{"id":89766,"date":"2026-08-03T17:17:02","date_gmt":"2026-08-03T09:17:02","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/89766.html"},"modified":"2026-08-03T17:17:02","modified_gmt":"2026-08-03T09:17:02","slug":"%e8%ae%ba%e6%96%87%e9%98%85%e8%af%bb%e7%ac%94%e8%ae%b0-videoseeker-%e9%80%9a%e8%bf%87%e5%8e%9f%e7%94%9f%e6%99%ba%e8%83%bd%e4%bd%93%e5%b7%a5%e5%85%b7%e8%b0%83%e7%94%a8%e6%bf%80%e5%8a%b1%e5%ae%9e","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/89766.html","title":{"rendered":"\u8bba\u6587\u9605\u8bfb\u7b14\u8bb0 | VideoSeeker: \u901a\u8fc7\u539f\u751f\u667a\u80fd\u4f53\u5de5\u5177\u8c03\u7528\u6fc0\u52b1\u5b9e\u4f8b\u7ea7\u89c6\u9891\u7406\u89e3"},"content":{"rendered":"<h2>VideoSeeker: Incentivizing Instance-level Video Understanding via Native Agentic Tool Invocation<\/h2>\n<ul>\n<li>\u9879\u76ee\u4e3b\u9875: https:\/\/gaotiexinqu.github.io\/VideoSeeker\/<\/li>\n<\/ul>\n<h3>\u4e00\u3001Motivation<\/h3>\n<p>\u5f53\u524d\u5927\u578b\u89c6\u89c9\u8bed\u8a00\u6a21\u578b&#xff08;LVLMs&#xff09;\u5728\u89c6\u9891\u7406\u89e3\u65b9\u9762\u5df2\u53d6\u5f97\u663e\u8457\u8fdb\u5c55&#xff0c;\u4f46\u5728\u9700\u8981\u5b9e\u4f8b\u7ea7\u7cbe\u786e\u65f6\u7a7a\u5b9a\u4f4d\u7684\u4efb\u52a1\u4e0a\u4ecd\u9762\u4e34\u4e24\u4e2a\u6838\u5fc3\u74f6\u9888&#xff1a;<\/p>\n<p>1. \u89c6\u89c9\u611f\u77e5\u4e0e\u8bed\u8a00\u63a8\u7406\u7684\u8131\u8026<\/p>\n<p>\u73b0\u6709\u65b9\u6cd5\u5927\u591a\u5c06\u63a8\u7406\u8fc7\u7a0b\u56f4\u7ed5\u8bed\u8a00\u5c55\u5f00&#xff0c;\u800c\u975e\u76f4\u63a5\u57fa\u4e8e\u89c6\u89c9\u8bc1\u636e\u3002\u8fd9\u79cd&#034;\u8bed\u8a00\u4e2d\u5fc3&#034;\u7684\u8303\u5f0f\u5728\u957f\u89c6\u9891\u573a\u666f\u4e0b\u5bb9\u6613\u4ea7\u751f\u5e7b\u89c9\u3002\u6b64\u5916&#xff0c;\u5e7f\u6cdb\u91c7\u7528\u7684\u5355\u6b21\u5747\u5300\u91c7\u6837\u7b56\u7565\u5c5e\u4e8e\u88ab\u52a8\u611f\u77e5\u673a\u5236&#xff0c;\u65e0\u6cd5\u81ea\u9002\u5e94\u5730\u6355\u83b7\u5173\u952e\u89c6\u89c9\u8bc1\u636e&#xff0c;\u5bfc\u81f4\u7ec6\u7c92\u5ea6\u5b9a\u4f4d\u4efb\u52a1&#xff08;\u5982&#034;\u67d0\u4eba\u7b2c\u4e8c\u6b21\u51fa\u73b0\u662f\u4ec0\u4e48\u65f6\u5019&#034;&#xff09;\u8868\u73b0\u4e0d\u4f73\u3002<\/p>\n<p>2. \u6587\u672c\u67e5\u8be2\u7684\u4ea4\u4e92\u5c40\u9650\u6027<\/p>\n<p>\u73b0\u6709\u65b9\u6cd5\u548c\u57fa\u51c6\u6d4b\u8bd5\u4e3b\u8981\u5173\u6ce8\u6574\u4f53\u89c6\u9891\u7406\u89e3&#xff0c;\u5f3a\u8c03\u5168\u5c40\u8bed\u4e49\u548c\u7c97\u7c92\u5ea6\u4e8b\u4ef6&#xff0c;\u7f3a\u4e4f\u5bf9\u7279\u5b9a\u5b9e\u4f8b\u7684\u7ec6\u7c92\u5ea6\u65f6\u7a7a\u5b9a\u4f4d\u4e0e\u63a8\u7406\u80fd\u529b\u3002\u7528\u6237\u53ea\u80fd\u901a\u8fc7\u5197\u957f\u7684\u6587\u672c\u63cf\u8ff0\u6765\u6307\u5b9a\u76ee\u6807&#xff08;\u5982&#034;\u821e\u53f0\u4e0a\u4ece\u5de6\u6570\u7b2c\u4e03\u4e2a\u4eba&#034;&#xff09;&#xff0c;\u4ea4\u4e92\u6548\u7387\u4f4e\u4e0b&#xff0c;\u7528\u6237\u4f53\u9a8c\u5dee\u3002<\/p>\n<p>\u6838\u5fc3\u6d1e\u5bdf&#xff1a;\u89c6\u89c9\u63d0\u793a&#xff08;Visual