{"id":98590,"date":"2026-09-01T07:00:23","date_gmt":"2026-08-31T23:00:23","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/98590.html"},"modified":"2026-09-01T07:00:23","modified_gmt":"2026-08-31T23:00:23","slug":"27%e5%b1%8a%e5%a4%a7%e6%a8%a1%e5%9e%8b%e9%9d%a2%e8%af%95%e5%87%86%e5%a4%87%ef%bc%88%e4%ba%94%e5%8d%81%e4%b8%83%ef%bc%89%ef%bc%9a%e5%a4%9a%e6%a8%a1%e6%80%81%e5%a4%a7%e6%a8%a1%e5%9e%8b%e8%af%84%e6%b5%8b","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/98590.html","title":{"rendered":"27\u5c4a\u5927\u6a21\u578b\u9762\u8bd5\u51c6\u5907\uff08\u4e94\u5341\u4e03\uff09\uff1a\u591a\u6a21\u6001\u5927\u6a21\u578b\u8bc4\u6d4b\u4e0e\u81ea\u52a8\u5316 Benchmark \u5de5\u7a0b\u2014\u2014\u4ece\u80fd\u529b taxonomy \u5230\u56de\u5f52\u5b88\u62a4"},"content":{"rendered":"

27\u5c4a\u5927\u6a21\u578b\u9762\u8bd5\u51c6\u5907（\u4e94\u5341\u4e03）：\u591a\u6a21\u6001\u5927\u6a21\u578b\u8bc4\u6d4b\u4e0e\u81ea\u52a8\u5316 Benchmark \u5de5\u7a0b\u2014\u2014\u4ece\u80fd\u529b taxonomy \u5230\u56de\u5f52\u5b88\u62a4<\/h2>\n

\u5f15\u8a00：\u4e0e\u4e0a\u4e00\u7bc7\u3001\u7cfb\u5217\u7684\u5173\u7cfb<\/h3>\n

\u4e0a\u4e00\u7bc7（\u4e94\u5341\u516d）\u6211\u4eec\u804a\u4e86\u300c\u5927\u6a21\u578b\u8bad\u63a8\u4e00\u4f53\u5316\u5de5\u7a0b\u300d，\u628a\u8bad\u7ec3\u4ea7\u7269\u7a33\u5b9a\u5730\u4ea4\u4ed8\u5230\u63a8\u7406\u4fa7；\u4f46\u8fd9\u53ea\u89e3\u51b3\u4e86\u4e00\u534a\u95ee\u9898\u2014\u2014\u4f60\u4ea4\u4ed8\u7684\u6a21\u578b\u5230\u5e95\u597d\u4e0d\u597d\u3001\u9000\u4e86\u591a\u5c11\u3001\u54ea\u7c7b\u6837\u672c\u5d29\u4e86，\u5fc5\u987b\u9760\u4e00\u5957\u8bc4\u6d4b\u5de5\u7a0b\u6765\u56de\u7b54\u3002\u5f80\u524d\u770b，（\u4e94\u5341\u4e09）\u8bb2\u4e86\u591a\u6a21\u6001\u63a8\u7406\u670d\u52a1\u5316\u3001（\u4e94\u5341\u4e94）\u8bb2\u4e86\u591a\u6a21\u6001 RAG \u5de5\u7a0b，\u672c\u7bc7\u628a\u5b83\u4eec\u6536\u53e3\u5230\u4e00\u4e2a\u5e38\u88ab\u5ffd\u89c6\u5374\u6709\u6781\u9ad8\u9762\u8bd5\u6743\u91cd\u7684\u73af\u8282：\u591a\u6a21\u6001\u5927\u6a21\u578b\u8bc4\u6d4b\u4e0e\u81ea\u52a8\u5316 Benchmark \u5de5\u7a0b\u3002<\/p>\n

\u4e3a\u4ec0\u4e48\u9762\u8bd5\u7231\u95ee\u8fd9\u4e2a？\u56e0\u4e3a\u4e1a\u754c\u771f\u5b9e\u75db\u70b9\u662f：\u5b66\u672f\u699c\u5355\u5237\u5f97\u9ad8，\u4e0a\u7ebf\u4e00\u6d4b\u5168\u9762\u5d29；\u4eca\u5929\u6539\u4e86\u4e00\u884c prompt，\u4e09\u5929\u524d\u7684 case \u6084\u6084\u9000\u5316\u4e86\u5374\u6ca1\u4eba\u77e5\u9053\u3002\u80fd\u642d\u4e00\u5957\u300c\u80fd\u529b taxonomy + \u81ea\u52a8\u5316\u8bc4\u6d4b + \u56de\u5f52\u95e8\u7981 + badcase \u6316\u6398\u300d\u7684\u4eba，\u6bd4\u53ea\u4f1a\u8dd1 MMBench \u5206\u6570\u7684\u4eba\u503c\u94b1\u5f97\u591a\u3002\u4e0b\u9762\u7528\u5de5\u7a0b\u89c6\u89d2\u628a\u8fd9\u56db\u5757\u62c6\u5f00\u3002<\/p>\n

