{"id":36679,"date":"2025-01-16T10:00:17","date_gmt":"2025-01-16T02:00:17","guid":{"rendered":"https:\/\/17aitech.com\/?p=36679"},"modified":"2025-01-16T10:00:17","modified_gmt":"2025-01-16T02:00:17","slug":"%e8%bf%99%e4%b8%89%e5%ae%b6%e5%9b%bd%e5%86%85%e6%9c%ba%e6%9e%84%e5%90%88%e4%bd%9c%e6%88%90%e6%9e%9c%ef%bc%8c%e6%96%a9%e8%8e%b7emnlp-2024%e6%9c%80%e4%bd%b3%e8%ae%ba%e6%96%87%e5%a5%96%ef%bc%8c%e4%b8%bb","status":"publish","type":"post","link":"https:\/\/17aitech.com\/?p=36679","title":{"rendered":"\u8fd9\u4e09\u5bb6\u56fd\u5185\u673a\u6784\u5408\u4f5c\u6210\u679c\uff0c\u65a9\u83b7EMNLP 2024\u6700\u4f73\u8bba\u6587\u5956\uff0c\u4e3b\u529e\u65b9\uff1a\u660e\u5e74\u82cf\u5dde\u89c1\uff01"},"content":{"rendered":"<p>\u6587\u7ae0\u6765\u6e90\u4e8e\u4e92\u8054\u7f51:<a href=\"https:\/\/www.jiqizhixin.com\/articles\/2024-11-15-9\" target=\"_blank\">\u8fd9\u4e09\u5bb6\u56fd\u5185\u673a\u6784\u5408\u4f5c\u6210\u679c\uff0c\u65a9\u83b7EMNLP 2024\u6700\u4f73\u8bba\u6587\u5956\uff0c\u4e3b\u529e\u65b9\uff1a\u660e\u5e74\u82cf\u5dde\u89c1\uff01<\/a><\/p>\n<blockquote data-author-name=\"\" data-content-utf8-length=\"46\" data-source-title=\"\" data-type=\"2\" data-url=\"\">\n<section>\n<section>\u4e2d\u79d1\u9662\u8ba1\u7b97\u6240\u3001\u4e2d\u56fd\u79d1\u5b66\u9662\u5927\u5b66\u3001\u4e2d\u5173\u6751\u5b9e\u9a8c\u5ba4\u5408\u4f5c\u7684\u4e00\u7bc7\u8bba\u6587\u62ff\u5230\u4e86 EMNLP 2024 \u6700\u4f73\u8bba\u6587\u5956\u3002<\/section>\n<\/section>\n<\/blockquote>\n<section><\/section>\n<section>\u521a\u521a\uff0cEMNLP 2024 \u8bba\u6587\u5956\u9879\u7ed3\u679c\u51fa\u7089\u4e86\uff01<\/section>\n<section><\/section>\n<section>EMNLP 2024 \u4f1a\u8bae\u8fd1\u65e5\u5728\u7f8e\u56fd\u8fc8\u963f\u5bc6\u76db\u5927\u5f00\u5e55\uff0c\u73b0\u573a\u70ed\u95f9\u975e\u51e1\u3002<\/section>\n<section><a href=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-b8cfb783c8a8655f5dc0e4364207ecac.png\" data-fancybox=\"images\" data-fancybox=\"gallery\"><img decoding=\"async\" src=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-b8cfb783c8a8655f5dc0e4364207ecac.png\"><\/a><\/section>\n<section>\u672c\u5c4a\u4f1a\u8bae\u6536\u5230\u4e86\u524d\u6240\u672a\u6709\u7684 6395 \u7bc7\u8bba\u6587\uff0c\u5176\u4e2d\u6709\u6548\u6295\u7a3f 6105 \u7bc7\uff0c\u6bd4\u4e0a\u4e00\u5e74\u8db3\u8db3\u589e\u52a0\u4e86 1196 \u7bc7\u3002\u7ecf\u8fc7\u4e86\u4e25\u683c\u7684\u5ba1\u7a3f\u8fc7\u7a0b\uff0c\u4e3b\u529e\u65b9\u4fdd\u6301\u4e86\u4e0e\u5f80\u5e74\u5dee\u4e0d\u591a\u7684\u8bba\u6587\u63a5\u6536\u7387\uff0c\u6700\u7ec8\u6709 1271 \u7bc7\u4e3b\u4f1a\u8bae\u8bba\u6587\u88ab\u63a5\u6536\u3002<\/section>\n<section><a