Prompts&#xff09;\u80fd\u8ba9\u7528\u6237\u76f4\u63a5\u5728\u89c6\u9891\u5e27\u4e0a\u6807\u6ce8\u76ee\u6807\u533a\u57df&#xff0c;\u5b9e\u73b0\u66f4\u7cbe\u786e\u7684\u7a7a\u95f4\u548c\u65f6\u95f4\u5f15\u7528&#xff1b;\u540c\u65f6&#xff0c;\u8d4b\u4e88\u6a21\u578b\u4e3b\u52a8\u611f\u77e5\u80fd\u529b&#xff08;Agentic Reasoning&#xff09;&#xff0c;\u8ba9\u6a21\u578b\u50cf\u4eba\u7c7b\u4e00\u6837&#034;\u5148\u5168\u5c40\u6d4f\u89c8&#xff0c;\u518d\u5c40\u90e8\u7cbe\u8bfb&#034;&#xff0c;\u53ef\u4ee5\u6839\u636e\u9700\u8981\u52a8\u6001\u83b7\u53d6\u89c6\u89c9\u8bc1\u636e\u3002<\/p>\n<hr \/>\n<h3>\u4e8c\u3001Related Work<\/h3>\n<p>\u672c\u6587\u7684\u76f8\u5173\u5de5\u4f5c\u4e3b\u8981\u6d89\u53ca\u4e24\u4e2a\u65b9\u5411&#xff1a;<\/p>\n<h4>2.1 \u89c6\u89c9\u8bed\u8a00\u6a21\u578b\u7684\u5f3a\u5316\u5b66\u4e60<\/h4>\n<p>\u53d7 OpenAI o1 \u548c DeepSeek-R1 \u7684\u542f\u53d1&#xff0c;\u8fd1\u671f\u7814\u7a76\u5c06 GRPO \u5f0f\u7684\u5f3a\u5316\u5b66\u4e60\u4ece\u7eaf\u6587\u672c\u63a8\u7406\u6269\u5c55\u5230\u591a\u6a21\u6001\u9886\u57df\u3002\u4ee3\u8868\u6027\u5de5\u4f5c\u5305\u62ec&#xff1a;<\/p>\n<ul>\n<li>\u56fe\u50cf\u9886\u57df: Perception-R1 \u5229\u7528 IoU \u4f5c\u4e3a\u5956\u52b1\u4fe1\u53f7\u6539\u8fdb\u5b9a\u4f4d&#xff0c;DeepEyes \u901a\u8fc7 RL \u9f13\u52b1\u6a21\u578b\u8c03\u7528\u89c6\u89c9\u5de5\u5177<\/li>\n<li>\u89c6\u9891\u9886\u57df: Video-R1\u3001VideoChat-R1\u3001VideoRFT \u7b49\u805a\u7126\u89c6\u9891 QA \u548c\u65f6\u5e8f\u5b9a\u4f4d<\/li>\n<li>\u5c40\u9650\u6027: \u8fd9\u4e9b\u65b9\u6cd5\u4ecd\u4f9d\u8d56\u6587\u672c\u94fe\u5f0f\u63a8\u7406&#xff08;CoT&#xff09;&#xff0c;\u672c\u8d28\u4e0a\u662f&#034;\u8bed\u8a00\u4e2d\u5fc3&#034;\u7684&#xff0c;\u5728\u957f\u89c6\u9891\u573a\u666f\u4e0b\u5bb9\u6613\u4ea7\u751f\u5e7b\u89c9<\/li>\n<\/ul>\n<h4>2.2 \u5de5\u5177\u589e\u5f3a\u7684\u667a\u80fd\u4f53\u89c6\u89c9\u8bed\u8a00\u6a21\u578b<\/h4>\n<p>\u8fd1\u671f\u5de5\u4f5c\u8868\u660e&#xff0c;\u4e3a\u6a21\u578b\u914d\u5907\u5916\u90e8\u5de5\u5177\u80fd\u663e\u8457\u589e\u5f3a\u611f\u77e5\u80fd\u529b&#xff1a;<\/p>\n<ul>\n<li>\u56fe\u50cf\u9886\u57df: PixelReasoner\u3001DeepEyesV2 \u7b49\u8ba9\u6a21\u578b&#034;\u7528\u56fe\u50cf\u601d\u8003&#034;<\/li>\n<li>\u89c6\u9891\u9886\u57df: LongVT \u63d0\u51fa\u539f\u751f\u65f6\u5e8f\u68c0\u7d22\u63a8\u7406&#xff0c;VITAL \u6784\u5efa\u89c6\u89c9\u5de5\u5177\u7bb1\u5141\u8bb8\u6a21\u578b\u6309\u9700\u5bc6\u96c6\u91c7\u6837<\/li>\n<\/ul>\n<p>VideoSeeker \u7684\u5dee\u5f02\u5316\u5b9a\u4f4d&#xff1a;&#xff08;1&#xff09;\u805a\u7126\u5b9e\u4f8b\u7ea7\u89c6\u9891\u7406\u89e3&#xff0c;\u800c\u975e\u6574\u4f53\u8bed\u4e49\u5efa\u6a21&#xff1b;&#xff08;2&#xff09;\u91c7\u7528\u89c6\u89c9\u63d0\u793a&#xff08;\u6846\u3001\u70b9\u3001\u63a9\u7801\u7b49&#xff09;\u800c\u975e\u7eaf\u6587\u672c\u67e5\u8be2&#xff1b;&#xff08;3&#xff09;\u63d0\u51fa\u5168\u81ea\u52a8\u6570\u636e\u751f\u6210\u7ba1\u7ebf&#xff0c;\u5e76\u901a\u8fc7\u4e24\u9636\u6bb5\u8bad\u7ec3\u5c06\u5de5\u5177\u8c03\u7528\u80fd\u529b\u5185\u5316\u5230\u6a21\u578b\u4e2d\u3002<\/p>\n<h3>\u4e09\u3001Method<\/h3>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260803091655-6a705c877f143.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<h4>3.1 \u4efb\u52a1\u5b9a\u4e49\u4e0e\u73af\u5883\u4ea4\u4e92<\/h4>\n<p>\u7ed9\u5b9a\u67e5\u8be2 Q\u3001\u89c6\u89c9\u63d0\u793a\u5e27 F_vp \u548c\u4efb\u610f\u957f\u5ea6\u7684\u89c6\u9891 V&#xff0c;\u76ee\u6807\u662f\u9488\u5bf9 F_vp \u6240\u6307\u793a\u7684\u7279\u5b9a\u5b9e\u4f8b\u51c6\u786e\u56de\u7b54\u67e5\u8be2 Q\u3002<\/p>\n<p>\u6a21\u578b\u88ab\u5efa\u6a21\u4e3a\u4e00\u4e2a\u667a\u80fd\u4f53&#xff0c;\u914d\u5907\u611f\u77e5\u5de5\u5177\u96c6 T &#061; {view_visual_prompt, crop_video}&#xff1a;<\/p>\n<ul>\n<li>view_visual_prompt: \u6301\u7eed\u63d0\u4f9b\u89c6\u89c9\u63d0\u793a\u5e27&#xff0c;\u4f5c\u4e3a\u76ee\u6807\u5b9e\u4f8b\u5916\u89c2\u7684\u8ba4\u77e5\u951a\u70b9<\/li>\n<li>crop_video: \u8d4b\u4e88\u6a21\u578b\u7ec6\u7c92\u5ea6\u5c40\u90e8\u89c2\u5bdf\u80fd\u529b&#xff0c;\u53ef\u4e3b\u52a8\u7b5b\u9009\u5173\u952e\u5e27\u5e76\u53bb\u9664\u5197\u4f59\u4fe1\u606f<\/li>\n<\/ul>\n<p>\u4ea4\u4e92\u8fc7\u7a0b\u4e3a\u591a\u8f6e\u5faa\u73af&#xff1a;\u6a21\u578b\u751f\u6210\u54cd\u5e94 \u2192 \u5982\u5305\u542b\u5de5\u5177\u8c03\u7528\u5219\u6267\u884c\u5de5\u5177\u5e76\u5c06\u7ed3\u679c\u8ffd\u52a0\u5230\u4e0a\u4e0b\u6587 \u2192 \u5982\u5305\u542b\u7b54\u6848\u5219\u7ec8\u6b62\u3002\u8fd9\u79cd&#034;\u4e3b\u52a8\u611f\u77e5 \u2192 \u5c40\u90e8\u653e\u5927 \u2192 \u8bc1\u636e\u63a8\u7406&#034;\u7684\u8ba4\u77e5\u5faa\u73af\u6a21\u62df\u4e86\u4eba\u7c7b\u9762\u5bf9\u590d\u6742\u89c6\u89c9\u573a\u666f\u65f6&#034;\u5148\u5168\u5c40\u6d4f\u89c8\u518d\u5c40\u90e8\u7cbe\u8bfb&#034;\u7684\u7b56\u7565\u3002<\/p>\n<h4>3.2 \u6570\u636e\u6784\u5efa<\/h4>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260803091656-6a705c88c64c7.