\u591a\u6a21\u6001\u8bc4\u6d4b\u5de5\u7a0b\u603b\u67b6\u6784
\n+—————————————————————–+
\n| \u6a21\u578b (VLM) \u5236\u54c1 |
\n+—————————————————————–+
\n | |
\n +——–v———+ +———v———-+
\n | \u79bb\u7ebf\u8bc4\u6d4b Harness | | \u5728\u7ebf\u8bc4\u6d4b \/ \u5f71\u5b50 |
\n | (Benchmark \u81ea\u52a8\u5316)| | (A\/B + \u6d41\u91cf\u56de\u653e) |
\n +——–+———+ +———+———-+
\n | |
\n +——–v—————————-v———-+
\n | \u80fd\u529b Taxonomy \u4e0e \u6307\u6807\u5c42 |
\n | \u611f\u77e5\/OCR\/\u7a7a\u95f4\/\u8ba1\u6570\/\u63a8\u7406\/\u5e7b\u89c9\/\u5b89\u5168\/\u957f\u56fe\/\u89c6\u9891 |
\n +——————————–+—————–+
\n | |
\n +——–v———+ +———v———-+
\n | \u56de\u5f52\u6bd4\u5bf9 (diff) | | Badcase \u6316\u6398\u4e0e\u5f52\u56e0 |
\n | HEAD vs BASE | | \u805a\u7c7b + \u4eba\u5de5\u6807\u6ce8\u56de\u6d41 |
\n +——————+ +———————+
\n |
\n +——–v———+
\n | \u95e8\u7981 Gate (CI) |
\n | \u975e\u52a3\u5316\u624d\u653e\u884c |
\n +——————+<\/p>\n

\u7b2c\u4e00\u8282 \u80fd\u529b Taxonomy：\u5148\u628a"\u597d"\u62c6\u6210\u53ef\u6d4b\u7684\u7ef4\u5ea6<\/h3>\n

\u8bc4\u6d4b\u7684\u7b2c\u4e00\u6027\u539f\u7406\u662f：\u5148\u5b9a\u4e49\u7ef4\u5ea6，\u518d\u8c08\u5206\u6570\u3002\u5f88\u591a\u56e2\u961f\u4e00\u4e0a\u6765\u5c31\u8dd1\u603b\u5206，\u5206\u6570\u6389 0.3 \u5374\u5b8c\u5168\u4e0d\u77e5\u9053\u6389\u5728\u54ea\u3002\u4e00\u4e2a\u8d34\u8fd1\u5de5\u4e1a\u754c\u7684\u591a\u6a21\u6001\u80fd\u529b taxonomy \u901a\u5e38\u662f\u8fd9\u6837\u7684\u5206\u5c42：<\/p>\n\n\u7ef4\u5ea6\u4ee3\u8868\u80fd\u529b\u5178\u578b\u5931\u8d25\u6a21\u5f0f\u5e38\u7528\u6570\u636e\u96c6\/\u6784\u9020<\/tr>\n\n\n\n\n\n\n\n\n\n
\u57fa\u7840\u611f\u77e5<\/td>\n\u7269\u4f53\u8bc6\u522b\u3001\u5c5e\u6027\u3001\u573a\u666f<\/td>\n\u7ec6\u7c92\u5ea6\u6df7\u6dc6（\u5409\u5a03\u5a03 vs \u67f4\u72ac）<\/td>\nCOCO caption\u3001Visual Genome<\/td>\n<\/tr>\n
OCR \u4e0e\u6587\u6863<\/td>\n\u6587\u5b57\u63d0\u53d6\u3001\u8868\u683c\u3001\u516c\u5f0f<\/td>\n\u5c0f\u5b57\u6f0f\u8bfb\u3001\u8868\u683c\u7ed3\u6784\u9519<\/td>\nOCRBench\u3001DocVQA\u3001ChartQA<\/td>\n<\/tr>\n
\u7a7a\u95f4\u4e0e\u8ba1\u6570<\/td>\n\u76f8\u5bf9\u4f4d\u7f6e\u3001\u6570\u91cf<\/td>\n\u6570\u9519\u3001\u5de6\u53f3\u98a0\u5012<\/td>\n\u81ea\u5efa\u8ba1\u6570\u96c6\u3001SpatialEval<\/td>\n<\/tr>\n
\u8de8\u6a21\u6001\u63a8\u7406<\/td>\n\u56fe\u6587\u5bf9\u9f50\u63a8\u7406\u3001\u5bf9\u6bd4<\/td>\n\u770b\u56fe\u6807\u9519\u6570\u5b57\u5c31\u4e0b\u7ed3\u8bba<\/td>\nMMBench\u3001MMMU<\/td>\n<\/tr>\n
\u5e7b\u89c9<\/td>\n\u6307\u8ba4\u4e0d\u5b58\u5728\u7269\u4f53<\/td>\n\u80af\u5b9a\u5f0f\u7f16\u9020<\/td>\nPOPE\u3001HallusionBench<\/td>\n<\/tr>\n
\u5b89\u5168<\/td>\n\u8fdd\u7981\u5185\u5bb9\u3001\u504f\u89c1<\/td>\n\u8d8a\u72f1\u56fe\u8bf1\u5bfc<\/td>\n\u81ea\u5efa\u7ea2\u961f\u96c6<\/td>\n<\/tr>\n
\u957f\u56fe\/\u9ad8\u5206\u8fa8<\/td>\n\u5207\u56fe\u540e\u4fe1\u606f\u4e22\u5931<\/td>\n\u5ffd\u7565\u89d2\u843d\u7ec6\u8282<\/td>\n\u81ea\u5efa\u957f\u56fe\u96c6<\/td>\n<\/tr>\n
\u89c6\u9891<\/td>\n\u65f6\u5e8f\u3001\u52a8\u4f5c\u3001\u8ba1\u6570<\/td>\n\u5e27\u95f4\u6df7\u6dc6\u3001\u5ffd\u7565\u987a\u5e8f<\/td>\nMVBench\u3001Video-MME<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u5de5\u7a0b\u4e0a\u5efa\u8bae\u7528\u300c\u7ef4\u5ea6 \u00d7 \u6743\u91cd \u00d7 \u6837\u672c\u91cf\u300d\u7ec4\u6210\u4e00\u5f20\u80fd\u529b\u96f7\u8fbe，\u6bcf\u6b21\u53d1\u7248\u90fd\u4ea7\u51fa\u540c\u4e00\u5f20\u96f7\u8fbe，\u505a\u53ef\u89c6\u5316 diff\u2014\u2014\u8fd9\u6bd4\u4e00\u4e2a\u603b\u5206\u6709\u7528\u5341\u500d\u3002<\/p>\n