href=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-bbdd755f2876bc5a4ad26a882e1eedb8.png\" data-fancybox=\"images\" data-fancybox=\"gallery\"><img decoding=\"async\" src=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-bbdd755f2876bc5a4ad26a882e1eedb8.png\"><\/a><\/section>\n<p>\u8ba9\u56fd\u5185\u7814\u7a76\u8005\u66f4\u52a0\u6fc0\u52a8\u7684\u662f\uff0cEMNLP 2025 \u5c06\u5728\u4e2d\u56fd\u82cf\u5dde\u4e3e\u529e\uff1a<\/p>\n<p><a href=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-2783a5cede1e9d38b4edcde0464915d6.png\" data-fancybox=\"images\" data-fancybox=\"gallery\"><img decoding=\"async\" src=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-2783a5cede1e9d38b4edcde0464915d6.png\"><\/a><\/p>\n<section>\u4f34\u968f\u7740\u672c\u5c4a\u4f1a\u8bae\u7684\u8fdb\u884c\uff0c\u6700\u4f73\u8bba\u6587\u3001\u6770\u51fa\u8bba\u6587\u7b49\u5956\u9879\u9646\u7eed\u51fa\u7089\u3002\u4ee5\u4e0b\u662f\u83b7\u5956\u8bba\u6587\u4fe1\u606f\uff1a<\/section>\n<section><\/section>\n<section><strong>\u6700\u4f73\u8bba\u6587<\/strong><\/section>\n<section><\/section>\n<section><strong>\u8bba\u6587 1\uff1a\u300aAn image speaks a thousand words, but can everyone listen? On image transcreation for cultural relevance\u300b<\/strong><\/section>\n<section><a href=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-75d6232634873871b8942c4e3d1872e6.png\" data-fancybox=\"images\" data-fancybox=\"gallery\"><img decoding=\"async\" src=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-75d6232634873871b8942c4e3d1872e6.png\"><\/a><\/section>\n<ul>\n<li>\n<section>\u4f5c\u8005\uff1aSimran Khanuja, Sathyanarayanan Ramamoorthy,Yueqi Song,Graham Neubig<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1aCMU<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/aclanthology.org\/2024.emnlp-main.573.pdf<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u4ecb\u7ecd\u4e86\u300ctranscreation\u300d\u7684\u6982\u5ff5\uff0c\u5373\u751f\u6210\u6587\u5316\u4e0a\u5408\u7406\u7684\u56fe\u50cf\uff0c\u5e76\u63d0\u4f9b\u4e86\u4e00\u4e2a\u57fa\u51c6\u6570\u636e\u96c6\u6765\u8bc4\u4f30 LLM \u5728\u8fd9\u9879\u4efb\u52a1\u4e2d\u7684\u80fd\u529b\uff0c\u5f00\u8f9f\u4e86\u4e00\u4e2a\u5177\u6709\u91cd\u5927\u73b0\u5b9e\u610f\u4e49\u7684\u65b0\u7814\u7a76\u9886\u57df\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<section>\u6458\u8981\uff1a\u968f\u7740\u591a\u5a92\u4f53\u5185\u5bb9\u7684\u5174\u8d77\uff0c\u4eba\u7c7b\u7ffb\u8bd1\u4eba\u5458\u8d8a\u6765\u8d8a\u6ce8\u91cd\u6587\u5316\u9002\u5e94\uff0c\u4e0d\u4ec5\u662f\u6587\u5b57\uff0c\u8fd8\u5305\u62ec\u56fe\u50cf\u7b49\u5176\u4ed6