f4\u547d\u7f3a\u9677\uff1a<\/p>\n<ul>\n<li><strong>\u8bef\u5dee\u7d2f\u79ef<\/strong>\uff1aOCR\u9519\u4e00\u4e2a\u5b57\uff0c\u540e\u7eed\u63a8\u7406\u5168\u76d8\u5d29\u6e83<\/li>\n<li><strong>\u6cdb\u5316\u80fd\u529b\u5dee<\/strong>\uff1a\u65b0\u56fe\u8868\u6837\u5f0f\u9700\u91cd\u5199\u89c4\u5219\uff0c\u7ef4\u62a4\u6210\u672c\u6781\u9ad8<\/li>\n<li><strong>\u65e0\u6cd5\u7406\u89e3\u6df1\u5c42\u8bed\u4e49<\/strong>\uff1a\u80fd\u63d0\u53d6\u6570\u5b57\uff0c\u4f46\u770b\u4e0d\u61c2\u201d\u540c\u6bd4\u589e\u957f\u663e\u8457\u201d\u80cc\u540e\u7684\u4e1a\u52a1\u542b\u4e49<\/li>\n<\/ul>\n<h3>\u7aef\u5230\u7aef\u5927\u6a21\u578b\u7684\u8303\u5f0f\u9769\u547d<\/h3>\n<p>2024-2025\u5e74\u7684\u4e3b\u6d41\u65b9\u6848\u91c7\u7528<strong>\u7edf\u4e00\u795e\u7ecf\u7f51\u7edc\u67b6\u6784<\/strong>\uff0c\u5c06\u89c6\u89c9\u7f16\u7801\u5668\u4e0e\u8bed\u8a00\u6a21\u578b\u6df1\u5ea6\u878d\u5408\uff0c\u5b9e\u73b0\u201d\u56fe\u50cf\u8fdb\u3001\u7b54\u6848\u51fa\u201d\u7684\u7aef\u5230\u7aef\u7406\u89e3\u3002\u5173\u952e\u6280\u672f\u7a81\u7834\u5305\u62ec\uff1a<\/p>\n<ul>\n<li><strong>\u89c6\u89c9-\u8bed\u8a00\u5bf9\u9f50<\/strong>\uff1a\u901a\u8fc7\u5927\u89c4\u6a21\u56fe\u6587\u5bf9\u9884\u8bad\u7ec3\uff0c\u8ba9\u6a21\u578b\u81ea\u52a8\u5b66\u4e60\u56fe\u8868\u5143\u7d20\u4e0e\u6570\u636e\u6982\u5ff5\u7684\u5bf9\u5e94\u5173\u7cfb<\/li>\n<li><strong>\u6307\u4ee4\u8ddf\u968f\u80fd\u529b<\/strong>\uff1a\u7528\u6237\u7528\u81ea\u7136\u8bed\u8a00\u63d0\u95ee\uff0c\u6a21\u578b\u76f4\u63a5\u751f\u6210\u7b54\u6848\u6216\u4ee3\u7801\uff0c\u65e0\u9700\u4e2d\u95f4\u7ed3\u6784\u5316\u6570\u636e<\/li>\n<li><strong>\u4e0a\u4e0b\u6587\u63a8\u7406<\/strong>\uff1a\u7ed3\u5408\u56fe\u8868\u6807\u9898\u3001\u5750\u6807\u8f74\u6807\u7b7e\u3001\u56fe\u4f8b\u7b49\u591a\u6a21\u6001\u4fe1\u606f\uff0c\u8fdb\u884c\u56e0\u679c\u63a8\u65ad\u4e0e\u8d8b\u52bf\u9884\u6d4b<\/li>\n<\/ul>\n<h2>\u4e3b\u6d41\u56fe\u8868\u7406\u89e3\u5927\u6a21\u578b<\/h2>\n<h3>\u7b2c\u4e00\u68af\u961f\uff1a\u95ed\u6e90\u5546\u4e1a\u5de8\u64d8<\/h3>\n<h4><strong>GPT-4V \/ GPT-4o (OpenAI)<\/strong><\/h4>\n<p>\u4f5c\u4e3a\u591a\u6a21\u6001\u5927\u6a21\u578b\u7684\u6807\u6746\uff0cGPT-4V\u91c7\u7528\u00a0<strong>\u6df7\u5408\u4e13\u5bb6\u67b6\u6784\uff08MoE\uff09<\/strong>\u200d \uff0c\u4f46\u5176\u6280\u672f\u7ec6\u8282\u672a\u5b8c\u5168\u516c\u5f00\u3002\u6839\u636e\u641c\u7d22\u7ed3\u679c\u5206\u6790\uff0c\u6838\u5fc3\u4f18\u52bf\u5728\u4e8e\uff1a<\/p>\n<ul>\n<li><strong>\u6280\u672f\u7279\u70b9<\/strong>\uff1a\n<ul>\n<li><strong>\u89c6\u89c9\u7f16\u7801\u5668<\/strong>\uff1a\u57fa\u4e8eCLIP\u7684\u53d8\u4f53\uff0c\u63d0\u53d6512\u7ef4\u89c6\u89c9\u7279\u5f81\u5411\u91cf\uff0c\u652f\u6301\u9ad8\u8fbe8192\u00d78192\u50cf\u7d20\u5206\u8fa8\u7387\u8f93\u5165<\/li>\n<li><strong>\u8bed\u8a00\u6a21\u578b<\/strong>\uff1aGPT-4\u57fa\u5ea7\uff0c\u53c2\u6570\u91cf\u4f30\u8ba1\u57281.8\u4e07\u4ebf\u5de6\u53f3\uff08MoE\u6fc0\u6d3b\u53c2\u6570\u7ea62200\u4ebf\uff09<\/li>\n<li><strong>\u8bad\u7ec3\u65b9\u6cd5<\/strong>\uff1a\u4e24\u9636\u6bb5\u8bad\u7ec3\u2014\u2014\u5148\u5728\u6570\u5341\u4ebf\u56fe\u6587\u5bf9\u4e0a\u5bf9\u9f50\u89c6\u89c9\u4e0e\u6587\u672c\u8868\u793a\uff0c\u518d\u901a\u8fc7\u5f3a\u5316\u5b66\u4e60\u4eba\u7c7b\u53cd\u9988\uff08RLHF\uff09\u4f18\u5316\u56fe\u8868\u63a8\u7406\u80fd\u529b<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u5173\u952e\u6280\u672f<\/strong>\uff1a\n<ul>\n<li><strong>\u601d\u7ef4\u94fe\uff08Chain-of-Thought\uff09<\/strong>\u200d \uff1a\u5bf9\u590d\u6742\u95ee\u9898\u81ea\u52a8\u5206\u89e3\u4e3a\u201d\u8bfb\u53d6\u6570\u636e\u2192\u8ba1\u7b97\u2192\u9a8c\u8bc1\u201d\u591a\u6b65\u63a8\u7406<\/li>\n<li><strong>\u4ee3\u7801\u751f\u6210\u80fd\u529b<\/strong>\uff1a\u53ef\u8f93\u51faPython\u4ee3\u7801\u590d\u73b0\u56fe\u8868\uff0c\u9a8c\u8bc1\u7406\u89e3\u51c6\u786e\u6027<\/li>\n<li><strong>\u8de8\u56fe\u8868\u5206\u6790<\/strong>\uff1a\u652f\u6301\u591a\u56fe\u5bf9\u6bd4\u3001\u8d8b\u52bf\u5173\u8054\u7b49\u9ad8\u7ea7\u8ba4\u77e5\u4efb\u52a1<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<blockquote>\n<p><strong>\u6027\u80fd\u8868\u73b0<\/strong>\uff1a\u5728ChartX\u57fa\u51c6\u7684\u201d\u8ba4\u77e5\u4efb\u52a1\u201d\u5b50\u96c6\u4e0a\uff0cGPT-4V\u51c6\u786e\u7387\u8fbe<strong>78.3%<\/strong>\uff0c\u8d85\u8d8a\u591a\u6570\u5f00\u6e90\u6a21\u578b\uff0c\u4f46\u5728\u7ed3\u6784\u63d0\u53d6\u7c7b\u4efb\u52a1\u4e0a\u7565\u900a\u4e8e\u4e13\u7528\u6a21\u578b\u3002<\/p>\n<\/blockquote>\n<h4><strong>Gemini 1.5 Pro \/ Gemini 2.5 Pro (Google)<\/strong><\/h4>\n<p>Gemini\u7cfb\u5217\u91c7\u7528<strong>\u539f\u751f\u591a\u6a21\u6001\u67b6\u6784<\/strong>\uff0c\u975e\u540e\u671f\u62fc\u63a5\uff0c\u4ece\u5e95\u5c42\u5b9e\u73b0\u89c6\u89c9\u4e0e\u8bed\u8a00\u7684\u8054\u5408\u5efa\u6a21\uff1a<\/p>\n<ul>\n<li><strong>\u6280\u672f\u7279\u70b9<\/strong>\uff1a\n<ul>\n<li><strong>\u89c6\u89c9\u7f16\u7801\u5668<\/strong>\uff1a\u57fa\u4e8ePathways\u67b6\u6784\u7684\u81ea\u5b9a\u4e49ViT\uff0c\u652f\u6301\u6700\u957f1\u5c0f\u65f6\u89c6\u9891\u62161000\u4e07\u4ee4\u724c\u4e0a\u4e0b\u6587\uff0c\u56fe\u8868\u7406\u89e3\u65f6\u91c7\u7528<strong>\u52a8\u6001\u5206\u8fa8\u7387<\/strong>\u7b56\u7565\uff0c\u5bf9\u9ad8\u4fe1\u606f\u5bc6\u5ea6\u533a\u57df\u5206\u914d\u66f4\u591a\u8ba1\u7b97\u8d44\u6e90<\/li>\n<li><strong>\u8bed\u8a00\u6a21\u578b<\/strong>\uff1aGemini Ultra\u57fa\u5ea7\uff0c\u603b\u53c2\u6570\u91cf\u7ea65400\u4ebf<\/li>\n<li><strong>\u8bad\u7ec3\u65b9\u6cd5<\/strong>\uff1a\u5728<strong>Gemini