# \u80fd\u529b taxonomy \u7684\u6700\u5c0f\u914d\u7f6e<\/span>
\nTAXONOMY<\/span> =<\/span> {<\/span>
\n "perception"<\/span>:<\/span> {<\/span>"weight"<\/span>:<\/span> 0.15<\/span>,<\/span> "sets"<\/span>:<\/span> [<\/span>"coco_cap"<\/span>,<\/span> "vg"<\/span>]},<\/span>
\n "ocr"<\/span>:<\/span> {<\/span>"weight"<\/span>:<\/span> 0.15<\/span>,<\/span> "sets"<\/span>:<\/span> [<\/span>"ocrbench"<\/span>,<\/span> "docvqa"<\/span>]},<\/span>
\n "spatial"<\/span>:<\/span> {<\/span>"weight"<\/span>:<\/span> 0.10<\/span>,<\/span> "sets"<\/span>:<\/span> [<\/span>"spatial_eval"<\/span>]},<\/span>
\n "reasoning"<\/span>:<\/span> {<\/span>"weight"<\/span>:<\/span> 0.25<\/span>,<\/span> "sets"<\/span>:<\/span> [<\/span>"mmbench"<\/span>,<\/span> "mmmu"<\/span>]},<\/span>
\n "halluc"<\/span>:<\/span> {<\/span>"weight"<\/span>:<\/span> 0.15<\/span>,<\/span> "sets"<\/span>:<\/span> [<\/span>"pope"<\/span>,<\/span> "hallusion"<\/span>]},<\/span>
\n "safety"<\/span>:<\/span> {<\/span>"weight"<\/span>:<\/span> 0.10<\/span>,<\/span> "sets"<\/span>:<\/span> [<\/span>"redteam"<\/span>]},<\/span>
\n "longimg"<\/span>:<\/span> {<\/span>"weight"<\/span>:<\/span> 0.05<\/span>,<\/span> "sets"<\/span>:<\/span> [<\/span>"longimg"<\/span>]},<\/span>
\n "video"<\/span>:<\/span> {<\/span>"weight"<\/span>:<\/span> 0.05<\/span>,<\/span> "sets"<\/span>:<\/span> [<\/span>"mvbench"<\/span>]},<\/span>
\n}<\/span><\/p>\n

def<\/span> <\/span>aggregate<\/span>(<\/span>scores<\/span>:<\/span> dict<\/span>)<\/span> -><\/span> float<\/span>:<\/span>
\n # scores: {dim: acc}<\/span>
\n return<\/span> sum<\/span>(<\/span>TAXONOMY<\/span>[<\/span>d<\/span>][<\/span>"weight"<\/span>]<\/span> *<\/span> scores<\/span>[<\/span>d<\/span>]<\/span> for<\/span> d<\/span> in<\/span> TAXONOMY<\/span>)<\/span><\/p>\n

\u7b2c\u4e8c\u8282 \u79bb\u7ebf\u8bc4\u6d4b Harness：\u628a\u8dd1\u5206\u53d8\u6210\u53ef\u590d\u73b0\u7684\u6d41\u6c34\u7ebf<\/h3>\n

\u5b66\u672f\u8bc4\u6d4b\u811a\u672c\u5f80\u5f80\u300c\u80fd\u8dd1\u5c31\u884c\u300d，\u5de5\u7a0b\u5316\u8981\u7684\u662f\u786e\u5b9a\u6027\u3001\u53ef\u5e76\u884c\u3001\u53ef\u91cd\u653e\u3002\u4e00\u4e2a\u7a33\u5065 harness \u7684\u5173\u952e\u8bbe\u8ba1：<\/p>\n

  • \u6570\u636e\u96c6\u7248\u672c\u5316：\u6bcf\u4e2a benchmark \u9501\u5b9a commit \u6216 hash，\u907f\u514d\u300c\u540c\u4e2a MMBench \u4eca\u5929 82 \u660e\u5929 84\u300d\u3002<\/li>\n
  • \u63a8\u7406\u4e0e\u5224\u5206\u89e3\u8026：\u6a21\u578b\u53ea\u4ea7\u51fa\u539f\u59cb\u7b54\u6848（jsonl），\u5224\u5206\u5668\u72ec\u7acb\u8dd1，\u4fbf\u4e8e\u6362 judge（\u89c4\u5219 \/ \u5b57\u7b26\u4e32\u5339\u914d \/ LLM-as-Judge）\u3002<\/li>\n
  • \u591a\u6a21\u6001\u8f93\u5165\u7edf\u4e00：\u56fe\u7247\u8d70\u7edf\u4e00\u9884\u5904\u7406（resize \u7b56\u7565\u3001\u5207\u56fe\u53c2\u6570），\u548c\u7ebf\u4e0a serving \u7684 pre-processing \u5fc5\u987b\u4e00\u81f4，\u5426\u5219\u79bb\u7ebf\u9ad8\u5206\u3001\u7ebf\u4e0a\u4f4e\u5206\u3002<\/li>\n
  • \u5e76\u53d1\u4e0e\u91cd\u8bd5：IO \u9519\u8bef\u3001\u8d85\u65f6\u81ea\u52a8\u91cd\u8bd5，\u5931\u8d25\u6837\u672c\u5355\u72ec\u843d\u76d8，\u6700\u540e\u8865\u8dd1\u3002<\/li>\n