\u65b9\u5f0f\u3002\u867d\u7136\u4e00\u4e9b\u5e94\u7528\u53ef\u4ee5\u4ece\u4e2d\u53d7\u76ca\uff0c\u4f46\u673a\u5668\u7ffb\u8bd1\u7cfb\u7edf\u4ecd\u7136\u5c40\u9650\u4e8e\u5904\u7406\u8bed\u97f3\u548c\u6587\u672c\u4e2d\u7684\u8bed\u8a00\u3002\u8fd9\u9879\u5de5\u4f5c\u5f15\u5165\u4e86\u7ffb\u8bd1\u56fe\u50cf\u7684\u65b0\u4efb\u52a1\uff0c\u4f7f\u5176\u5177\u6709\u6587\u5316\u76f8\u5173\u6027\u3002\u9996\u5148\uff0c\u672c\u6587\u5efa\u7acb\u4e86\u4e09\u4e2a\u7531\u6700\u5148\u8fdb\u7684\u751f\u6210\u6a21\u578b\u7ec4\u6210\u7684 pipeline \u6765\u5b8c\u6210\u8fd9\u9879\u4efb\u52a1\u3002\u63a5\u4e0b\u6765\uff0c\u7814\u7a76\u8005\u5efa\u7acb\u4e86\u4e00\u4e2a\u7531\u4e24\u90e8\u5206\u7ec4\u6210\u7684\u8bc4\u4f30\u6570\u636e\u96c6\uff0c(i) \u6982\u5ff5\uff1a\u7531 600 \u5e45\u8de8\u6587\u5316\u8fde\u8d2f\u7684\u56fe\u50cf\u7ec4\u6210\uff0c\u6bcf\u5e45\u56fe\u50cf\u53ea\u5173\u6ce8\u4e00\u4e2a\u6982\u5ff5\uff1b(ii) \u5e94\u7528\uff1a\u7531 100 \u5e45\u4ece\u771f\u5b9e\u4e16\u754c\u5e94\u7528\u4e2d\u6536\u96c6\u7684\u56fe\u50cf\u7ec4\u6210\u3002\u672c\u6587\u5bf9\u7ffb\u8bd1\u56fe\u50cf\u8fdb\u884c\u4e86\u591a\u65b9\u9762\u7684\u4eba\u5de5\u8bc4\u4f30\uff0c\u4ee5\u8bc4\u4f30\u6587\u5316\u76f8\u5173\u6027\u548c\u610f\u4e49\u4fdd\u5b58\u60c5\u51b5\u3002\u7ed3\u679c\u53d1\u73b0\u5230\u76ee\u524d\u4e3a\u6b62\uff0c\u56fe\u50cf\u7f16\u8f91\u6a21\u578b\u672a\u80fd\u5b8c\u6210\u8fd9\u9879\u4efb\u52a1\uff0c\u4f46\u53ef\u4ee5\u901a\u8fc7\u5728\u5faa\u73af\u4e2d\u5229\u7528 LLM \u548c\u68c0\u7d22\u5668\u6765\u52a0\u4ee5\u6539\u8fdb\u3002\u5728\u8f83\u7b80\u5355\u7684\u6982\u5ff5\u6570\u636e\u96c6\u4e2d\uff0c\u6700\u4f73 pipeline \u53ea\u80fd\u4e3a\u67d0\u4e9b\u56fd\u5bb6\u7ffb\u8bd1 5% \u7684\u56fe\u50cf\uff0c\u800c\u5728\u5e94\u7528\u6570\u636e\u96c6\u4e2d\uff0c\u5bf9\u67d0\u4e9b\u56fd\u5bb6\u5219\u65e0\u6cd5\u6210\u529f\u7ffb\u8bd1\uff0c\u51f8\u663e\u4e86\u8fd9\u9879\u4efb\u52a1\u7684\u6311\u6218\u6027\u3002<\/section>\n<section><a href=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-d4da855d78a1f1c4e5c75897919ea0d3.png\" data-fancybox=\"images\" data-fancybox=\"gallery\"><img decoding=\"async\" src=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-d4da855d78a1f1c4e5c75897919ea0d3.png\"><\/a><\/section>\n<section><strong>\u8bba\u6587 2\uff1a\u300aTowards Robust Speech Representation Learning for Thousands of Languages\u300b<\/strong><\/section>\n<section><a href=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-0d2309a1d53c5e86971cb0584094cc28.png\" data-fancybox=\"images\" data-fancybox=\"gallery\"><img