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<p>\u63d0\u51fa\u56db\u9636\u6bb5\u5168\u81ea\u52a8\u6570\u636e\u5408\u6210\u7ba1\u7ebf&#xff0c;\u5c06\u4efb\u610f\u89c6\u9891 QA \u6570\u636e\u96c6\u8f6c\u5316\u4e3a\u89c6\u89c9\u63d0\u793a\u4f9d\u8d56\u7684 QA \u6570\u636e&#xff1a;<\/p>\n<table>\n<tr>\u9636\u6bb5\u65b9\u6cd5\u529f\u80fd\u4fdd\u7559\u7387<\/tr>\n<tbody>\n<tr>\n<td>(1) \u4f4e\u6210\u672c\u6587\u672c\u8fc7\u6ee4<\/td>\n<td>GPT-4o<\/td>\n<td>\u5feb\u901f\u7b5b\u9664\u4e0d\u9002\u5408\u89c6\u89c9\u63d0\u793a\u7684 QA&#xff08;\u5982\u76f8\u673a\u8fd0\u52a8\u3001\u573a\u666f\u63cf\u8ff0\u3001\u8ba1\u6570\u9898\u7b49&#xff09;<\/td>\n<td>44.5%<\/td>\n<\/tr>\n<tr>\n<td>(2) \u89c6\u9891\u7ea7\u9a8c\u8bc1<\/td>\n<td>Gemini-3.1-Pro<\/td>\n<td>\u4e94\u6b65\u63a8\u7406&#xff1a;\u76ee\u6807\u63d0\u53d6&#043;\u552f\u4e00\u6027\u5224\u65ad&#043;\u8bed\u4e49\u6807\u7b7e\u751f\u6210&#043;\u65f6\u95f4\u7a97\u53e3\u5b9a\u4f4d&#043;QA \u6539\u5199<\/td>\n<td>32.9%<\/td>\n<\/tr>\n<tr>\n<td>(3) \u50cf\u7d20\u7ea7\u63a9\u7801\u751f\u6210<\/td>\n<td>SAM3<\/td>\n<td>\u57fa\u4e8e\u8bed\u4e49\u6807\u7b7e\u8fdb\u884c\u6587\u672c\u9a71\u52a8\u89c6\u9891\u5206\u5272&#xff0c;1fps \u91c7\u6837\u751f\u6210\u50cf\u7d20\u7ea7\u63a9\u7801<\/td>\n<td>27.9%<\/td>\n<\/tr>\n<tr>\n<td>(4) \u89c6\u89c9\u63d0\u793a\u6e32\u67d3<\/td>\n<td>\u5747\u5300\u91c7\u6837 8 \u79cd\u63d0\u793a\u7c7b\u578b<\/td>\n<td>\u5728\u5e27\u4e0a\u6e32\u67d3\u89c6\u89c9\u63d0\u793a&#xff0c;\u6539\u5199 QA \u4f7f\u5176\u4f9d\u8d56\u89c6\u89c9\u63d0\u793a<\/td>\n<td>27.8%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u6700\u7ec8\u6570\u636e\u6e90\u81ea LLaVA-Video-178K&#xff0c;\u4ece 147,245 \u4e2a\u6837\u672c\u4e2d\u7b5b\u9009\u5f97\u5230\u7ea6 40,929 \u4e2a\u9ad8\u8d28\u91cf\u6837\u672c\u3002<\/p>\n<p>SFT \u548c RL \u6570\u636e\u7b56\u5212&#xff1a;\u4f7f\u7528 Qwen3-VL-235B-A22B-Thinking \u901a\u8fc7\u62d2\u7edd\u91c7\u6837\u7b56\u7565\u751f\u6210\u591a\u8f6e\u5de5\u5177\u8c03\u7528\u8f68\u8ff9&#xff0c;\u7b5b\u9009\u6b63\u786e\u8f68\u8ff9\u83b7\u5f97 34.2k \u6837\u672c\u7528\u4e8e SFT&#xff0c;\u8fdb\u4e00\u6b65\u57fa\u4e8e pass-k \u8fc7\u6ee4\u5f97\u5230 4.1k \u6837\u672c\u7528\u4e8e GRPO \u8bad\u7ec3\u3002<\/p>\n<h4>3.3 \u8bad\u7ec3\u7b56\u7565<\/h4>\n<p>\u9636\u6bb5\u4e00&#xff1a;\u76d1\u7763\u5fae\u8c03&#xff08;SFT&#xff09;<\/p>\n<p>\u4f7f\u7528 34.2k \u9ad8\u8d28\u91cf\u8f68\u8ff9\u8bad\u7ec3&#xff0c;\u901a\u8fc7\u6807\u51c6\u81ea\u56de\u5f52\u4ea4\u53c9\u71b5\u635f\u5931\u4f18\u5316\u3002\u76ee\u6807\u662f\u8ba9\u6a21\u578b\u4e60\u5f97\u591a\u8f6e\u3001\u591a\u5c3a\u5ea6\u7684\u4e3b\u52a8\u611f\u77e5\u6a21\u5f0f&#xff0c;\u4e3a\u667a\u80fd\u4f53\u5f3a\u5316\u5b66\u4e60\u5960\u5b9a\u57fa\u7840\u3002<\/p>\n<p>\u9636\u6bb5\u4e8c&#xff1a;\u667a\u80fd\u4f53\u5f3a\u5316\u5b66\u4e60&#xff08;Agentic