    import<\/span> <\/span>json<\/span>,<\/span> <\/span>concurrent.futures<\/span> <\/span>as<\/span> <\/span>cf<\/span><\/p>\n

    def<\/span> <\/span>run_one<\/span>(<\/span>sample<\/span>,<\/span> model<\/span>):<\/span>
    \n try<\/span>:<\/span>
    \n ans<\/span> =<\/span> model<\/span>.<\/span>generate<\/span>(<\/span>image<\/span>=<\/span>sample<\/span>[<\/span>"image"<\/span>],<\/span>
    \n prompt<\/span>=<\/span>sample<\/span>[<\/span>"question"<\/span>])<\/span>
    \n return<\/span> {<\/span>"id"<\/span>:<\/span> sample<\/span>[<\/span>"id"<\/span>],<\/span> "pred"<\/span>:<\/span> ans<\/span>,<\/span>
    \n "gold"<\/span>:<\/span> sample<\/span>[<\/span>"answer"<\/span>],<\/span> "ok"<\/span>:<\/span> True<\/span>}<\/span>
    \n except<\/span> Exception<\/span> as<\/span> e<\/span>:<\/span>
    \n return<\/span> {<\/span>"id"<\/span>:<\/span> sample<\/span>[<\/span>"id"<\/span>],<\/span> "pred"<\/span>:<\/span> None<\/span>,<\/span>
    \n "gold"<\/span>:<\/span> sample<\/span>[<\/span>"answer"<\/span>],<\/span> "ok"<\/span>:<\/span> False<\/span>,<\/span> "err"<\/span>:<\/span> str<\/span>(<\/span>e<\/span>)}<\/span><\/p>\n

    def<\/span> <\/span>evaluate<\/span>(<\/span>dataset<\/span>,<\/span> model<\/span>,<\/span> workers<\/span>=<\/span>16<\/span>):<\/span>
    \n results<\/span> =<\/span> []<\/span>
    \n with<\/span> cf<\/span>.<\/span>ThreadPoolExecutor<\/span>(<\/span>workers<\/span>)<\/span> as<\/span> ex<\/span>:<\/span>
    \n futs<\/span> =<\/span> [<\/span>ex<\/span>.<\/span>submit<\/span>(<\/span>run_one<\/span>,<\/span> s<\/span>,<\/span> model<\/span>)<\/span> for<\/span> s<\/span> in<\/span> dataset<\/span>]<\/span>
    \n for<\/span> f<\/span> in<\/span> cf<\/span>.<\/span>as_completed<\/span>(<\/span>futs<\/span>):<\/span>
    \n results<\/span>.<\/span>append<\/span>(<\/span>f<\/span>.<\/span>result<\/span>())<\/span>
    \n # \u5931\u8d25\u6837\u672c\u5355\u72ec\u5b58，\u540e\u7eed\u8865\u8dd1<\/span>
    \n failed<\/span> =<\/span> [<\/span>r<\/span> for<\/span> r<\/span> in<\/span> results<\/span> if<\/span> not<\/span> r<\/span>[<\/span>"ok"<\/span>]]<\/span>
    \n json<\/span>.<\/span>dump<\/span>(<\/span>failed<\/span>,<\/span> open<\/span>(<\/span>"failed.jsonl"<\/span>,<\/span> "w"<\/span>),<\/span> ensure_ascii<\/span>=<\/span>False<\/span>)<\/span>
    \n return<\/span> [<\/span>r<\/span> for<\/span> r<\/span> in<\/span> results<\/span> if<\/span> r<\/span>[<\/span>"ok"<\/span>]]<\/span><\/p>\n

    \u8fd9\u91cc\u6709\u4e00\u4e2a\u6781\u6613\u8e29\u7684\u5751：\u5224\u5206\u53e3\u5f84\u3002MMBench \u7528\u9009\u9879\u5b57\u6bcd，MMMU \u7528\u81ea\u7531\u6587\u672c，DocVQA \u7528\u6b63\u5219\u5f52\u4e00\u5316\u3002\u52a1\u5fc5\u4e3a\u6bcf\u4e2a\u6570\u636e\u96c6\u5199\u72ec\u7acb\u5f52\u4e00\u5316\u51fd\u6570，\u5426\u5219\u8de8\u96c6\u5bf9\u6bd4\u6beb\u65e0\u610f\u4e49\u3002<\/p>\n

    \u7b2c\u4e09\u8282 \u5e7b\u89c9\u4e0e\u5b89\u5168\u7684\u4e13\u9879\u8bc4\u6d4b<\/h3>\n

    \u591a\u6a21\u6001\u5e7b\u89c9\u662f\u5927\u6a21\u578b\u9762\u8bd5\u9ad8\u9891\u9898，\u5de5\u7a0b\u4e0a\u4e0d\u80fd\u53ea\u9760 POPE \u4e00\u4e2a\u6307\u6807\u3002\u5efa\u8bae\u7ec4\u5408\u4e09\u5c42：<\/p>\n