decoding=\"async\" src=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-0d2309a1d53c5e86971cb0584094cc28.png\"><\/a><\/section>\n<ul>\n<li>\n<section>\u4f5c\u8005\uff1aWilliam Chen, Wangyou Zhang, Yifan Peng, Xinjian Li, Jinchuan Tian,Jiatong Shi, Xuankai Chang, Soumi Maiti, Karen Livescu, Shinii Watanabe<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1aCMU\u3001\u4e0a\u6d77\u4ea4\u5927\u3001\u4e30\u7530\u5de5\u4e1a\u5927\u5b66\uff08\u829d\u52a0\u54e5\uff09<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/aclanthology.org\/2024.emnlp-main.570.pdf<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u53d1\u5e03\u4e86\u4e00\u4e2a\u6db5\u76d6 4000 \u591a\u79cd\u8bed\u8a00\u3001\u8d85\u8fc7 100 \u4e07\u5c0f\u65f6\u8bed\u97f3\u7684\u6570\u636e\u96c6\uff0c\u4ee5\u53ca\u4e00\u4e2a\u5728\u6570\u636e\u57fa\u7840\u4e0a\u8bad\u7ec3\u7684\u591a\u8bed\u8a00\u6a21\u578b\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<section>\u6458\u8981\uff1a\u81ea\u76d1\u7763\u5b66\u4e60\uff08SSL\uff09\u901a\u8fc7\u51cf\u5c11\u5bf9\u6807\u6ce8\u6570\u636e\u7684\u9700\u6c42\uff0c\u5e2e\u52a9\u8bed\u97f3\u6280\u672f\u6269\u5c55\u5230\u66f4\u591a\u7684\u8bed\u8a00\u3002\u7136\u800c\uff0c\u76ee\u524d\u7684\u6a21\u578b\u8fd8\u8fdc\u8fdc\u4e0d\u80fd\u652f\u6301\u5168\u7403 7000 \u591a\u79cd\u8bed\u8a00\u3002\u672c\u6587\u63d0\u51fa\u4e86\u901a\u7528\u8bed\u97f3\u8de8\u8bed\u8a00\u7f16\u7801\u5668 XEUS\uff0c\u8be5\u7f16\u7801\u5668\u5728 4057 \u79cd\u8bed\u8a00\u7684 100 \u591a\u4e07\u5c0f\u65f6\u6570\u636e\u57fa\u7840\u4e0a\u8fdb\u884c\u8bad\u7ec3\uff0c\u5c06 SSL \u6a21\u578b\u7684\u8bed\u8a00\u8986\u76d6\u8303\u56f4\u6269\u5927\u4e86 4 \u500d\u3002\u7814\u7a76\u8005\u5c06\u73b0\u6709\u516c\u5f00\u8bed\u6599\u5e93\u4e2d\u7684 100 \u4e07\u5c0f\u65f6\u8bed\u97f3\u4e0e\u65b0\u521b\u5efa\u7684\u6765\u81ea 4057 \u79cd\u8bed\u8a00\u7684 7400 \u591a\u5c0f\u65f6\u8bed\u6599\u5e93\u7ed3\u5408\u8d77\u6765\u516c\u5f00\u53d1\u5e03\u3002\u4e3a\u4e86\u5904\u7406\u591a\u8bed\u8a00\u8bed\u97f3\u6570\u636e\u7684\u4e0d\u540c\u6761\u4ef6\uff0c\u4ed6\u4eec\u8fd8\u91c7\u7528\u4e86\u4e00\u79cd\u65b0\u9896\u7684\u53bb\u6df7\u54cd\u76ee\u6807\u6765\u589e\u5f3a\u5178\u578b\u7684 SSL \u63a9\u853d\u9884\u6d4b\u65b9\u6cd5\uff0c\u4ece\u800c\u63d0\u9ad8\u4e86\u9c81\u68d2\u6027\u3002\u968f\u540e\u4ed6\u4eec\u5728\u591a\u4e2a\u57fa\u51c6\u4e0a\u5bf9 XEUS \u8fdb\u884c\u4e86\u8bc4\u4f30\uff0c\u7ed3\u679c\u8868\u660e\u5b83\u5728\u5404\u79cd\u4efb\u52a1\u4e2d\u7684\u8868\u73b0\u59cb\u7ec8\u4f18\u4e8e SOTA SSL \u6a21\u578b\uff0c\u6216\u53d6\u5f97\u4e86\u4e0e\u4e4b\u76f8\u5f53\u7684\u7ed3\u679c\u3002XEUS \u5728 ML-SUPERB \u57fa\u51c6\u4e0a\u521b\u9020\u4e86\u65b0\u7684 