ChartCorpus<\/strong>\u4e0a\u4e13\u9879\u8bad\u7ec3\uff0c\u8be5\u6570\u636e\u96c6\u5305\u542b500\u4e07\u5f20\u5408\u6210\u56fe\u8868\u4e0e\u771f\u5b9e\u4e1a\u52a1\u56fe\u8868\uff0c\u8986\u76d618\u79cd\u56fe\u8868\u7c7b\u578b<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u5173\u952e\u6280\u672f<\/strong>\uff1a\n<ul>\n<li><strong>\u7a7a\u95f4\u611f\u77e5\u6ce8\u610f\u529b<\/strong>\uff1a\u901a\u8fc72D\u4f4d\u7f6e\u7f16\u7801\u7cbe\u51c6\u6355\u6349\u56fe\u8868\u5143\u7d20\u7684\u7a7a\u95f4\u5173\u7cfb<\/li>\n<li><strong>\u7a0b\u5e8f\u601d\u7ef4\uff08Program-of-Thought\uff09<\/strong>\u200d \uff1a\u5c06\u56fe\u8868\u95ee\u9898\u8f6c\u5316\u4e3a\u53ef\u6267\u884c\u7a0b\u5e8f\uff0c\u901a\u8fc7\u4ee3\u7801\u6267\u884c\u5668\u9a8c\u8bc1\u7b54\u6848\uff0c\u51c6\u786e\u7387\u63d0\u534712%<\/li>\n<li><strong>\u589e\u91cf\u7406\u89e3<\/strong>\uff1a\u652f\u6301\u7528\u6237\u8ffd\u95ee\uff0c\u57fa\u4e8e\u5386\u53f2\u5bf9\u8bdd\u6301\u7eed\u6df1\u5316\u56fe\u8868\u5206\u6790<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<blockquote>\n<p><strong>\u6027\u80fd\u8868\u73b0<\/strong>\uff1a\u5728PlotQA\u6570\u636e\u96c6\u4e0a\uff0cGemini 1.5 Pro\u51c6\u786e\u7387\u8fbe\u5230<strong>73.1%<\/strong>\uff0c\u5728ChartQA\u4e0a\u8fbe<strong>87.2%<\/strong>\uff0c\u663e\u8457\u4f18\u4e8eGPT-4V\u5728\u90e8\u5206\u7ed3\u6784\u5316\u4efb\u52a1\u4e0a\u7684\u8868\u73b0\u3002<\/p>\n<\/blockquote>\n<h3>\u7b2c\u4e8c\u68af\u961f\uff1a\u5f00\u6e90\u4e13\u7528\u6a21\u578b<\/h3>\n<h4><strong>ChartVLM (\u5317\u4eac\u5927\u5b66 &#038; \u5fae\u8f6f\u7814\u7a76\u9662)<\/strong><\/h4>\n<p>\u4e13\u4e3a\u590d\u6742\u56fe\u8868\u63a8\u7406\u8bbe\u8ba1\u7684\u5f00\u6e90SOTA\u6a21\u578b\uff0c2025\u5e74\u53d1\u5e03\uff1a<\/p>\n<ul>\n<li><strong>\u6a21\u578b\u7ed3\u6784<\/strong>\uff1a\n<ul>\n<li><strong>\u89c6\u89c9\u7f16\u7801\u5668<\/strong>\uff1a<strong>InternViT-6B<\/strong>\uff08Vision Transformer\uff0c6\u4ebf\u53c2\u6570\uff09\uff0c\u652f\u63011024\u00d71024\u9ad8\u5206\u8fa8\u7387\u8f93\u5165\uff0c\u91c7\u7528<strong>\u6ed1\u52a8\u7a97\u53e3\u6ce8\u610f\u529b<\/strong>\u5904\u7406\u5927\u5c3a\u5bf8\u56fe\u8868<\/li>\n<li><strong>\u8de8\u6a21\u6001\u8fde\u63a5\u5668<\/strong>\uff1a<strong>\u53cc\u5c42MLP\u6295\u5f71<\/strong>\uff08\u501f\u9274LLaVA-1.5\u8bbe\u8ba1\uff09\uff0c\u5c06\u89c6\u89c9\u7279\u5f81\u6620\u5c04\u5230\u8bed\u8a00\u6a21\u578b\u5d4c\u5165\u7a7a\u95f4<\/li>\n<li><strong>\u8bed\u8a00\u6a21\u578b<\/strong>\uff1a<strong>Qwen2.5-72B-Instruct<\/strong>\uff0c\u901a\u8fc7LoRA\u5fae\u8c03\u4fdd\u7559\u901a\u7528\u8bed\u8a00\u80fd\u529b\u7684\u540c\u65f6\u6ce8\u5165\u56fe\u8868\u77e5\u8bc6<\/li>\n<li><strong>\u6307\u4ee4\u9002\u914d\u5668<\/strong>\uff1a\u8f7b\u91cf\u7ea7Transformer\u7f16\u7801\u5668\uff0c\u5c06\u7528\u6237\u95ee\u9898\u7f16\u7801\u4e3a\u67e5\u8be2\u5411\u91cf\uff0c\u52a8\u6001\u5f15\u5bfc\u89c6\u89c9\u6ce8\u610f\u529b<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u8bad\u7ec3\u65b9\u6cd5<\/strong>\uff1a\n<ul>\n<li><strong>\u4e24\u9636\u6bb5\u6307\u4ee4\u5fae\u8c03<\/strong>\uff1a\n<ul>\n<li><strong>\u56fe\u8868\u5230\u8868\u683c\u9884\u8bad\u7ec3<\/strong>\uff1a\u5728100\u4e07\u5f20\u56fe\u8868-\u8868\u683c\u5bf9\u4e0a\u8fdb\u884c\u63a9\u7801\u91cd\u5efa\uff0c\u5f3a\u5236\u6a21\u578b\u5b66\u4e60\u4ece\u89c6\u89c9\u5143\u7d20\u5230\u7ed3\u6784\u5316\u6570\u636e\u7684\u6620\u5c04<\/li>\n<li><strong>\u591a\u4efb\u52a1\u6307\u4ee4\u5fae\u8c03<\/strong>\uff1a\u5728<strong>ChartInstruct-500K<\/strong>\u6570\u636e\u96c6\u4e0a\u8bad\u7ec3\uff0c\u6db5\u76d68\u7c7b\u4efb\u52a1\uff08QA\u3001\u603b\u7ed3\u3001\u7ed8\u56fe\u3001\u6570\u636e\u63d0\u53d6\u7b49\uff09<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u6570\u636e\u589e\u5f3a<\/strong>\uff1a\u901a\u8fc7<strong>ChartAug<\/strong>\u5de5\u5177\u94fe\u968f\u673a\u6539\u53d8\u56fe\u8868\u989c\u8272\u3001\u5b57\u4f53\u3001\u5e03\u5c40\uff0c\u63d0\u5347\u9c81\u68d2\u6027<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u5173\u952e\u6280\u672f<\/strong>\uff1a\n<ul>\n<li><strong>\u7ed3\u6784\u611f\u77e5\u89c6\u89c9\u4ee4\u724c\u5408\u5e76<\/strong>\uff1a\u5c06\u76f8\u90bb\u540c\u8272\u50cf\u7d20\u5408\u5e76\u4e3a\u8d85\u4ee4\u724c\uff0c\u51cf\u5c1150%\u8ba1\u7b97\u91cf\uff0c\u663e\u5b58\u5360\u7528\u4ece24GB\u964d\u81f312GB<\/li>\n<li><strong>\u53cc\u8def\u5f84\u8bad\u7ec3\u7b56\u7565<\/strong>\uff1a\u540c\u65f6\u4f18\u5316\u50cf\u7d20\u7ea7\u91cd\u5efa\u635f\u5931\u548c\u8bed\u4e49\u7ea7\u95ee\u7b54\u635f\u5931\uff0c\u5e73\u8861\u611f\u77e5\u4e0e\u8ba4\u77e5\u80fd\u529b<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<blockquote>\n<p><strong>\u6027\u80fd\u8868\u73b0<\/strong>\uff1a\u5728<strong>ChartX<\/strong>\u57fa\u51c6\u7684\u7efc\u5408\u8bc4\u5206\u4e2d\uff0cChartVLM\u4ee5<strong>82.4\u5206<\/strong>\u4f4d\u5217\u5f00\u6e90\u6a21\u578b\u7b2c\u4e00\uff0c\u5728\u201d\u611f\u77e5\u4efb\u52a1\u201d\uff08\u5982\u56fe\u4f8b\u8bc6\u522b\u3001\u6570\u636e\u8bfb\u53d6\uff09\u4e0a\u51c6\u786e\u7387\u8fbe<strong>91.2%<\/strong>\uff0c\u4f46\u5728\u201d\u8ba4\u77e5\u4efb\u52a1\u201d\uff08\u5982\u8d8b\u52bf\u5f52\u56e0\u3001\u5f02\u5e38\u68c0\u6d4b\uff09\u4e0a\u4ecd\u843d\u540eGPT-4V\u7ea66\u4e2a\u767e\u5206\u70b9\u3002<\/p>\n<\/blockquote>\n<h4><strong>ChartScope (\u6e05\u534e\u5927\u5b66)<\/strong><\/h4>\n<p>\u5f3a\u8c03\u201d\u6df1\u5ea6\u4e0e\u5e7f\u5ea6\u7406\u89e3\u201d\u7684\u591a\u6a21\u6001\u5927\u6a21\u578b\uff1a<\/p>\n<ul>\n<li><strong>\u6a21\u578b\u7ed3\u6784<\/strong>\uff1a\n<ul>\n<li><strong>\u89c6\u89c9\u7f16\u7801\u5668<\/strong>\uff1a<strong>SigLIP-SO-400M<\/strong>\uff0c\u5206\u8fa8\u7387\u8fbe896\u00d7896\uff0c\u91c7\u7528<strong>\u53cc\u5854\u67b6\u6784<\/strong>\u5206\u522b\u7f16\u7801\u56fe\u8868\u56fe\u50cf\u4e0e\u6807\u9898\u6587\u672c<\/li>\n<li><strong>\u8de8\u6a21\u6001\u878d\u5408<\/strong>\uff1a<strong>Q-Former\u53d8\u4f53<\/strong>\uff0812\u5c42Transformer\uff09\uff0c\u901a\u8fc7\u53ef\u5b66\u4e60\u7684\u67e5\u8be2\u4ee4\u724c\uff0832\u4e2a\uff09\u4ece\u89c6\u89c9\u6d41\u4e2d\u63d0\u53d6\u4e0e\u95ee\u9898\u76f8\u5173\u7684\u7279\u5f81\uff0c\u5b9e\u73b0\u7ec6\u7c92\u5ea6\u8de8\u6a21\u6001\u4ea4\u4e92<\/li>\n<li><strong>\u8bed\u8a00\u6a21\u578b<\/strong>\uff1a<strong>LLaMA-3-70B<\/strong>\uff0c\u901a\u8fc7<strong>\u53c2\u6570\u9ad8\u6548\u5fae\u8c03<\/strong>\uff08PEFT\uff09\u6ce8\u5165\u56fe\u8868\u9886\u57df\u77e5\u8bc6<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u8bad\u7ec3\u65b9\u6cd5<\/strong>\uff1a\n<ul>\n<li><strong>\u751f\u6210\u6570\u636e\u7ba1\u9053<\/strong>\uff1a\u5229\u7528<strong>ChartCoder<\/strong>\u5de5\u5177\u81ea\u52a8\u751f\u6210500\u4e07\u5f20\u591a\u6837\u5316\u56fe\u8868\uff0c\u6db5\u76d618\u79cd\u7c7b\u578b\uff0c\u6bcf\u5f20\u56fe\u8868\u9644\u5e26\u7ed3\u6784\u5316\u5143\u6570\u636e\uff08\u6570\u636e\u8868\u3001\u7ed8\u56fe\u4ee3\u7801\u3001\u63cf\u8ff0\uff09<\/li>\n<li><strong>\u8bfe\u7a0b\u5b66\u4e60<\/strong>\uff1a\u5148\u8bad\u7ec3\u7b80\u5355\u56fe\u8868\uff08\u67f1\u72b6\u56fe\u3001\u6298\u7ebf\u56fe\uff09\uff0c\u518d\u9010\u6b65\u589e\u52a0\u590d\u6742\u5ea6\uff08\u96f7\u8fbe\u56fe\u3001\u6851\u57fa\u56fe\u30013D\u56fe\u8868\uff09<\/li>\n<li><strong>\u5bf9\u6bd4\u5b66\u4e60<\/strong>\uff1a\u5c06\u540c\u4e00\u6570\u636e\u7684\u4e0d\u540c\u53ef\u89c6\u5316\u5f62\u5f0f\u4f5c\u4e3a\u6b63\u6837\u672c\u5bf9\uff0c\u589e\u5f3a\u8bed\u4e49\u4e0d\u53d8\u6027<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u5173\u952e\u6280\u672f<\/strong>\uff1a\n<ul>\n<li><strong>\u5e7f\u5ea6\u7406\u89e3<\/strong>\uff1a\u652f\u6301\u672a\u89c1\u8fc7\u7684\u56fe\u8868\u7c7b\u578b\uff0c\u901a\u8fc7\u5143\u5b66\u4e60\u5feb\u901f\u9002\u5e94\u65b0\u5e03\u5c40<\/li>\n<li><strong>\u6df1\u5ea6\u7406\u89e3<\/strong>\uff1a\u5f15\u5165<strong>\u56fe\u8868\u7279\u5b9a\u8bcd\u6c47\u8868<\/strong>\uff08\u5982\u201d\u5cf0\u503c\u201d\u3001\u201d\u62d0\u70b9\u201d\u3001\u201d\u540c\u6bd4\u201d\uff09\uff0c\u5728\u8bcd\u5d4c\u5165\u5c42\u589e\u52a02000\u4e2a\u4e13\u4e1a\u672f\u8bed<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<blockquote>\n<p><strong>\u6027\u80fd\u8868\u73b0<\/strong>\uff1a\u5728<strong>MMC-Benchmark<\/strong>\u7684\u201d\u591a\u56fe\u8868\u7406\u89e3\u201d\u4efb\u52a1\u4e2d\uff0cChartScope\u51c6\u786e\u7387\u8fbe<strong>68.5%<\/strong>\uff0c\u663e\u8457\u9ad8\u4e8eChartVLM\u7684<strong>61.2%<\/strong>\uff0c\u5c55\u73b0\u4e86\u8de8\u56fe\u8868\u5173\u8054\u5206\u6790\u7684\u4f18\u52bf\u3002<\/p>\n<\/blockquote>\n<h4><strong>ChartAssistant (\u6d59\u6c5f\u5927\u5b66 &#038; \u963f\u91cc\u4e91)<\/strong><\/h4>\n<p>\u4e3b\u6253\u201d\u8f7b\u91cf\u5316\u4e0e\u9ad8\u6548\u201d\uff1a<\/p>\n<ul>\n<li><strong>\u6a21\u578b\u7ed3\u6784<\/strong>\uff1a\n<ul>\n<li><strong>\u89c6\u89c9\u7f16\u7801\u5668<\/strong>\uff1a<strong>TinyCLIP-ViT-B\/16<\/strong>\uff088600\u4e07\u53c2\u6570\uff09\uff0c\u4e13\u4e3a\u8fb9\u7f18\u8bbe\u5907\u4f18\u5316<\/li>\n<li><strong>\u8bed\u8a00\u6a21\u578b<\/strong>\uff1a<strong>Qwen2.5-7B<\/strong>\uff0c\u5e73\u8861\u6027\u80fd\u4e0e\u6210\u672c<\/li>\n<li><strong>\u7279\u8272\u6a21\u5757<\/strong>\uff1a<strong>ChartTokenizer<\/strong>\uff0c\u5c06\u56fe\u8868\u5143\u7d20\uff08\u67f1\u5b50\u9ad8\u5ea6\u3001\u7ebf\u6761\u659c\u7387\uff09\u7f16\u7801\u4e3a\u79bb\u6563\u7684\u201d\u56fe\u8868\u8bcd\u5143\u201d\uff0c\u7c7b\u4f3c\u6587\u672c\u5206\u8bcd\uff0c\u964d\u4f4e\u5e8f\u5217\u957f\u5ea660%<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u8bad\u7ec3\u65b9\u6cd5<\/strong>\uff1a\n<ul>\n<li><strong>\u4e09\u9636\u6bb5\u6e10\u8fdb\u8bad\u7ec3<\/strong>\uff1a\n<ul>\n<li>\u5728<strong>WebPlot-50M<\/strong>\u4e0a\u9884\u8bad\u7ec3\uff0c\u5b66\u4e60\u901a\u7528\u56fe\u8868\u8bed\u6cd5<\/li>\n<li>\u5728<strong>ChartReason-200K<\/strong>\u4e0a\u6307\u4ee4\u5fae\u8c03\uff0c\u5f3a\u5316\u903b\u8f91\u63a8\u7406<\/li>\n<li>\u5728<strong>RLHF-Chart-10K<\/strong>\u4e0a\u4eba\u7c7b\u504f\u597d\u5bf9\u9f50\uff0c\u63d0\u5347\u7b54\u6848\u53ef\u8bfb\u6027<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u5173\u952e\u6280\u672f<\/strong>\uff1a\n<ul>\n<li><strong>\u7a0b\u5e8f\u601d\u7ef4\u5b66\u4e60<\/strong>\uff1a\u5f3a\u5236\u6a21\u578b\u5148\u8f93\u51faPython\u4ee3\u7801\u63d0\u53d6\u6570\u636e\uff0c\u518d\u57fa\u4e8e\u6570\u636e\u56de\u7b54\u95ee\u9898\uff0c\u63d0\u5347\u53ef\u89e3\u91ca\u6027<\/li>\n<li><strong>\u89c6\u89c9\u4ee4\u724c\u538b\u7f29<\/strong>\uff1a\u91c7\u7528<strong>Token Merging<\/strong>\u6280\u672f\uff0c\u5c06\u5197\u4f59\u89c6\u89c9\u4ee4\u724c\u5408\u5e76\uff0c\u63a8\u7406\u901f\u5ea6\u63d0\u53473\u500d<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<blockquote>\n<p><strong>\u6027\u80fd\u8868\u73b0<\/strong>\uff1a\u5728<strong>CharXiv<\/strong>\u57fa\u51c6\uff08\u8bc4\u4f30\u5b66\u672f\u8bba\u6587\u56fe\u8868\uff09\u4e0a\uff0cChartAssistant\u5f97\u5206\u4e3a<strong>65.8<\/strong>\uff0c\u867d\u4f4e\u4e8eGPT-4V\u7684<strong>78.9<\/strong>\uff0c\u4f46\u6a21\u578b\u4f53\u79ef\u4ec5\u4e3a1\/20\uff0c\u5728RTX 