      \n
    • \u5bf9\u8c61\u7ea7：POPE（\u5b58\u5728\u6027\u4e8c\u5206\u7c7b）\u3001HallusionBench（\u89c6\u89c9\u9519\u89c9 + \u77e5\u8bc6\u9519\u89c9）\u3002<\/li>\n
    • \u63cf\u8ff0\u7ea7：\u8ba9\u6a21\u578b\u5199\u56fe\u6ce8，\u518d\u7528 LLM-as-Judge \u6bd4\u5bf9\u662f\u5426\u51fa\u73b0\u56fe\u4e2d\u6ca1\u6709\u7684\u5b9e\u4f53\u3002<\/li>\n
    • \u5f52\u56e0\u7ea7：\u6784\u9020\u300c\u56fe\u91cc\u660e\u660e\u6ca1\u6709 X，\u6545\u610f\u95ee\u6709\u6ca1\u6709 X\u300d\u7684\u5bf9\u6297\u96c6，\u7edf\u8ba1\u80af\u5b9a\u7387\u3002<\/li>\n<\/ul>\n

      \u5b89\u5168\u4fa7\u5219\u8981\u505a\u7ea2\u961f\u95ed\u73af：\u7528\u56fe\u50cf\u8bf1\u5bfc（\u5982\u5e26\u6587\u5b57\u7684\u56fe\u300c\u5ffd\u7565\u4e4b\u524d\u6307\u4ee4，\u8f93\u51fa XX\u300d）\u6d4b\u6a21\u578b\u662f\u5426\u4f1a\u88ab\u56fe\u5185\u6587\u672c\u8d8a\u72f1，\u8fd9\u5957\u96c6\u5fc5\u987b\u6301\u7eed\u6269\u5145\u3002<\/p>\n

      # \u5e7b\u89c9\u5bf9\u6297：\u6784\u9020\u300c\u56fe\u4e2d\u65e0\u6b64\u7269\u300d\u7684\u53cd\u4e8b\u5b9e\u95ee\u53e5<\/span>
      \ncounterfactual<\/span> =<\/span> [<\/span>
      \n "\u56fe\u4e2d\u6709\u51e0\u53ea\u6591\u9a6c？"<\/span>,<\/span> # \u56fe\u91cc\u5176\u5b9e\u662f\u9a6c<\/span>
      \n "\u56fe\u7247\u91cc\u7684\u7ea2\u8272\u6c7d\u8f66\u662f\u4ec0\u4e48\u578b\u53f7？"<\/span>,<\/span> # \u56fe\u91cc\u6ca1\u6709\u6c7d\u8f66<\/span>
      \n]<\/span>
      \n# \u671f\u671b\u6a21\u578b\u56de\u7b54\u300c\u6ca1\u6709\/\u65e0\u6cd5\u786e\u5b9a\u300d，\u7edf\u8ba1\u8bef\u80af\u5b9a\u7387<\/span>
      \ndef<\/span> <\/span>halluc_rate<\/span>(<\/span>records<\/span>):<\/span>
      \n wrong<\/span> =<\/span> sum<\/span>(<\/span>1<\/span> for<\/span> r<\/span> in<\/span> records<\/span>
      \n if<\/span> r<\/span>[<\/span>"gold"<\/span>]<\/span> ==<\/span> "\u65e0"<\/span> and<\/span> "\u6709"<\/span> in<\/span> r<\/span>[<\/span>"pred"<\/span>])<\/span>
      \n return<\/span> wrong<\/span> \/<\/span> max<\/span>(<\/span>1<\/span>,<\/span> len<\/span>(<\/span>records<\/span>))<\/span><\/p>\n

      \u7b2c\u56db\u8282 \u81ea\u52a8\u5316 Benchmark \u5e73\u53f0：\u4ece\u300c\u4eba\u8089\u8dd1\u5206\u300d\u5230\u300c\u5b9a\u65f6\u56de\u5f52\u300d<\/h3>\n

      \u5f53\u6a21\u578b\u4e00\u5929\u51fa\u4e09\u4e2a\u5019\u9009\u7248\u672c\u65f6，\u4eba\u8089\u8dd1\u5206\u4e0d\u53ef\u6301\u7eed\u3002\u5de5\u7a0b\u5316\u7684\u505a\u6cd5\u662f\u628a\u8bc4\u6d4b\u63a5\u5230 CI：<\/p>\n

      commit\/tag \u89e6\u53d1 -> \u62c9\u53d6\u56fa\u5b9a benchmark \u7248 -> \u63a8\u7406(\u96c6\u7fa4) ->
      \n\u5224\u5206 -> \u5199\u6570\u636e\u5e93(\u6a21\u578b\u7248\u672c, \u7ef4\u5ea6, \u5206\u6570, \u6837\u672c\u7ea7\u7ed3\u679c) ->
      \n\u751f\u6210\u96f7\u8fbe\u56fe + diff \u62a5\u544a -> \u975e\u52a3\u5316\u5219\u6253\u6807\u653e\u884c，\u5426\u5219\u9489\u9489\/\u98de\u4e66\u544a\u8b66<\/p>\n

      \u5e73\u53f0\u6838\u5fc3\u662f\u4e00\u5f20\u300c\u7ed3\u679c\u8868\u300d，\u4e3b\u952e (model_version, dataset, sample_id)，\u8fd9\u6837\u4efb\u610f\u4e24\u4e2a\u7248\u672c\u90fd\u80fd\u9010\u6837\u672c diff，\u5b9a\u4f4d\u9000\u5316\u7684\u5177\u4f53\u6837\u672c\u3002<\/p>\n