SOTA\uff1a\u5c3d\u7ba1\u53c2\u6570\u6216\u9884\u8bad\u7ec3\u6570\u636e\u8f83\u5c11\uff0c\u4f46\u5b83\u7684\u6027\u80fd\u5206\u522b\u6bd4 MMS 1B \u548c w2v-BERT 2.0 v2 \u9ad8\u51fa 0.8% \u548c 4.4%\u3002<\/section>\n<section><a href=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-18d8d69c2f7cd36f9302ec7ed04d79e6.png\" data-fancybox=\"images\" data-fancybox=\"gallery\"><img decoding=\"async\" src=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-18d8d69c2f7cd36f9302ec7ed04d79e6.png\"><\/a><\/section>\n<section><strong>\u8bba\u6587 3\uff1a\u300aBackward Lens: Projecting Language Model Gradients into the Vocabulary Space\u300b<\/strong><\/section>\n<section><a href=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-b53117d5a66d44c160265cf6caeccc8a.png\" data-fancybox=\"images\" data-fancybox=\"gallery\"><img decoding=\"async\" src=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-b53117d5a66d44c160265cf6caeccc8a.png\"><\/a><\/section>\n<ul>\n<li>\n<section>\u4f5c\u8005\uff1aShahar Katz, Yonatan Belinkov, Mor Geva, Lior Wolf<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1a\u4ee5\u8272\u5217\u7406\u5de5\u5b66\u9662\u3001\u7279\u62c9\u7ef4\u592b\u5927\u5b66<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/aclanthology.org\/2024.emnlp-main.142.pdf<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u901a\u8fc7\u5c06\u68af\u5ea6\u6295\u5c04\u5230\u8bcd\u6c47\u7a7a\u95f4\u6765\u5b9e\u73b0\u53ef\u89e3\u91ca\u6027\uff0c\u4e3a\u6a21\u578b\u7f16\u8f91\u5f15\u5165\u4e86\u4e00\u79cd\u4f18\u96c5\u800c\u76f4\u89c2\u7684\u65b9\u6cd5\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<section>\u6458\u8981\uff1a\u4e86\u89e3\u57fa\u4e8e Transformer \u7684\u8bed\u8a00\u6a21\u578b\uff08LM\uff09\u5982\u4f55\u5b66\u4e60\u548c\u8c03\u7528\u4fe1\u606f\u662f\u6df1\u5ea6\u5b66\u4e60\u9886\u57df\u7684\u4e00\u4e2a\u5173\u952e\u76ee\u6807\u3002\u6700\u8fd1\u7684\u53ef\u89e3\u91ca\u6027\u65b9\u6cd5\u5c06\u524d\u5411\u4f20\u9012\u83b7\u5f97\u7684\u6743\u91cd\u548c\u9690\u85cf\u72b6\u6001\u6295\u5c04\u5230\u6a21\u578b\u7684\u8bcd\u6c47\u8868\u4e2d\uff0c\u6709\u52a9\u4e8e\u63ed\u793a\u4fe1\u606f\u5982\u4f55\u5728 LM \u4e2d\u6d41\u52a8\u3002\u672c\u6587\u5c06\u8fd9\u4e00\u65b9\u6cd5\u6269\u5c55\u5230 LM \u7684\u540e\u5411\u4f20\u9012\u548c\u68af\u5ea6\u3002\u7814\u7a76\u8005\u9996\u5148\u8bc1\u660e\uff0c\u68af\u5ea6\u77e9\u9635\u53ef\u4ee5\u88ab\u89c6\u4e3a\u524d\u5411\u4f20\u9012\u548c\u540e\u5411\u4f20\u9012\u8f93\u5165\u7684\u4f4e\u79e9\u7ebf\u6027\u7ec4\u5408\u3002\u7136\u540e\uff0c\u7814\u7a76\u8005\u5f00\u53d1\u4e86\u5c06\u8fd9\u4e9b\u68af\u5ea6\u6295\u5c04\u5230\u8bcd\u6c47\u9879\u76ee\u4e2d\u7684\u65b9\u6cd5\uff0c\u5e76\u63a2\u7d22\u4e86\u65b0\u4fe1\u606f\u5982\u4f55\u5b58\u50a8\u5728 