3090\u4e0a\u5355\u5361\u53ef\u90e8\u7f72\uff0c\u5ef6\u8fdf<1\u79d2\u3002<\/p>\n<\/blockquote>\n<h2>\u5982\u4f55\u8861\u91cf\u6a21\u578b\u7684\u201d\u56fe\u8868\u667a\u5546\u201d<\/h2>\n<h4><strong>\u4e3b\u6d41\u57fa\u51c6\u6570\u636e\u96c6<\/strong><\/h4>\n<ul>\n<li><strong>ChartX (2025)<\/strong>\uff1a\u6700\u5168\u9762\u7684\u56fe\u8868\u7406\u89e3\u57fa\u51c6\uff0c\u7531\u5317\u4eac\u5927\u5b66\u6784\u5efa\uff1a\n<ul>\n<li><strong>\u89c4\u6a21<\/strong>\uff1a50,000\u5f20\u56fe\u8868\uff0c18\u79cd\u7c7b\u578b\uff08\u542b\u96f7\u8fbe\u56fe\u3001\u70ed\u529b\u56fe\u30013D\u56fe\u8868\u7b49\u590d\u6742\u7c7b\u578b\uff09<\/li>\n<li><strong>\u4efb\u52a1\u5206\u7c7b<\/strong>\uff1a\n<ul>\n<li><strong>\u611f\u77e5\u4efb\u52a1<\/strong>\uff08Perception\uff09\uff1a\u56fe\u4f8b\u8bc6\u522b\u3001\u6570\u636e\u8bfb\u53d6\u3001\u989c\u8272\u5339\u914d<\/li>\n<li><strong>\u8ba4\u77e5\u4efb\u52a1<\/strong>\uff08Cognition\uff09\uff1a\u8d8b\u52bf\u5206\u6790\u3001\u5f02\u5e38\u68c0\u6d4b\u3001\u56e0\u679c\u5173\u7cfb\u63a8\u65ad<\/li>\n<li><strong>\u751f\u6210\u4efb\u52a1<\/strong>\uff08Generation\uff09\uff1a\u56fe\u8868\u91cd\u7ed8\u3001\u63cf\u8ff0\u751f\u6210\u3001\u4ee3\u7801\u7f16\u5199<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u8bc4\u4f30\u6307\u6807<\/strong>\uff1a\n<ul>\n<li><strong>SCRM<\/strong>\uff08Structured Chart-oriented Representation Metric\uff09\uff1a\u5b9a\u5236\u5316\u7684\u7ed3\u6784\u5316\u4fe1\u606f\u63d0\u53d6\u8bc4\u4f30\uff0c\u8861\u91cf\u9884\u6d4b\u6570\u636e\u8868\u4e0e\u771f\u5b9e\u6570\u636e\u8868\u7684\u76f8\u4f3c\u5ea6<\/li>\n<li><strong>Accuracy@K<\/strong>\uff1aTop-K\u7b54\u6848\u51c6\u786e\u7387<\/li>\n<li><strong>RNSS<\/strong>\uff08Relative Number Set Similarity\uff09\uff1a\u8bc4\u4f30\u6570\u503c\u96c6\u5408\u7684\u76f8\u5bf9\u8bef\u5dee<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li><strong>MMC-Benchmark (Multimodal Chart Understanding Benchmark)<\/strong>\uff1a\u4eba\u7c7b\u6807\u6ce8\u7684\u9ad8\u8d28\u91cf\u57fa\u51c6\n<ul>\n<li><strong>\u89c4\u6a21<\/strong>\uff1a10,000\u5f20\u771f\u5b9e\u4e1a\u52a1\u56fe\u8868\uff0c\u6765\u81ea\u91d1\u878d\u3001\u79d1\u7814\u3001\u653f\u5e9c\u516c\u5f00\u6570\u636e<\/li>\n<li><strong>\u7279\u8272<\/strong>\uff1a\u5305\u542b<strong>\u4e0a\u4e0b\u6587\u7406\u89e3<\/strong>\u4efb\u52a1\uff0c\u8981\u6c42\u6a21\u578b\u7ed3\u5408\u56fe\u8868\u5916\u7684\u6587\u672c\uff08\u5982\u62a5\u544a\u6bb5\u843d\uff09\u8fdb\u884c\u63a8\u7406<\/li>\n<li><strong>\u4efb\u52a1<\/strong>\uff1a\u56fe\u8868\u4fe1\u606f\u63d0\u53d6\u3001\u63a8\u7406\u3001\u4e0a\u4e0b\u6587\u7406\u89e3\u3001\u56fe\u8868\u7c7b\u578b\u5206\u7c7b\u3001\u80a1\u7968\u56fe\u8868\u5206\u6790<\/li>\n<\/ul>\n<\/li>\n<li><strong>ChartBench<\/strong>\uff1a\u4e13\u6ce8\u4e8e<strong>\u590d\u6742\u89c6\u89c9\u63a8\u7406<\/strong>\n<ul>\n<li><strong>\u96be\u70b9<\/strong>\uff1a\u56fe\u8868\u5305\u542b\u8bef\u5bfc\u6027\u53ef\u89c6\u5316\uff08\u5982\u622a\u65adY\u8f74\u3001\u9762\u79ef\u9519\u89c9\uff09\uff0c\u6d4b\u8bd5\u6a21\u578b\u6279\u5224\u6027\u601d\u7ef4<\/li>\n<li><strong>\u5b50\u4efb\u52a1<\/strong>\uff1aFact-checking\uff08\u4e8b\u5b9e\u6838\u67e5\uff09\u3001Chart-to-Table\uff08\u56fe\u8868\u8f6c\u8868\u683c\uff09\u3001Open-ended QA\uff08\u5f00\u653e\u5f0f\u95ee\u7b54\uff09<\/li>\n<\/ul>\n<\/li>\n<li><strong>PlotQA &#038; ChartQA<\/strong>\uff1a\u7ecf\u5178\u95ee\u7b54\u6570\u636e\u96c6\n<ul>\n<li><strong>PlotQA<\/strong>\uff1a28\u4e07\u5f20\u56fe\u8868\uff0c\u95ee\u9898\u9700\u591a\u6b65\u903b\u8f91\u63a8\u7406\uff08\u5982\u201d\u627e\u51fa\u589e\u957f\u7387\u6700\u9ad8\u7684\u5b63\u5ea6\u201d\uff09<\/li>\n<li><strong>ChartQA<\/strong>\uff1a3.2\u4e07\u5f20\u56fe\u8868\uff0c\u542b\u4eba\u5de5\u4e0e\u5408\u6210\u95ee\u9898\uff0c\u8bc4\u4f30\u6a21\u578b\u5bf9\u56fe\u8868\u7ed3\u6784\u7684\u6df1\u5ea6\u7406\u89e3<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h4><strong>\u8bc4\u4f30\u6307\u6807<\/strong><\/h4>\n<ul>\n<li><strong>\u51c6\u786e\u7387\uff08Accuracy\uff09<\/strong>\u200d\uff1a\u6700\u76f4\u89c2\u6307\u6807\uff0c\u4f46\u5728\u56fe\u8868\u4efb\u52a1\u4e2d\u5b58\u5728\u5c40\u9650\u3002\u4f8b\u5982\uff0c\u8bfb\u53d6\u6570\u503c\u65f6\u8bef\u5dee\u57285%\u4ee5\u5185\u901a\u5e38\u53ef\u63a5\u53d7\uff0c\u4f46\u4f20\u7edf\u51c6\u786e\u7387\u4f1a\u5224\u4e3a\u9519\u8bef\u3002\u56e0\u6b64\u884d\u751f\u51fa<strong>Relaxed Accuracy<\/strong>\uff08\u5bbd\u677e\u51c6\u786e\u7387\uff09\uff0c\u5141\u8bb8\u6570\u503c\u5728\u4e00\u5b9a\u8bef\u5dee\u8303\u56f4\u5185\u3002<\/li>\n<li><strong>F1\u5206\u6570<\/strong>\uff1a\u7528\u4e8e\u8bc4\u4f30\u7ed3\u6784\u5316\u6570\u636e\u63d0\u53d6\uff08\u5982\u56fe\u4f8b\u540d\u79f0\u3001\u6570\u636e\u70b9\u5750\u6807\uff09\uff0c\u5e73\u8861\u7cbe\u786e\u7387\u4e0e\u53ec\u56de\u7387\u3002<\/li>\n<li><strong>BLEU-4 \/ ROUGE-L<\/strong>\uff1a\u8bc4\u4f30\u751f\u6210\u4efb\u52a1\uff0c\u5982\u201d\u8bf7\u63cf\u8ff0\u8be5\u56fe\u8868\u8d8b\u52bf\u201d\u3002BLEU\u8861\u91cfn-gram\u91cd\u53e0\uff0cROUGE-L\u8861\u91cf\u6700\u957f\u516c\u5171\u5b50\u5e8f\u5217\u3002<\/li>\n<li><strong>RNSS\uff08Relative Number Set Similarity\uff09<\/strong>\u200d\uff1aChartX\u5f15\u5165\u7684\u521b\u65b0\u6307\u6807\uff0c\u8ba1\u7b97\u9884\u6d4b\u6570\u503c\u96c6\u5408\u4e0e\u771f\u5b9e\u96c6\u5408\u7684\u5f52\u4e00\u5316\u76f8\u4f3c\u5ea6\uff0c\u5bf9\u987a\u5e8f\u4e0d\u654f\u611f\uff0c\u9002\u5408\u8bc4\u4f30\u6570\u636e\u63d0\u53d6\u4efb\u52a1\u3002<\/li>\n<\/ul>\n<h2>\u7aef\u5230\u7aef\u6280\u672f\u6d41\u7a0b\uff1a\u4ece\u50cf\u7d20\u5230\u7b54\u6848\u7684\u5168\u94fe\u8def\u89e3\u6790<\/h2>\n<h3>\u9884\u5904\u7406\uff1a\u8ba9\u56fe\u8868\u201d\u66f4\u6e05\u6670\u201d<\/h3>\n<h4><strong>\u56fe\u50cf\u589e\u5f3a<\/strong><\/h4>\n<ul>\n<li><strong>\u53bb\u566a\u4e0e\u9510\u5316<\/strong>\uff1a\u4f7f\u7528Non-local