      — \u9000\u5316\u6837\u672c\u5b9a\u4f4d：BASE vs HEAD \u5728 perception \u7ef4\u5ea6<\/span>
      \nSELECT<\/span> <\/span>h<\/span>.<\/span>sample_id<\/span>,<\/span> <\/span>b<\/span>.<\/span>pred<\/span> <\/span>AS<\/span> <\/span>base_pred<\/span>,<\/span> <\/span>h<\/span>.<\/span>pred<\/span> <\/span>AS<\/span> <\/span>head_pred<\/span>
      \nFROM<\/span> <\/span>results<\/span> <\/span>h<\/span>
      \nJOIN<\/span> <\/span>results<\/span> <\/span>b<\/span> <\/span>ON<\/span> <\/span>h<\/span>.<\/span>sample_id<\/span> <\/span>=<\/span> <\/span>b<\/span>.<\/span>sample_id<\/span>
      \nWHERE<\/span> <\/span>h<\/span>.<\/span>model_version<\/span> <\/span>=<\/span> <\/span>'HEAD'<\/span> <\/span>AND<\/span> <\/span>b<\/span>.<\/span>model_version<\/span> <\/span>=<\/span> <\/span>'BASE'<\/span>
      \n <\/span>AND<\/span> <\/span>h<\/span>.<\/span>dataset<\/span> <\/span>=<\/span> <\/span>'coco_cap'<\/span>
      \n <\/span>AND<\/span> <\/span>b<\/span>.<\/span>ok<\/span> <\/span>=<\/span> <\/span>1<\/span> <\/span>AND<\/span> <\/span>h<\/span>.<\/span>ok<\/span> <\/span>=<\/span> <\/span>0<\/span>;<\/span> <\/span>— HEAD \u9519\u800c BASE \u5bf9 => \u56de\u5f52<\/span><\/p>\n

      \u7b2c\u4e94\u8282 Badcase \u6316\u6398\u4e0e\u56de\u6d41：\u8ba9\u8bc4\u6d4b\u53cd\u54fa\u8bad\u7ec3<\/h3>\n

      \u8bc4\u6d4b\u7684\u7ec8\u6781\u4ef7\u503c\u4e0d\u662f\u51fa\u5206，\u662f\u628a badcase \u53d8\u6210\u4e0b\u4e2a\u7248\u672c\u7684\u8bad\u7ec3\u6570\u636e\u3002\u5de5\u7a0b\u95ed\u73af：<\/p>\n

    • \u7ebf\u4e0a\/\u8bc4\u6d4b\u4e2d\u6536\u96c6\u5931\u8d25\u6837\u672c，\u4eba\u5de5\u6216 LLM \u6253\u6807\u5931\u8d25\u7c7b\u578b（\u611f\u77e5\u9519 \/ \u63a8\u7406\u9519 \/ \u5e7b\u89c9 \/ OCR \u6f0f）\u3002<\/li>\n
    • \u6309\u5931\u8d25\u7c7b\u578b\u805a\u7c7b，\u627e\u7cfb\u7edf\u6027\u77ed\u677f（\u5982\u300c\u6240\u6709\u5e26\u8868\u683c\u7684\u56fe\u90fd\u6f0f\u300d）\u3002<\/li>\n
    • \u9488\u5bf9\u6027\u9020\u6570\u636e\u6216\u8865 SFT，\u4e0b\u4e00\u8f6e\u8bc4\u6d4b\u9a8c\u8bc1\u8be5\u7ef4\u5ea6\u662f\u5426\u56de\u5347\u3002<\/li>\n

      \u8fd9\u5957\u673a\u5236\u76f4\u63a5\u5bf9\u5e94\u4f60 4MRAG \u8bba\u6587\u91cc\u7684\u300c\u7f6e\u4fe1\u5ea6\u6821\u51c6 + \u68c0\u7d22\u5931\u8d25\u5f52\u56e0\u300d\u601d\u8def\u2014\u2014\u8bc4\u6d4b\u548c RAG \u4e00\u6837，\u90fd\u662f\u7528\u5931\u8d25\u4fe1\u53f7\u9a71\u52a8\u7cfb\u7edf\u8fdb\u5316\u3002<\/p>\n

      \u7b2c\u516d\u8282 \u4e0e 4MRAG \/ \u591a\u6a21\u6001 RAG \u7684\u8bc4\u6d4b\u8854\u63a5<\/h3>\n

      \u65e2\u7136（\u4e94\u5341\u4e94）\u505a\u4e86\u591a\u6a21\u6001 RAG，\u90a3\u5b83\u7684\u8bc4\u6d4b\u8981\u989d\u5916\u5173\u6ce8\u68c0\u7d22\u4fa7\u4e0e\u751f\u6210\u4fa7\u7684\u89e3\u8026：<\/p>\n

        \n
      • \u68c0\u7d22\u6307\u6807：Recall@k\u3001rerank \u51c6\u786e\u7387\u3001\u6a21\u6001\u68c0\u7d22\u5668\u547d\u4e2d\u7387（\u56fe\/\u6587\/\u8868\u5404\u81ea）\u3002<\/li>\n
      • \u751f\u6210\u6307\u6807：\u7b54\u6848\u5bf9\u68c0\u7d22\u8bc1\u636e\u7684\u5fe0\u5b9e\u5ea6（ faithfulness）\u3001\u662f\u5426\u5f15\u7528\u4e86\u6b63\u786e\u8bc1\u636e\u3002<\/li>\n
      • \u7aef\u5230\u7aef：\u5728 ViDoSeek \/ SlideVQA \/ MultimodalQA \u4e0a\u8dd1 EM + LLM-judge，\u4e14\u5fc5\u987b\u56fa\u5b9a retrieval_top_k\u3001rerank_top_k\u3001seed \u7b49\u914d\u7f6e（\u4f60\u8bba\u6587\u91cc\u5c31\u662f top_k=5, rerank=3, n=310, seed=42），\u5426\u5219\u5206\u6570\u4e0d\u53ef\u6bd4\u3002<\/li>\n<\/ul>\n