RL&#xff09;<\/p>\n<p>\u91c7\u7528 GRPO \u7b97\u6cd5&#xff0c;\u5c06\u6a21\u578b\u89c6\u4e3a\u80fd\u81ea\u4e3b\u4f7f\u7528\u5de5\u5177\u7684\u667a\u80fd\u4f53\u3002\u8bbe\u8ba1\u4e86\u4e09\u7ef4\u5ea6\u5956\u52b1\u51fd\u6570&#xff1a;<\/p>\n<li>\u7b54\u6848\u51c6\u786e\u6027 R_acc&#xff1a;\u4f7f\u7528 Qwen3-VL-235B \u4f5c\u4e3a\u8bc4\u5224\u8005&#xff0c;\u8f93\u51fa {1, 0.5, 0} \u8bc4\u5206<\/li>\n<li>\u683c\u5f0f\u5408\u89c4\u6027 R_format&#xff1a;\u9f13\u52b1\u6a21\u578b\u751f\u6210\u7ed3\u6784\u5316\u8f93\u51fa&#xff0c;\u4fbf\u4e8e\u89e3\u6790\u548c\u9a8c\u8bc1<\/li>\n<li>\u7b80\u7ea6\u6027 R_par&#xff1a;\u60e9\u7f5a\u8fc7\u591a\u7684\u5de5\u5177\u8c03\u7528\u6b21\u6570&#xff0c;\u9f13\u52b1\u9ad8\u6548\u63a8\u7406\u3002\u516c\u5f0f\u4e3a R_par &#061; max{0, 1 &#8211; \u03bb\u00b7N}<\/li>\n<p>\u7efc\u5408\u5956\u52b1&#xff1a;R &#061; \u03b1\u00b7R_acc &#043; \u03b2\u00b7R_format &#043; \u03b3\u00b7R_par&#xff08;\u03b1&#061;0.8, \u03b2&#061;0.15, \u03b3&#061;0.05&#xff09;<\/p>\n<hr \/>\n<h3>\u56db\u3001Experiments<\/h3>\n<h4>4.1 \u5b9e\u9a8c\u8bbe\u7f6e<\/h4>\n<ul>\n<li>\u57fa\u5ea7\u6a21\u578b: Qwen3-VL-4B \u548c Qwen3-VL-8B<\/li>\n<li>\u8bad\u7ec3\u57fa\u7840\u8bbe\u65bd: SFT \u4f7f\u7528 LLaMA-Factory&#xff0c;RL \u4f7f\u7528 verl&#xff0c;8 \u5f20 NVIDIA H800 GPU<\/li>\n<li>\u8bc4\u6d4b\u57fa\u51c6: V2P-Bench&#xff08;\u5b9e\u4f8b\u7ea7&#xff09;\u3001Video-MME\u3001LongVideoBench\u3001LongVT&#xff08;\u901a\u7528&#xff09;<\/li>\n<\/ul>\n<h4>4.2 \u4e3b\u8981\u7ed3\u679c<\/h4>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260803091658-6a705c8a56268.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<p>\u5b9e\u4f8b\u7ea7\u89c6\u9891\u7406\u89e3&#xff08;V2P-Bench&#xff09;&#xff1a;<\/p>\n<table>\n<tr>\u6a21\u578b\u5e73\u5747\u51c6\u786e\u7387\u76f8\u5bf9\u57fa\u7ebf\u63d0\u5347<\/tr>\n<tbody>\n<tr>\n<td>VideoSeeker-4B<\/td>\n<td>70.6%<\/td>\n<td>&#043;11.4%<\/td>\n<\/tr>\n<tr>\n<td>VideoSeeker-8B<\/td>\n<td>74.5%<\/td>\n<td>&#043;13.7%<\/td>\n<\/tr>\n<tr>\n<td>GPT-4o<\/td>\n<td>65.4%<\/td>\n<td>&#8211;<\/td>\n<\/tr>\n<tr>\n<td>Gemini-2.5-Pro<\/td>\n<td>69.8%<\/td>\n<td>&#8211;<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>VideoSeeker-8B \u4ee5 74.5% \u7684\u5e73\u5747\u5206\u8d85\u8d8a\u4e86 GPT-4o \u548c Gemini-2.5-Pro&#xff0c;\u5728 12 \u4e2a\u8bc4\u4f30\u7ef4\u5ea6\u4e2d\u5927\u90e8\u5206\u53d6\u5f97\u6700\u4f18\u3002<\/p>\n<p>\u901a\u7528\u89c6\u9891\u7406\u89e3\u57fa\u51c6\u4e0a\u7684\u8fc1\u79fb\u6027&#xff1a;<br \/>\n<img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260803091659-6a705c8be3ca3.