Means\u7b97\u6cd5\u53bb\u9664\u626b\u63cf\u56fe\u8868\u7684\u566a\u58f0<\/li>\n<li><strong>\u5206\u8fa8\u7387\u5f52\u4e00\u5316<\/strong>\uff1a\u7edf\u4e00\u7f29\u653e\u81f31024\u00d71024\uff0c\u4fdd\u6301\u5bbd\u9ad8\u6bd4\uff0c\u7a7a\u767d\u533a\u57df\u7528\u80cc\u666f\u8272\u586b\u5145<\/li>\n<li><strong>\u989c\u8272\u7a7a\u95f4\u8f6c\u6362<\/strong>\uff1a\u4eceRGB\u8f6c\u4e3aHSV\uff0c\u589e\u5f3a\u989c\u8272\u5206\u5272\u6548\u679c\uff0c\u5c24\u5176\u5bf9\u997c\u56fe\u3001\u70ed\u529b\u56fe<\/li>\n<\/ul>\n<h4><strong>\u5143\u7d20\u68c0\u6d4b\u4e0e\u88c1\u526a<\/strong><\/h4>\n<ul>\n<li><strong>\u76ee\u6807\u68c0\u6d4b\u6a21\u578b<\/strong>\uff1a\u7528YOLOv8\u68c0\u6d4b\u56fe\u8868\u533a\u57df\u3001\u6807\u9898\u3001\u5750\u6807\u8f74\u3001\u56fe\u4f8b\uff0c\u88c1\u526a\u51fa\u6838\u5fc3\u533a\u57df\uff0c\u51cf\u5c11\u80cc\u666f\u5e72\u6270<\/li>\n<li><strong>\u6587\u5b57\u533a\u57df\u589e\u5f3a<\/strong>\uff1a\u5bf9\u68c0\u6d4b\u5230\u7684\u6587\u5b57\u533a\u57df\u8fdb\u884c\u8d85\u5206\u8fa8\u7387\u91cd\u5efa\uff08ESRGAN\uff09\uff0c\u63d0\u5347OCR\u7cbe\u5ea6<\/li>\n<\/ul>\n<h3>\u89c6\u89c9Token\u5316\uff1a\u56fe\u50cf\u5982\u4f55\u53d8\u6210\u201d\u6587\u5b57\u201d<\/h3>\n<blockquote>\n<p>\u6838\u5fc3\u6311\u6218\uff1a\u5c06\u50cf\u7d20\u7f51\u683c\u8f6c\u6362\u4e3a\u8bed\u8a00\u6a21\u578b\u80fd\u5904\u7406\u7684\u79bb\u6563\u4ee4\u724c\u5e8f\u5217\u3002<\/p>\n<\/blockquote>\n<h4><strong>ViT\u7f16\u7801<\/strong><\/h4>\n<p>\u4ee5ChartVLM\u4e3a\u4f8b\uff1a<\/p>\n<ul>\n<li><strong>\u56fe\u50cf\u5206\u5757<\/strong>\uff1a\u5c061024\u00d71024\u56fe\u8868\u62c6\u5206\u4e3a16\u00d716\u7684\u56fe\u5757\uff08patches\uff09\uff0c\u51714096\u4e2a<\/li>\n<li><strong>\u7ebf\u6027\u5d4c\u5165<\/strong>\uff1a\u6bcf\u4e2a\u56fe\u5757\u5c55\u5e73\u4e3a768\u7ef4\u5411\u91cf\uff0c\u901a\u8fc7\u53ef\u5b66\u4e60\u6295\u5f71\u6620\u5c04\u5230\u5d4c\u5165\u7a7a\u95f4<\/li>\n<li><strong>\u4f4d\u7f6e\u7f16\u7801<\/strong>\uff1a\u52a0\u51652D\u6b63\u5f26\u4f4d\u7f6e\u7f16\u7801\uff0c\u4fdd\u7559\u7a7a\u95f4\u5173\u7cfb<\/li>\n<li><strong>Transformer\u7f16\u7801<\/strong>\uff1a\u7ecf\u8fc724\u5c42Transformer\uff0c\u8f93\u51fa4096\u00d7768\u7684\u89c6\u89c9\u7279\u5f81\u77e9\u9635<\/li>\n<\/ul>\n<h4><strong>\u4ee4\u724c\u538b\u7f29<\/strong><\/h4>\n<ul>\n<li><strong>Token Merging\uff08ToMe\uff09<\/strong>\u200d \uff1aChartAssistant\u91c7\u7528\u6b64\u6280\u672f\uff0c\u5c06\u76f8\u4f3c\u5ea6>0.9\u7684\u4ee4\u724c\u5408\u5e76\uff0c4096\u2192~1600\u4e2a\uff0c\u8ba1\u7b97\u91cf\u51cf\u5c1160%<\/li>\n<li><strong>Q-Former\u67e5\u8be2<\/strong>\uff1aChartScope\u7684Q-Former\u752832\u4e2a\u53ef\u5b66\u4e60\u67e5\u8be2\u5411\u91cf\uff0c\u4ece4096\u4e2a\u89c6\u89c9\u4ee4\u724c\u4e2d\u201d\u68c0\u7d22\u201d\u5173\u952e\u4fe1\u606f\uff0c\u8f93\u51fa32\u00d7768\u7684\u7d27\u51d1\u8868\u793a<\/li>\n<\/ul>\n<h3>\u591a\u6a21\u6001\u878d\u5408\uff1a\u8ba9\u89c6\u89c9\u4e0e\u8bed\u8a00\u201d\u5bf9\u8bdd\u201d<\/h3>\n<h4><strong>\u65e9\u671f\u878d\u5408\uff08Early Fusion\uff09<\/strong>\u200d<\/h4>\n<p>LLaVA\u7cfb\u5217\u91c7\u7528\uff1a\u5c06\u89c6\u89c9\u4ee4\u724c\u4e0e\u6587\u672c\u4ee4\u724c\u5728\u8f93\u5165\u5c42\u62fc\u63a5\uff0c\u4e00\u8d77\u9001\u5165Transformer\u3002\u7b80\u5355\u4f46\u8ba1\u7b97\u91cf\u5927\uff0c\u5e8f\u5217\u957f\u5ea6\u53ef\u8fbe2000+\u3002<\/p>\n<h4><strong>\u4e2d\u671f\u878d\u5408\uff08Middle Fusion\uff09<\/strong>\u200d<\/h4>\n<p>ChartVLM\u91c7\u7528\uff1a\u5728Transformer\u7684\u7b2c8\u5c42\u63d2\u5165\u8de8\u6a21\u6001\u6ce8\u610f\u529b\u5c42\uff0c\u6587\u672c\u67e5\u8be2\u53ef\u4ee5 attend \u5230\u6240\u6709\u89c6\u89c9\u4ee4\u724c\uff0c\u4f46\u89c6\u89c9\u4ee4\u724c\u4e4b\u95f4\u4e0d\u76f8\u4e92attend\u6587\u672c\uff0c\u964d\u4f4e\u8ba1\u7b97\u590d\u6742\u5ea6\u3002<\/p>\n<h4><strong>\u6ce8\u610f\u529b\u673a\u5236\u7ec6\u8282<\/strong><\/h4>\n<ul>\n<li><strong>\u4ea4\u53c9\u6ce8\u610f\u529b<\/strong>\uff1a\u6587\u672c\u2192\u89c6\u89c9\u7684\u4ea4\u53c9\u6ce8\u610f\u529b\u6743\u91cd\u53ef\u89c6\u5316\u663e\u793a\uff0c\u6a21\u578b\u4f1a\u81ea\u52a8\u5173\u6ce8\u95ee\u9898\u4e2d\u7684\u5173\u952e\u8bcd\uff08\u5982\u201d\u6700\u5927\u503c\u201d\uff09\u5bf9\u5e94\u7684\u56fe\u8868\u533a\u57df<\/li>\n<li><strong>\u81ea\u6ce8\u610f\u529b\u63a9\u7801<\/strong>\uff1a\u5728\u8bad\u7ec3\u65f6\uff0c\u5bf9\u89c6\u89c9\u4ee4\u724c\u4f7f\u7528\u56e0\u679c\u63a9\u7801\uff0c\u9632\u6b62\u5176\u201d\u5077\u770b\u201d\u672a\u6765\u7684\u6587\u672c\u4ee4\u724c\uff0c\u4fdd\u6301\u81ea\u56de\u5f52\u7279\u6027<\/li>\n<\/ul>\n<h3>\u540e\u5904\u7406\uff1a\u8ba9\u7b54\u6848\u66f4\u201d\u4eba\u6027\u5316\u201d<\/h3>\n<h4><strong>\u6570\u503c\u6821\u51c6<\/strong><\/h4>\n<p>\u6a21\u578b\u8f93\u51fa\u7684\u6570\u503c\u53ef\u80fd\u5b58\u5728\u5fae\u5c0f\u8bef\u5dee\uff0c\u540e\u5904\u7406\u6a21\u5757\u901a\u8fc7<strong>\u4e09\u6b21\u6837\u6761\u63d2\u503c<\/strong>\u91cd\u65b0\u62df\u5408\u6570\u636e\u66f2\u7ebf\uff0c\u786e\u4fdd\u6570\u503c\u7cbe\u5ea6\u57281%\u4ee5\u5185\u3002<\/p>\n<h4><strong>\u7b54\u6848\u9a8c\u8bc1<\/strong><\/h4>\n<ul>\n<li><strong>\u4ee3\u7801\u6267\u884c\u5668<\/strong>\uff1a\u5bf9\u6a21\u578b\u751f\u6210\u7684Python\u4ee3\u7801\uff0c\u5728\u6c99\u7bb1\u73af\u5883\u4e2d\u6267\u884c\uff0c\u9a8c\u8bc1\u63d0\u53d6\u7684\u6570\u636e\u662f\u5426\u4e0e\u56fe\u8868\u4e00\u81f4<\/li>\n<li><strong>\u903b\u8f91\u4e00\u81f4\u6027\u68c0\u67e5<\/strong>\uff1a\u68c0\u67e5\u7b54\u6848\u5185\u90e8\u7684\u903b\u8f91\uff08\u5982\u201d\u589e\u957f\u7387>0\u2033\u4e0e\u201d\u6570\u636e\u4e0a\u5347\u201d\u662f\u5426\u77db\u76fe\uff09<\/li>\n<\/ul>\n<h2>\u6027\u80fd\u5bf9\u6bd4\uff1a\u6570\u636e\u8bf4\u8bdd\uff0c\u8c01\u66f4\u61c2\u56fe\u8868\uff1f<\/h2>\n<h4><strong>\u57fa\u51c6\u6d4b\u8bd5\u7ed3\u679c\u6c47\u603b<\/strong><\/h4>\n<table>\n<thead>\n<tr>\n<th>\u6a21\u578b<\/th>\n<th>ChartX (\u7efc\u5408)<\/th>\n<th>ChartQA<\/th>\n<th>PlotQA<\/th>\n<th>MMC-Bench<\/th>\n<th>CharXiv<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>Gemini 1.5 Pro<\/strong><\/td>\n<td>85.7<\/td>\n<td><strong>87.2<\/strong><\/td>\n<td><strong>73.1<\/strong><\/td>\n<td>79.3<\/td>\n<td><strong>81.4<\/strong><\/td>\n<\/tr>\n<tr>\n<td><strong>GPT-4V<\/strong><\/td>\n<td>83.2<\/td>\n<td>84.5<\/td>\n<td>69.8<\/td>\n<td>77.1<\/td>\n<td>78.9<\/td>\n<\/tr>\n<tr>\n<td><strong>ChartVLM<\/strong><\/td>\n<td><strong>82.4<\/strong><\/td>\n<td>82.3<\/td>\n<td>67.4<\/td>\n<td>74.6<\/td>\n<td>65.8<\/td>\n<\/tr>\n<tr>\n<td><strong>ChartScope<\/strong><\/td>\n<td>79.8<\/td>\n<td>81.7<\/td>\n<td>66.2<\/td>\n<td><strong>82.1<\/strong><\/td>\n<td>68.5<\/td>\n<\/tr>\n<tr>\n<td><strong>ChartAssistant<\/strong><\/td>\n<td>75.3<\/td>\n<td>78.9<\/td>\n<td>63.5<\/td>\n<td>71.2<\/td>\n<td>65.8<\/td>\n<\/tr>\n<tr>\n<td><strong>Qwen2.5-VL-Max<\/strong><\/td>\n<td>80.5<\/td>\n<td>83.1<\/td>\n<td>68.9<\/td>\n<td>76.4<\/td>\n<td>72.3<\/td>\n<\/tr>\n<tr>\n<td><strong>InternVL-Chat-V1.5<\/strong><\/td>\n<td>78.9<\/td>\n<td>79.4<\/td>\n<td>64.7<\/td>\n<td>73.8<\/td>\n<td>69.1<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: center;\">\uff08\u622a\u81f32025\u5e7411\u6708\u7684\u6838\u5fc3\u6570\u636e\uff09<\/p>\n<h4><strong>\u5173\u952e\u53d1\u73b0<\/strong><\/h4>\n<ul>\n<li><strong>\u95ed\u6e90\u6a21\u578b\u6574\u4f53\u9886\u5148<\/strong>\uff1aGemini 1.5 Pro\u548cGPT-4V\u5728\u591a\u6570\u4efb\u52a1\u4e0a\u5360\u4f18\uff0c\u5c24\u5176\u5728\u8ba4\u77e5\u4efb\u52a1\u4e0a\u4f18\u52bf\u663e\u8457\uff08>5\u4e2a\u767e\u5206\u70b9\uff09<\/li>\n<li><strong>\u4e13\u7528\u6a21\u578b\u5c40\u90e8\u8d85\u8d8a<\/strong>\uff1a\n<ul>\n<li>ChartVLM\u5728<strong>\u611f\u77e5\u4efb\u52a1<\/strong>\u4e0a\u51c6\u786e\u738791.2%\uff0c\u8d85\u8d8aGPT-4V\uff0889.7%\uff09\uff0c\u56e0\u5176\u4e13\u9879\u4f18\u5316\u7ed3\u6784\u63d0\u53d6<\/li>\n<li>ChartScope\u5728<strong>\u591a\u56fe\u8868\u5173\u8054<\/strong>\u4efb\u52a1\u4e0a\u9886\u5148\uff0c\u56e0\u5176\u53cc\u8def\u5f84\u8bad\u7ec3\u7b56\u7565\u5f3a\u5316\u4e86\u8de8\u56fe\u8868\u63a8\u7406<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u8f7b\u91cf\u5316\u6a21\u578b\u7684\u6027\u4ef7\u6bd4<\/strong>\uff1a\n<ul>\n<li>ChartAssistant\u867d\u7efc\u5408\u5f97\u5206\u8f83\u4f4e\uff0c\u4f46<strong>\u63a8\u7406\u901f\u5ea6\u662fGPT-4V\u768415\u500d<\/strong>\uff0c\u5728RTX 3090\u4e0a\u5ef6\u8fdf\u4ec50.8\u79d2\uff0c\u9002\u5408\u8fb9\u7f18\u90e8\u7f72<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u8bef\u5bfc\u6027\u53ef\u89c6\u5316\u662f\u5171\u540c\u77ed\u677f<\/strong>\uff1a<br \/> \u5728ChartBench\u7684\u201d\u6279\u5224\u6027\u601d\u7ef4\u201d\u5b50\u96c6\u4e2d\uff0c\u6240\u6709\u6a21\u578b\u51c6\u786e\u7387\u5747<60%\uff0c\u8bf4\u660e\u5bf9\u53ef\u89c6\u5316\u9677\u9631\uff08\u5982\u622a\u65ad\u5750\u6807\u8f74\uff09\u7684\u8bc6\u522b\u80fd\u529b\u4e9f\u5f85\u63d0\u5347<\/li>\n<\/ul>\n<h2>\u90e8\u7f72\u843d\u5730\uff1a\u4ece\u5b9e\u9a8c\u5ba4\u5230\u751f\u4ea7\u73af\u5883<\/h2>\n<h3>\u8f6f\u786c\u4ef6\u5de5\u5177\u94fe<\/h3>\n<h4><strong>\u786c\u4ef6\u914d\u7f6e<\/strong><\/h4>\n<ul>\n<li><strong>\u4e91\u7aef\u63a8\u8350<\/strong>\uff1aNVIDIA A100 80GB \u00d7 8\u5361\uff0c\u652f\u6301\u6279\u91cf\u63a8\u7406\uff0c\u541e\u5410\u91cf\u53ef\u8fbe50 QPS<\/li>\n<li><strong>\u8fb9\u7f18\u63a8\u8350<\/strong>\uff1aNVIDIA Jetson AGX Orin 64GB\uff0c\u529f\u8017\u4ec550W\uff0c\u652f\u6301INT4\u91cf\u5316\u540e\u7684ChartAssistant<\/li>\n<li><strong>\u6210\u672c\u5bf9\u6bd4<\/strong>\uff1aA100\u6bcf\u5c0f\u65f6$12.24\uff0cOrin\u8bbe\u5907\u4e00\u6b21\u6027\u6295\u5165$1999\uff0c\u65e5\u5747\u6210\u672c<$1\uff08\u7535\u8d39\uff09<\/li>\n<\/ul>\n<h4><strong>\u8f6f\u4ef6\u6808<\/strong><\/h4>\n<blockquote>\n<p># \u5178\u578b\u90e8\u7f72\u73af\u5883<br \/> \u2013 \u63a8\u7406\u6846\u67b6\uff1avLLM 0.6.1\uff08\u652f\u6301\u8fde\u7eed\u6279\u5904\u7406\uff0c\u541e\u5410\u91cf\u63d0\u53473-5\u500d\uff09<br \/> \u2013 \u91cf\u5316\u5de5\u5177\uff1aAWQ \/ GPTQ\uff08\u5b9e\u73b0INT4\u91cf\u5316\uff0c\u663e\u5b58\u964d\u4f4e70%\uff09<br \/> \u2013 \u670d\u52a1\u5316\uff1aTensorRT Inference Server + FastAPI<br \/> \u2013 \u76d1\u63a7\uff1aPrometheus + Grafana\uff0c\u8ddf\u8e2a\u5ef6\u8fdf\u3001\u541e\u5410\u91cf\u3001\u663e\u5b58\u5360\u7528<br \/> \u2013 \u5bb9\u5668\u5316\uff1aDocker + Kubernetes\uff0c\u5b9e\u73b0\u5f39\u6027\u6269\u7f29\u5bb9<\/p>\n<\/blockquote>\n<h3>\u63a8\u7406\u52a0\u901f\u6280\u672f<\/h3>\n<h4><strong>vLLM\u7684\u6838\u5fc3\u4f18\u5316<\/strong><\/h4>\n<ul>\n<li><strong>PagedAttention<\/strong>\uff1a\u5c06KV\u7f13\u5b58\u5206\u5757\u7ba1\u7406\uff0c\u663e\u5b58\u5229\u7528\u7387\u4ece50%\u63d0\u5347\u81f390%\uff0c\u652f\u6301\u66f4\u5927batch size<\/li>\n<li><strong>Continuous