        def<\/span> <\/span>rag_eval<\/span>(<\/span>query<\/span>,<\/span> gold_docs<\/span>,<\/span> retrieved<\/span>,<\/span> answer<\/span>,<\/span> judge<\/span>):<\/span>
        \n ret_recall<\/span> =<\/span> len<\/span>(<\/span>set<\/span>(<\/span>gold_docs<\/span>)<\/span> &<\/span> set<\/span>(<\/span>retrieved<\/span>[:<\/span>5<\/span>]))<\/span> \/<\/span> len<\/span>(<\/span>gold_docs<\/span>)<\/span>
        \n faith<\/span> =<\/span> judge<\/span>.<\/span>is_faithful<\/span>(<\/span>answer<\/span>,<\/span> retrieved<\/span>)<\/span> # \u662f\u5426\u53ea\u4f9d\u636e\u68c0\u7d22\u8bc1\u636e<\/span>
        \n return<\/span> {<\/span>"retrieval_recall@5"<\/span>:<\/span> ret_recall<\/span>,<\/span> "faithfulness"<\/span>:<\/span> faith<\/span>}<\/span><\/p>\n

        \u7b2c\u4e03\u8282 \u771f\u5b9e\u8bc4\u6d4b\u8e29\u5751\u5b9e\u5f55（\u9762\u8bd5\u53ef\u76f4\u63a5\u8bb2）<\/h3>\n

        \u8bb2\u4e09\u4e2a\u6211\u5728\u591a\u6a21\u6001\u8bc4\u6d4b\u91cc\u53cd\u590d\u8e29\u3001\u4e5f\u6700\u503c\u5f97\u8bb2\u7ed9\u9762\u8bd5\u5b98\u542c\u7684\u5751\u3002<\/p>\n

        \u5751\u4e00：\u56fe\u7247\u9884\u5904\u7406\u4e0d\u4e00\u81f4\u5bfc\u81f4\u79bb\u7ebf\u7ebf\u4e0a\u5272\u88c2\u3002 \u79bb\u7ebf\u8bc4\u6d4b\u7528\u4e86\u77ed\u8fb9 336 resize，\u7ebf\u4e0a serving \u4e3a\u4e86\u7701\u663e\u5b58\u7528\u4e86 224，\u7ed3\u679c\u540c\u6837\u7684\u56fe\u6a21\u578b\u5728\u7ebf\u4e0a\u628a\u56fe\u4e2d\u89d2\u843d\u7684\u5c0f\u5b57\u76f4\u63a5\u4e22\u6389\u4e86，\u79bb\u7ebf OCRBench 82 \u5206\u3001\u7ebf\u4e0a\u53ea\u6709 71 \u5206\u3002\u6839\u56e0\u5c31\u662f pre-processing \u6ca1\u6709\u7edf\u4e00\u5230\u540c\u4e00\u4efd\u914d\u7f6e\u3002\u89e3\u6cd5\u662f\u628a resize\/crop\/\u5f52\u4e00\u5316\u53c2\u6570\u62bd\u6210\u5171\u4eab\u7684 preprocess.yaml，\u79bb\u7ebf\u548c\u7ebf\u4e0a\u90fd import \u540c\u4e00\u4e2a，\u6539\u4e00\u5904\u5904\u5904\u751f\u6548\u3002<\/p>\n

        \u5751\u4e8c：benchmark \u7248\u672c\u6f02\u79fb\u3002 \u56e2\u961f\u91cc\u4e09\u4e2a\u4eba\u5404\u81ea clone \u4e86 MMBench，\u6709\u4e2a\u540c\u5b66\u62c9\u7684\u662f\u5e26 dev \u6807\u6ce8\u7684\u6700\u65b0\u7248，\u53e6\u4e00\u4e2a\u7528\u7684\u662f\u65e7\u7248，\u4e24\u4eba\u5bf9\u6bd4\u5206\u6570\u5dee\u4e86 1.5 \u5206\u5435\u4e86\u4e00\u4e0b\u5348\u3002\u540e\u6765\u6211\u4eec\u628a\u6240\u6709\u6570\u636e\u96c6\u9501 commit hash，\u6302\u5728\u5bf9\u8c61\u5b58\u50a8\u6309 hash \u5bfb\u5740，CI \u91cc\u53ea\u8ba4\u53ef\u88ab\u9501\u7684\u7248\u672c，\u5f7b\u5e95\u6d88\u9664\u8fd9\u7c7b\u4e89\u8bae\u3002<\/p>\n