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<p>\u5c3d\u7ba1\u8bad\u7ec3\u6570\u636e\u5b8c\u5168\u6765\u81ea\u5b9e\u4f8b\u7ea7\u4efb\u52a1&#xff0c;VideoSeeker \u5728 Video-MME\u3001LongVideoBench\u3001LongVT \u4e09\u4e2a\u901a\u7528\u57fa\u51c6\u4e0a\u4ecd\u5206\u522b\u53d6\u5f97 &#043;3.2%&#xff08;4B&#xff09;\u548c &#043;3.3%&#xff08;8B&#xff09;\u7684\u5e73\u5747\u63d0\u5347&#xff0c;\u8868\u73b0\u51fa\u826f\u597d\u7684\u8de8\u4efb\u52a1\u6cdb\u5316\u80fd\u529b\u3002<\/p>\n<h4>4.3 \u6d88\u878d\u5b9e\u9a8c<\/h4>\n<p>\u5de5\u5177\u6d88\u878d&#xff1a;view_visual_prompt \u5355\u72ec\u4f7f\u7528\u63d0\u5347 8.6%&#xff0c;crop_video \u5355\u72ec\u63d0\u5347 2.9%&#xff0c;\u4e24\u8005\u7ec4\u5408\u63d0\u5347 13.7%&#xff0c;\u5448\u73b0\u8d85\u52a0\u6027\u534f\u540c\u6548\u5e94\u3002<\/p>\n<p>\u5956\u52b1\u6d88\u878d&#xff1a;\u4ec5\u7528 R_acc \u5f97 65.4%&#xff1b;\u52a0\u5165 R_format \u63d0\u5347\u81f3 73.1%&#xff1b;\u4e09\u7ef4\u5ea6\u7ec4\u5408\u8fbe\u5230\u6700\u4f18 74.5%&#xff0c;\u4e09\u8005\u5b58\u5728\u4e92\u8865\u6548\u5e94\u3002<\/p>\n<p>\u8bad\u7ec3\u9636\u6bb5\u6d88\u878d&#xff1a;SFT \u5355\u72ec\u8d21\u732e &#043;9.6%&#xff1b;\u96f6\u6837\u672c RL \u4e2d&#xff0c;\u5355\u8f6e RL \u4ec5\u63d0\u5347 1.8%&#xff0c;\u800c\u667a\u80fd\u4f53 RL \u63d0\u5347 5.1%&#xff0c;\u9a8c\u8bc1\u4e86\u667a\u80fd\u4f53\u8303\u5f0f\u662f\u6709\u6548 RL \u8bad\u7ec3\u7684\u5173\u952e\u4f7f\u80fd\u5668\u3002\u4e24\u9636\u6bb5\u7ea7\u8054\u8fbe\u5230\u6700\u4f18 74.5%\u3002<\/p>\n<h4>4.4 \u6df1\u5ea6\u5206\u6790<\/h4>\n<p>\u5f02\u6784\u84b8\u998f\u6096\u8bba&#xff1a;\u66f4\u5f3a\u7684\u6559\u5e08\u6a21\u578b\u4e0d\u4e00\u5b9a\u8bad\u7ec3\u51fa\u66f4\u5f3a\u7684\u5b66\u751f\u6a21\u578b\u3002Gemini-3.1-Pro \u4f5c\u4e3a\u6559\u5e08&#xff08;83.8%&#xff09;\u53cd\u800c\u4f7f\u5b66\u751f\u6a21\u578b\u6027\u80fd\u9000\u5316 19.1%&#xff0c;\u800c\u540c\u7cfb\u5217\u7684 Qwen3-VL-235B&#xff08;78.4%&#xff09;\u4ec5\u9000\u5316 8.0%\u3002\u540c\u6784\u84b8\u998f\u4e2d\u6559\u5e08\u4e0e\u5b66\u751f\u5171\u4eab\u76f8\u4f3c\u6a21\u5f0f&#xff0c;\u77e5\u8bc6\u4f20\u9012\u66f4\u9ad8\u6548\u3002<\/p>\n<p>\u5956\u52b1\u653b\u51fb\u95ee\u9898&#xff1a;\u591a\u9009\u9898\u6570\u636e\u4e0a\u7684 RL \u8bad\u7ec3\u5bfc\u81f4\u6027\u80fd\u66b4\u8dcc\u81f3 43.8%&#xff08;\u6a21\u578b\u5b66\u4f1a\u4e86\u968f\u673a\u731c\u6d4b&#xff09;&#xff0c;\u800c\u5f00\u653e\u5f0f\u95ee\u7b54 &#043; LLM \u8bc4\u5224\u7684\u7b56\u7565\u66f4\u9c81\u68d2&#xff08;74.5%&#xff09;\u3002<\/p>\n<p>\u63a8\u7406\u6548\u7387&#xff1a;VideoSeeker \u901a\u8fc7\u7cbe\u7b80\u7684\u5de5\u5177\u8c03\u7528\u7b56\u7565\u548c\u66f4\u7d27\u51d1\u7684\u63a8\u7406\u94fe&#xff0c;\u5728\u751f\u6210\u548c\u5de5\u5177\u8c03\u7528\u4e24\u4e2a\u9636\u6bb5\u90fd\u663e\u8457\u964d\u4f4e\u4e86\u63a8\u7406\u5f00\u9500\u3002<\/p>\n<hr \/>\n<h3>\u4e94\u3001Conclusion<\/h3>\n<p>VideoSeeker \u63d0\u51fa\u4e86\u4e00\u79cd\u667a\u80fd\u4f53\u8303\u5f0f&#xff0c;\u901a\u8fc7\u539f\u751f\u5de5\u5177\u8c03\u7528\u5b9e\u73b0\u5b9e\u4f8b\u7ea7\u89c6\u9891\u7406\u89e3\u3002\u5176\u6838\u5fc3\u8d21\u732e\u5305\u62ec&#xff1a;<\/p>\n<li>\u6709\u673a\u6574\u5408\u667a\u80fd\u4f53\u63a8\u7406\u4e0e\u5b9e\u4f8b\u7ea7\u89c6\u9891\u7406\u89e3&#xff0c;\u7a81\u7834\u6587\u672c\u67e5\u8be2\u5c40\u9650<\/li>\n<li>\u6784\u5efa\u56db\u9636\u6bb5\u5168\u81ea\u52a8\u6570\u636e\u5408\u6210\u7ba1\u7ebf&#xff0c;\u9ad8\u6548\u751f\u6210\u5927\u89c4\u6a21\u9ad8\u8d28\u91cf\u8bad\u7ec3\u6570\u636e<\/li>\n<li>\u4e24\u9636\u6bb5\u8bad\u7ec3\u7b56\u7565&#xff08;SFT &#043; Agentic RL&#xff09;\u5c06\u5de5\u5177\u8c03\u7528\u80fd\u529b\u5185\u5316\u5230\u6a21\u578b\u4e2d<\/li>\n<li>8B \u6a21\u578b\u5728 V2P-Bench \u4e0a\u8d85\u8d8a GPT-4o \u548c Gemini-2.5-Pro&#xff0c;\u540c\u65f6\u5728\u901a\u7528\u57fa\u51c6\u4e0a\u5c55\u73b0\u826f\u597d\u8fc1\u79fb\u6027<\/li>\n<hr \/>\n<h3>\u516d\u3001\u4e2a\u4eba\u601d\u8003<\/h3>\n<h4>\u4eae\u70b9<\/h4>\n<li>\n<p>\u89c6\u89c9\u63d0\u793a &#043; \u667a\u80fd\u4f53\u63a8\u7406\u7684\u7ed3\u5408\u975e\u5e38\u81ea\u7136\u3002\u7528\u89c6\u89c9\u63d0\u793a\u66ff\u4ee3\u5197\u957f\u6587\u672c\u63cf\u8ff0\u6765\u6307\u5b9a\u76ee\u6807\u5b9e\u4f8b&#xff0c;\u4e0d\u4ec5\u63d0\u5347\u4e86\u4ea4\u4e92\u6548\u7387&#xff0c;\u4e5f\u66f4\u7b26\u5408\u4eba\u7c7b\u76f4\u89c9\u3002\u6a21\u578b\u901a\u8fc7\u4e3b\u52a8\u8c03\u7528\u5de5\u5177&#034;\u770b\u4e00\u770b&#034;\u518d\u63a8\u7406&#xff0c;\u6a21\u62df\u4e86\u4eba\u7c7b&#034;\u5148\u626b\u4e00\u773c\u5168\u5c40&#xff0c;\u518d\u4ed4\u7ec6\u770b\u7ec6\u8282&#034;\u7684\u8ba4\u77e5\u7b56\u7565&#xff0c;\u8fd9\u6bd4\u5355\u6b21\u524d\u5411\u4f20\u64ad\u66f4\u5408\u7406\u3002<\/p>\n<\/li>\n<li>\n<p>\u6570\u636e\u6784\u5efa\u7ba1\u7ebf\u8bbe\u8ba1\u7cbe\u5de7\u3002\u56db\u9636\u6bb5\u7ba1\u7ebf\u4ece\u6587\u672c\u8fc7\u6ee4\u5230\u89c6\u9891\u9a8c\u8bc1\u518d\u5230\u63a9\u7801\u751f\u6210\u548c\u6e32\u67d3&#xff0c;\u9010\u6b65\u63d0\u9ad8\u6570\u636e\u8d28\u91cf\u3002\u7528\u8f7b\u91cf LLM \u505a\u6587\u672c\u9884\u7b5b &#043; \u5f3a\u5927 VLM \u505a\u89c6\u9891\u9a8c\u8bc1\u7684&#034;\u7531\u7c97\u5230\u7ec6&#034;\u7b56\u7565&#xff0c;\u6709\u6548\u5e73\u8861\u4e86\u6210\u672c\u548c\u8d28\u91cf\u3002\u8fd9\u5957\u7ba1\u7ebf\u7684\u81ea\u52a8\u5316\u7a0b\u5ea6\u5f88\u9ad8&#xff0c;\u53ef\u6269\u5c55\u5230\u5176\u4ed6\u6570\u636e\u6e90\u3002<\/p>\n<\/li>\n<li>\n<p>\u4e09\u7ef4\u5ea6\u5956\u52b1\u8bbe\u8ba1\u6709\u5de5\u7a0b\u6d1e\u5bdf\u3002\u7279\u522b\u662f\u7b80\u7ea6\u6027\u5956\u52b1\u7684\u5f15\u5165&#xff0c;\u9f13\u52b1\u6a21\u578b\u53ea\u5728\u9700\u8981\u989d\u5916\u8bc1\u636e\u65f6\u624d\u8c03\u7528\u5de5\u5177&#xff0c;\u907f\u514d\u4e86\u65e0\u610f\u4e49\u7684\u5de5\u5177\u6ee5\u7528&#xff0c;\u8fd9\u5728\u5b9e\u9645\u90e8\u7f72\u4e2d\u5bf9\u63a7\u5236\u63a8\u7406\u6210\u672c\u5f88\u91cd\u8981\u3002<\/p>\n<\/li>\n<h4>\u5c40\u9650\u4e0e\u601d\u8003<\/h4>\n<li>\n<p>\u5de5\u5177\u96c6\u8f83\u4e3a\u6709\u9650\u3002\u76ee\u524d\u4ec5\u6709 view_visual_prompt \u548c crop_video \u4e24\u4e2a\u5de5\u5177&#xff0c;\u672a\u6765\u53ef\u4ee5\u8003\u8651\u5f15\u5165\u76ee\u6807\u8ffd\u8e2a\u3001\u5149\u6d41\u5206\u6790\u3001\u5b9e\u4f8b\u5206\u5272\u7b49\u66f4\u4e30\u5bcc\u7684\u89c6\u89c9\u5de5\u5177&#xff0c;\u8fdb\u4e00\u6b65\u589e\u5f3a\u6a21\u578b\u7684\u4e3b\u52a8\u611f\u77e5\u80fd\u529b\u3002<\/p>\n<\/li>\n<li>\n<p>\u6570\u636e\u6e90\u4f9d\u8d56\u3002\u7ba1\u7ebf\u4f9d\u8d56 LLaVA-Video-178K \u4f5c\u4e3a\u6e90\u6570\u636e&#xff0c;\u53ef\u80fd\u7ee7\u627f\u5176\u9886\u57df\u504f\u5dee\u3002\u8bba\u6587\u4e2d 72.1% \u7684\u89c6\u9891\u6765\u81ea YouTube&#xff0c;\u9886\u57df\u8986\u76d6\u7684\u591a\u6837\u6027\u6709\u5f85\u63d0\u5347\u3002<\/p>\n<\/li>\n<li>\n<p>\u5f02\u6784\u84b8\u998f\u6096\u8bba\u503c\u5f97\u6df1\u5165\u63a2\u7d22\u3002\u8fd9\u4e00\u53d1\u73b0\u5bf9\u5927\u6a21\u578b\u77e5\u8bc6\u84b8\u998f\u7684\u5b9e\u8df5\u5177\u6709\u91cd\u8981\u542f\u793a&#xff1a;\u9009\u62e9\u6559\u5e08\u6a21\u578b\u65f6\u4e0d\u5e94\u5355\u7eaf\u8ffd\u6c42\u6700\u5f3a&#xff0c;\u800c\u8981\u8003\u8651\u4e0e\u5b66\u751f\u6a21\u578b\u7684\u67b6\u6784\u517c\u5bb9\u6027\u3002\u8fd9\u4e0e\u8fd1\u671f&#034;\u5c0f\u6a21\u578b\u81ea\u6211\u8fdb\u5316&#034;\u7684\u7814\u7a76\u65b9\u5411\u5f62\u6210\u6709\u8da3\u547c\u5e94\u3002<\/p>\n<\/li>\n<li>\n<p>\u89c6\u89c9\u63d0\u793a\u7684\u5b9e\u7528\u6027\u3002\u5728\u5b9e\u9645\u5e94\u7528\u4e2d&#xff0c;\u7528\u6237\u662f\u5426\u613f\u610f\u5728\u89c6\u9891\u5e27\u4e0a\u624b\u52a8\u6807\u6ce8\u76ee\u6807\u4ecd\u662f\u4e00\u4e2a\u5f00\u653e\u95ee\u9898\u3002\u672a\u6765\u53ef\u4ee5\u8003\u8651\u7ed3\u5408\u81ea\u7136\u8bed\u8a00\u63cf\u8ff0\u7684\u6a21\u7cca\u5339\u914d 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