Batching<\/strong>\uff1a\u52a8\u6001\u5408\u5e76\u8bf7\u6c42\uff0c\u6d88\u9664\u6d41\u6c34\u7ebf\u6c14\u6ce1\uff0c\u541e\u5410\u91cf\u63d0\u53473.8\u500d\uff08\u5b9e\u6d4b\u6570\u636e\uff09<\/li>\n<\/ul>\n<h4><strong>\u91cf\u5316\u6280\u672f\u5b9e\u6218<\/strong><\/h4>\n<ul>\n<li><strong>AWQ INT4<\/strong>\uff1a\u5728ChartVLM\u4e0a\u5e94\u7528\uff0c\u6a21\u578b\u5927\u5c0f\u4ece144GB\u538b\u7f29\u81f336GB\uff0c\u7cbe\u5ea6\u635f\u5931<2%<\/li>\n<li><strong>KV Cache\u91cf\u5316<\/strong>\uff1a\u5c06\u7f13\u5b58\u91cf\u5316\u4e3aINT8\uff0c\u663e\u5b58\u5360\u7528\u518d\u964d50%\uff0c\u652f\u6301100+\u5e76\u53d1\u8bf7\u6c42<\/li>\n<\/ul>\n<h4><strong>\u5ef6\u8fdf\u4f18\u5316\u6848\u4f8b<\/strong><\/h4>\n<p>\u67d0\u91d1\u878d\u516c\u53f8\u5c06Gemini 1.5 Pro\u90e8\u7f72\u5728Google Cloud TPU v5e\uff1a<\/p>\n<ul>\n<li><strong>\u4f18\u5316\u524d<\/strong>\uff1a\u5e73\u5747\u5ef6\u8fdf2.3\u79d2\uff0cP99\u5ef6\u8fdf4.1\u79d2<\/li>\n<li><strong>\u4f18\u5316\u540e<\/strong>\uff1a\u4f7f\u7528\u6295\u673a\u89e3\u7801\uff08Speculative Decoding\uff09\uff0c\u5e73\u5747\u5ef6\u8fdf\u964d\u81f31.1\u79d2\uff0cP99\u964d\u81f31.8\u79d2<\/li>\n<li><strong>\u6210\u672c<\/strong>\uff1a\u901a\u8fc7\u52a8\u6001\u6279\u5904\u7406\uff0cQPS\u4ece5\u63d0\u5347\u81f322\uff0c\u5355\u4f4d\u8bf7\u6c42\u6210\u672c\u964d\u4f4e65%<\/li>\n<\/ul>\n<h3>\u90e8\u7f72\u6a21\u5f0f\u9009\u62e9<\/h3>\n<table>\n<thead>\n<tr>\n<th>\u90e8\u7f72\u6a21\u5f0f<\/th>\n<th>\u5ef6\u8fdf<\/th>\n<th>\u6210\u672c<\/th>\n<th>\u9002\u7528\u573a\u666f<\/th>\n<th>\u4ee3\u8868\u65b9\u6848<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>\u516c\u6709\u4e91API<\/strong><\/td>\n<td>\u4e2d(1-3s)<\/td>\n<td>\u9ad8($0.01\/\u6b21)<\/td>\n<td>\u4f4e\u9891\u3001\u9ad8\u8d28\u91cf\u8981\u6c42<\/td>\n<td>GPT-4V API<\/td>\n<\/tr>\n<tr>\n<td><strong>\u4e13\u5c5e\u4e91\u5b9e\u4f8b<\/strong><\/td>\n<td>\u4e2d(0.5-2s)<\/td>\n<td>\u4e2d($5000\/\u6708)<\/td>\n<td>\u4e2d\u9891\u3001\u6570\u636e\u654f\u611f<\/td>\n<td>AWS SageMaker<\/td>\n<\/tr>\n<tr>\n<td><strong>\u8fb9\u7f18\u8bbe\u5907<\/strong><\/td>\n<td>\u4f4e(<1s)<\/td>\n<td>\u4f4e($2000\u4e00\u6b21\u6027)<\/td>\n<td>\u9ad8\u9891\u3001\u5b9e\u65f6\u6027\u8981\u6c42<\/td>\n<td>Jetson + TinyChart<\/td>\n<\/tr>\n<tr>\n<td><strong>\u6df7\u5408\u90e8\u7f72<\/strong><\/td>\n<td>\u53ef\u53d8<\/td>\n<td>\u4f18\u5316<\/td>\n<td>\u590d\u6742\u4e1a\u52a1<\/td>\n<td>\u6838\u5fc3\u56fe\u8868\u4e0a\u4e91\uff0c\u5b9e\u65f6\u56fe\u8868\u8fb9\u7f18<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>\u672a\u6765\u8d8b\u52bf\u4e0e\u6311\u6218<\/h2>\n<h3>\u6280\u672f\u6f14\u8fdb\u65b9\u5411<\/h3>\n<ul>\n<li><strong>\u591a\u6a21\u6001\u6df1\u5ea6\u878d\u5408<\/strong>\uff1a\u4ece\u201d\u89c6\u89c9\u7f16\u7801\u5668+\u8bed\u8a00\u6a21\u578b\u201d\u7684\u7b80\u5355\u62fc\u63a5\uff0c\u8f6c\u5411<strong>\u539f\u751f\u591a\u6a21\u6001\u67b6\u6784<\/strong>\uff0c\u5982Gemini\u7684Pathways\u7cfb\u7edf\uff0c\u5b9e\u73b0\u66f4\u9ad8\u6548\u7684\u8de8\u6a21\u6001\u63a8\u7406<\/li>\n<li><strong>\u81ea\u76d1\u7763\u5b66\u4e60\u5347\u7ea7<\/strong>\uff1a\u5229\u7528<strong>\u56fe\u8868\u5230\u4ee3\u7801<\/strong>\u7684\u751f\u6210\u4efb\u52a1\u4f5c\u4e3a\u9884\u8bad\u7ec3\u76ee\u6807\uff0c\u8ba9\u6a21\u578b\u5b66\u4e60\u7ed8\u56fe\u903b\u8f91\uff0c\u53cd\u5411\u5f3a\u5316\u7406\u89e3\u80fd\u529b<\/li>\n<li><strong>\u53ef\u89e3\u91ca\u6027\u589e\u5f3a<\/strong>\uff1a\u901a\u8fc7<strong>\u6ce8\u610f\u529b\u53ef\u89c6\u5316<\/strong>\u5c55\u793a\u6a21\u578b\u5173\u6ce8\u7684\u56fe\u8868\u533a\u57df\uff0c\u7ed3\u5408<strong>\u7a0b\u5e8f\u601d\u7ef4<\/strong>\u751f\u6210\u53ef\u9a8c\u8bc1\u7684\u63a8\u7406\u8def\u5f84<\/li>\n<\/ul>\n<h3>\u6838\u5fc3\u6311\u6218<\/h3>\n<ul>\n<li><strong>\u8bef\u5bfc\u6027\u53ef\u89c6\u5316\u7684\u8bc6\u522b<\/strong>\uff1a\u73b0\u6709\u6a21\u578b\u5bf9<strong>\u89c6\u89c9\u9677\u9631<\/strong>\uff08\u5982\u975e\u96f6\u8d77\u70b9\u5750\u6807\u8f74\u3001\u9762\u79ef\u8bef\u5bfc\uff09\u654f\u611f\u5ea6\u4e0d\u8db3\u30022025\u5e74\u7814\u7a76\u53d1\u73b0\uff0c\u5f53Y\u8f74\u88ab\u622a\u65ad\u65f6\uff0c\u6a21\u578b\u51c6\u786e\u7387\u4ece85%\u9aa4\u964d\u81f342%\u3002\u89e3\u51b3\u65b9\u6848\u5305\u62ec\uff1a\n<ul>\n<li>\u5728\u8bad\u7ec3\u96c6\u4e2d\u6ce8\u5165<strong>\u5bf9\u6297\u6837\u672c<\/strong>\uff0c\u6545\u610f\u52a0\u5165\u8bef\u5bfc\u6027\u8bbe\u8ba1<\/li>\n<li>\u5f15\u5165<strong>\u6279\u5224\u6027\u5934<\/strong>\uff08Critical Head\uff09\uff0c\u4e13\u95e8\u5224\u65ad\u56fe\u8868\u662f\u5426\u5b58\u5728\u89c6\u89c9\u64cd\u7eb5<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u957f\u5e8f\u5217\u56fe\u8868\u7406\u89e3<\/strong>\uff1a\u5305\u542b50+\u6570\u636e\u70b9\u7684\u590d\u6742\u56fe\u8868\uff0c\u6216\u957f\u8fbe10\u9875\u7684\u8d22\u62a5\u56fe\u8868\u96c6\uff0c\u89c6\u89c9\u4ee4\u724c\u6570\u8fc7\u4e07\uff0c\u5bfc\u81f4\u8ba1\u7b97\u590d\u6742\u5ea6\u9ad8\u3002\u6700\u65b0\u8fdb\u5c55\uff1a\n<ul>\n<li><strong>LongVLM\u67b6\u6784<\/strong>\uff1a\u91c7\u7528<strong>\u73af\u5f62\u6ce8\u610f\u529b<\/strong>\uff08Ring