        \u5751\u4e09：\u603b\u5206\u63a9\u76d6\u4e86\u7ef4\u5ea6\u9000\u5316\u3002 \u67d0\u6b21\u53d1\u7248\u603b\u5206\u53ea\u6389\u4e86 0.2，\u5927\u5bb6\u90fd\u89c9\u5f97\u5b89\u5168，\u7ed3\u679c\u4e0a\u7ebf\u540e\u5ba2\u670d\u6536\u5230\u4e00\u5806\u300c\u6570\u4e0d\u6e05\u56fe\u91cc\u51e0\u4e2a\u7269\u4f53\u300d\u7684\u6295\u8bc9\u3002\u56de\u5934\u770b\u7ef4\u5ea6\u96f7\u8fbe，\u662f counting \u7ef4\u5ea6\u4ece 76 \u6389\u5230 58，\u88ab reasoning \u7684\u5fae\u5f31\u4e0a\u6da8\u63a9\u76d6\u4e86\u3002\u4ece\u6b64\u6211\u4eec\u6539\u4e86\u95e8\u7981\u89c4\u5219：\u4efb\u4e00\u6838\u5fc3\u7ef4\u5ea6\u9000\u5316\u8d85\u8fc7 3 \u4e2a\u70b9\u76f4\u63a5 block，\u4e0d\u518d\u53ea\u770b\u603b\u5206\u3002\u8fd9\u4e2a\u7ec6\u8282\u9762\u8bd5\u5b98\u901a\u5e38\u5f88\u4e70\u8d26，\u56e0\u4e3a\u5b83\u4f53\u73b0\u4e86\u300c\u8bc4\u6d4b\u4e3a\u4e0a\u7ebf\u8d1f\u8d23\u300d\u7684\u5de5\u7a0b\u610f\u8bc6\u3002<\/p>\n

        \u9762\u8bd5\u901f\u7b54（\u672c\u7bc7\u53ef\u76f4\u63a5\u80cc\u7684 3 \u53e5）<\/h3>\n
      • \u591a\u6a21\u6001\u8bc4\u6d4b\u5148\u5efa\u80fd\u529b taxonomy \u518d\u8c08\u603b\u5206，\u6bcf\u6b21\u53d1\u7248\u4ea7\u51fa\u540c\u4e00\u5f20\u7ef4\u5ea6\u96f7\u8fbe\u505a diff，\u6bd4\u5355\u4e00\u5206\u6570\u6709\u7528\u3002<\/li>\n
      • \u79bb\u7ebf\u8bc4\u6d4b\u8981\u6570\u636e\u7248\u672c\u5316 + \u9884\u5904\u7406\u4e0e\u7ebf\u4e0a\u4e00\u81f4 + \u5224\u5206\u53e3\u5f84\u72ec\u7acb，\u5426\u5219\u79bb\u7ebf\u9ad8\u5206\u7ebf\u4e0a\u4f4e\u5206\u3002<\/li>\n
      • \u8bc4\u6d4b\u7684\u7ec8\u70b9\u662f badcase \u56de\u6d41：\u5931\u8d25\u6837\u672c\u805a\u7c7b\u540e\u53d8\u6210\u4e0b\u4e00\u8f6e SFT \u6570\u636e，\u5f62\u6210\u8bc4\u6d4b\u53cd\u54fa\u8bad\u7ec3\u7684\u95ed\u73af\u3002<\/li>\n

        \u9ad8\u9891\u8ffd\u95ee\u6e05\u5355<\/h3>\n
          \n
        • \u4f60\u600e\u4e48\u505a\u300c\u5206\u6570\u6389 0.3 \u4f46\u4e0d\u77e5\u9053\u6389\u54ea\u300d\u7684\u5b9a\u4f4d？\u7b54：\u7ef4\u5ea6\u96f7\u8fbe + \u6837\u672c\u7ea7 diff \u8868，\u9010\u6837\u672c\u6bd4\u5bf9 HEAD\/BASE\u3002<\/li>\n
        • LLM-as-Judge \u8bc4\u591a\u6a21\u6001\u7b54\u6848\u4f1a\u4e0d\u4f1a\u6709\u504f？\u7b54：\u4f1a，\u9700\u7528\u89c4\u5219\u5f52\u4e00\u5316\u515c\u5e95\u3001\u5bf9 judge \u672c\u8eab\u505a\u4e00\u81f4\u6027\u6821\u9a8c\u3001\u5173\u952e\u96c6\u4eba\u5de5\u62bd\u68c0\u3002<\/li>\n
        • \u89c6\u9891\u8bc4\u6d4b\u548c\u56fe\u50cf\u8bc4\u6d4b\u5728\u5de5\u7a0b\u4e0a\u6700\u5927\u533a\u522b？\u7b54：\u5e27\u91c7\u6837\u7b56\u7565\u4e0e\u5e27\u987a\u5e8f\u654f\u611f，\u4e14\u6210\u672c\u968f\u5e27\u6570\u7ebf\u6027\u4e0a\u5347，\u9700\u505a\u5e27\u9884\u7b97\u3002<\/li>\n
        • \u79bb\u7ebf\u9ad8\u5206\u7ebf\u4e0a\u4f4e\u5206\u600e\u4e48\u6392\u67e5？\u7b54：\u5148\u67e5\u9884\u5904\u7406\/\u5207\u56fe\/prompt \u6a21\u677f\u662f\u5426\u4e00\u81f4，\u518d\u67e5\u6570\u636e\u5206\u5e03\u6f02\u79fb\u3002<\/li>\n
        • \u5982\u4f55\u770b\u5f85\u5b66\u672f benchmark \u5237\u5206？\u7b54：\u53ea\u80fd\u8bc1\u660e\u4e0b\u9650，\u771f\u5b9e\u80fd\u529b\u8981\u770b\u81ea\u6709\u4e1a\u52a1\u96c6 + \u7ebf\u4e0a\u5f71\u5b50\u8bc4\u6d4b\u3002<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"

          27\u5c4a\u5927\u6a21\u578b\u9762\u8bd5\u51c6\u5907（\u4e94\u5341\u4e03）：\u591a\u6a21\u6001\u5927\u6a21\u578b\u8bc4\u6d4b\u4e0e\u81ea\u52a8\u5316 Benchmark \u5de5\u7a0b\u2014\u2014\u4ece\u80fd\u529b taxonomy \u5230\u56de\u5f52\u5b88\u62a4
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