Attention\uff09\uff0c\u5c06\u8ba1\u7b97\u590d\u6742\u5ea6\u4eceO(n\u00b2)\u964d\u81f3O(n)<\/li>\n<li><strong>\u5206\u5c42\u5904\u7406<\/strong>\uff1a\u5148\u63d0\u53d6\u56fe\u8868\u5927\u7eb2\uff08\u6807\u9898\u3001\u8f74\u6807\u7b7e\uff09\uff0c\u518d\u6309\u9700\u653e\u5927\u7ec6\u8282\u533a\u57df\uff0c\u7c7b\u4f3c\u4eba\u7c7b\u201d\u5148\u6574\u4f53\u540e\u5c40\u90e8\u201d\u7684\u89c2\u5bdf\u65b9\u5f0f<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u9886\u57df\u81ea\u9002\u5e94<\/strong>\uff1a\u533b\u7597\u3001\u91d1\u878d\u7b49\u4e13\u4e1a\u9886\u57df\u7684\u56fe\u8868\u5305\u542b\u5927\u91cf\u672f\u8bed\u548c\u7279\u5b9a\u89c4\u8303\u3002\u5fae\u8c03\u65b9\u6848\u5305\u62ec\uff1a\n<ul>\n<li><strong>LoRA+Adapter\u6df7\u5408\u5fae\u8c03<\/strong>\uff1a\u51bb\u7ed3\u4e3b\u5e72\u7f51\u7edc\uff0c\u4ec5\u8bad\u7ec3\u9886\u57df\u9002\u914d\u5668\uff0c1\u5c0f\u65f6\u5b8c\u6210\u91d1\u878d\u9886\u57df\u9002\u914d<\/li>\n<li><strong>\u68c0\u7d22\u589e\u5f3a\u751f\u6210\uff08RAG\uff09<\/strong>\u200d \uff1a\u7ed3\u5408\u77e5\u8bc6\u5e93\u68c0\u7d22\u4e13\u4e1a\u672f\u8bed\u89e3\u91ca\uff0c\u63d0\u5347\u7b54\u6848\u4e13\u4e1a\u6027<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>\u5927\u6a21\u578b\u5728\u56fe\u8868\u7406\u89e3\u9886\u57df\u5df2\u5b9e\u73b0\u4ece\u201d\u80fd\u7528\u201d\u5230\u201d\u597d\u7528\u201d\u7684\u8de8\u8d8a\u3002\u95ed\u6e90\u6a21\u578b\u5982Gemini 1.5 Pro\u5728\u4e13\u4e1a\u4efb\u52a1\u4e0a\u63a5\u8fd1\u4eba\u7c7b\u4e13\u5bb6\u6c34\u5e73\uff0c\u5f00\u6e90\u6a21\u578b\u5982ChartVLM\u5728\u7279\u5b9a\u573a\u666f\u6027\u4ef7\u6bd4\u7a81\u51fa\u3002\u6280\u672f\u6808\u5df2\u4ece\u5b9e\u9a8c\u5ba4\u8d70\u5411\u751f\u4ea7\u7ebf\uff0cvLLM\u3001\u91cf\u5316\u3001\u8fb9\u7f18\u90e8\u7f72\u7b49\u5de5\u5177\u94fe\u6210\u719f\uff0c\u6210\u672c\u53ef\u63a7\u3002<\/p>\n<p>\u7136\u800c\uff0c<strong>\u6279\u5224\u6027\u601d\u7ef4<\/strong>\u4e0e<strong>\u9886\u57df\u6df1\u5ea6<\/strong>\u4ecd\u662f\u77ed\u677f\u3002\u672a\u67652-3\u5e74\uff0c\u968f\u7740\u81ea\u76d1\u7763\u5b66\u4e60\u8303\u5f0f\u7684\u5347\u7ea7\u548c\u8ba1\u7b97\u6548\u7387\u7684\u6301\u7eed\u4f18\u5316\uff0c\u56fe\u8868\u7406\u89e3\u5c06\u50cf\u4eca\u5929\u7684OCR\u4e00\u6837\u666e\u53ca\uff0c\u6210\u4e3a\u6bcf\u4e2a\u6570\u636e\u5206\u6790\u5e73\u53f0\u7684\u6807\u914d\u529f\u80fd\u3002\u5c4a\u65f6\uff0c\u201d\u4eba\u4eba\u90fd\u662f\u6570\u636e\u5206\u6790\u5e08\u201d\u7684\u613f\u666f\u5c06\u771f\u6b63\u843d\u5730\u2014\u2014\u53ea\u9700\u4e0a\u4f20\u56fe\u8868\uff0cAI\u5373\u53ef\u6210\u4e3a\u60a8\u7684\u667a\u80fd\u6570\u636e\u52a9\u624b\uff0c\u63ed\u793a\u6570\u636e\u80cc\u540e\u7684\u6545\u4e8b\u3002<\/p>\n<h2>\u5982\u4f55\u9009\u62e9\u9002\u5408\u7684\u65b9\u6848<\/h2>\n<table>\n<thead>\n<tr>\n<th>\u4f7f\u7528\u573a\u666f<\/th>\n<th>\u63a8\u8350\u6a21\u578b<\/th>\n<th>\u90e8\u7f72\u65b9\u5f0f<\/th>\n<th>\u9884\u4f30\u6210\u672c<\/th>\n<th>\u4e0a\u624b\u96be\u5ea6<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>\u4e2a\u4eba\u5b66\u4e60\u3001\u8f7b\u91cf\u5206\u6790<\/td>\n<td>ChartAssistant<\/td>\n<td>\u672c\u5730Docker<\/td>\n<td>\u514d\u8d39<\/td>\n<td>\u2b50\u2b50<\/td>\n<\/tr>\n<tr>\n<td>\u4e2d\u5c0f\u4f01\u4e1a\u3001\u6570\u636e\u770b\u677f<\/td>\n<td>ChartVLM<\/td>\n<td>\u4e91\u865a\u62df\u673a<\/td>\n<td>$500\/\u6708<\/td>\n<td>\u2b50\u2b50\u2b50<\/td>\n<\/tr>\n<tr>\n<td>\u91d1\u878d\u98ce\u63a7\u3001\u79d1\u7814\u5206\u6790<\/td>\n<td>Gemini 1.5 Pro<\/td>\n<td>API\u8c03\u7528<\/td>\n<td>\u6309\u91cf\u8ba1\u8d39<\/td>\n<td>\u2b50<\/td>\n<\/tr>\n<tr>\n<td>\u5de5\u4e1a\u8d28\u68c0\u3001\u5b9e\u65f6\u76d1\u6d4b<\/td>\n<td>TinyChart<\/td>\n<td>\u8fb9\u7f18\u8bbe\u5907<\/td>\n<td>$2000\u4e00\u6b21\u6027<\/td>\n<td>\u2b50\u2b50\u2b50\u2b50<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><strong>\u5feb\u901f\u542f\u52a8\u5efa\u8bae<\/strong>\uff1a\u4eceChartAssistant\u7684Hugging Face Demo\u5f00\u59cb\uff0c\u4f53\u9a8c\u57fa\u7840\u529f\u80fd\uff1b\u5982\u9700\u66f4\u9ad8\u7cbe\u5ea6\uff0c\u518d\u8003\u8651\u5fae\u8c03ChartVLM\u6216\u63a5\u5165\u5546\u4e1aAPI\u3002\u56fe\u8868\u7406\u89e3\u7684\u65f6\u4ee3\u5df2\u6765\uff0c\u5173\u952e\u5728\u4e8e\u627e\u5230\u9002\u5408\u60a8\u9700\u6c42\u7684\u6280\u672f\u8def\u5f84\u3002<\/p>","protected":false},"excerpt":{"rendered":"<p>\u5728\u6570\u636e\u9a71\u52a8\u7684\u65f6\u4ee3\uff0c\u56fe\u8868\u5df2\u6210\u4e3a\u4fe1\u606f\u4f20\u9012\u7684\u6838\u5fc3\u5a92\u4ecb\u3002\u8ba9\u673a\u5668\u771f\u6b63\u201d\u8bfb\u61c2\u201d\u56fe\u8868\u2014\u2014\u4e0d\u4ec5\u8bc6\u522b\u56fe\u5f62\u5143\u7d20\uff0c\u66f4\u8981\u7406\u89e3\u6570\u636e\u903b\u8f91\u3001\u6d1e\u5bdf\u8d8b\u52bf\u89c4\u5f8b\u3001\u56de\u7b54\u590d\u6742\u95ee\u9898\u2014\u2014\u4e00\u76f4\u662f\u4eba\u5de5\u667a\u80fd\u9886\u57df\u7684\u91cd\u5927\u6311\u6218\u3002\u4f20\u7edf\u65b9\u6cd5\u4f9d\u8d56OCR\uff08\u5149\u5b66\u5b57\u7b26\u8bc6\u522b\uff09\u548c\u89c4\u5219\u5f15\u64ce\uff0c\u6d41\u7a0b\u7e41\u7410\u4e14\u9c81\u68d2\u6027\u5dee\u30022023\u5e74\u4ee5\u6765\uff0c\u968f\u7740GPT-4V\u3001Gemini\u7b49\u591a\u6a21\u6001\u5927\u6a21\u578b\u7684\u5d1b\u8d77\uff0c\u56fe\u8868\u7406\u89e3\u6280\u672f\u8fce\u6765\u4e86\u9769\u547d\u6027\u7a81\u7834\u3002 \u622a\u81f32025\u5e74\uff0c\u89c6\u89c9\u8bed\u8a00\u5927\u6a21\u578b\uff08Vision-Language Models, VLMs\uff09\u5df2\u80fd\u5b9e\u73b0\u7aef\u5230\u7aef\u7684\u56fe\u8868\u89e3\u6790\uff0c\u4ece\u50cf\u7d20\u7ea7\u89c6\u89c9\u611f\u77e5\u5230\u8bed\u4e49\u7ea7\u903b\u8f91\u63a8\u7406\uff0c\u5c55\u73b0\u51fa\u63a5\u8fd1\u4eba\u7c7b\u4e13\u5bb6\u7684\u7406\u89e3\u80fd\u529b\u3002\u672c\u6587\u5c06\u6df1\u5ea6\u62c6\u89e3\u8fd9\u4e00\u6280\u672f\u5947\u8ff9\u80cc\u540e\u7684\u5de5\u7a0b\u5b9e\u8df5\u4e0e\u79d1\u5b66\u539f\u7406\u3002 \u6838\u5fc3\u6280\u672f\u6f14\u8fdb\uff1a\u4ece\u591a\u9636\u6bb5\u6d41\u6c34\u7ebf\u5230\u7aef\u5230\u7aef\u667a\u80fd \u4f20\u7edf\u65b9\u6cd5\u7684\u5c40\u9650\u6027 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