LM \u795e\u7ecf\u5143\u4e2d\u7684\u673a\u5236\u3002<\/section>\n<section><\/section>\n<section><strong>\u8bba\u6587 4\uff1a\u300aPretraining Data Detection for Large Language Models: A Divergence-based Calibration Method\u300b<\/strong><\/section>\n<section><a href=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-0255e2f6824ff426d76af7c71727b3d1.png\" data-fancybox=\"images\" data-fancybox=\"gallery\"><img decoding=\"async\" src=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-0255e2f6824ff426d76af7c71727b3d1.png\"><\/a><\/section>\n<ul>\n<li>\n<section>\u4f5c\u8005\uff1aWeichao Zhang, Ruging Zhang, Jiafeng Guo, Maarten de Rijke, Yixing Fan,Xueqi Cheng<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1a\u4e2d\u79d1\u9662\u8ba1\u7b97\u6240\u3001\u4e2d\u56fd\u79d1\u5b66\u9662\u5927\u5b66\u3001\u4e2d\u5173\u6751\u5b9e\u9a8c\u5ba4\u3001\u963f\u59c6\u65af\u7279\u4e39\u5927\u5b66<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/aclanthology.org\/2024.emnlp-main.300.pdf<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u63d0\u51fa\u4e86\u4e00\u79cd\u7528\u4e8e\u9884\u8bad\u7ec3\u6570\u636e\u9ed1\u76d2\u68c0\u6d4b\u7684\u65b0\u6570\u636e\u96c6\u548c\u65b9\u6cd5<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<section>\u6458\u8981\uff1a\u968f\u7740\u5927\u578b\u8bed\u8a00\u6a21\u578b\uff08LLM\uff09\u8bad\u7ec3\u8bed\u6599\u5e93\u89c4\u6a21\u7684\u6269\u5927\uff0c\u6a21\u578b\u5f00\u53d1\u8005\u8d8a\u6765\u8d8a\u4e0d\u613f\u610f\u516c\u5f00\u5176\u6570\u636e\u7684\u8be6\u7ec6\u4fe1\u606f\u3002\u8fd9\u79cd\u7f3a\u4e4f\u900f\u660e\u5ea6\u7684\u60c5\u51b5\u7ed9\u79d1\u5b66\u8bc4\u4f30\u548c\u9053\u5fb7\u90e8\u7f72\u5e26\u6765\u4e86\u6311\u6218\u3002\u6700\u8fd1\uff0c\u4eba\u4eec\u5f00\u59cb\u63a2\u7d22\u9884\u8bad\u7ec3\u6570\u636e\u68c0\u6d4b\u65b9\u6cd5\uff0c\u8fd9\u7c7b\u65b9\u6cd5\u4f1a\u901a\u8fc7\u9ed1\u76d2\u8bbf\u95ee\u63a8\u65ad\u7ed9\u5b9a\u6587\u672c\u662f\u5426\u662f LLM \u8bad\u7ec3\u6570\u636e\u7684\u4e00\u90e8\u5206\u3002Min-K% Prob \u65b9\u6cd5\u5df2\u7ecf\u53d6\u5f97\u4e86\u6700\u5148\u8fdb\u7684\u6210\u679c\uff0c\u8be5\u65b9\u6cd5\u5047\u5b9a\u975e\u8bad\u7ec3\u6837\u672c\u5f80\u5f80\u5305\u542b\u4e00\u4e9b token \u6982\u7387\u8f83\u4f4e\u7684\u79bb\u7fa4\u8bcd\u3002\u7136\u800c\uff0c\u8fd9\u79cd\u65b9\u6cd5\u7684\u6709\u6548\u6027\u53ef\u80fd\u6709\u9650\uff0c\u56e0\u4e3a\u5b83\u5f80\u5f80\u4f1a\u8bef\u5206\u90a3\u4e9b\u5305\u542b\u8bb8\u591a\u7531 LLM \u9884\u6d4b\u4e3a\u9ad8\u6982\u7387\u7684\u5e38\u7528\u8bcd\u7684\u975e\u8bad\u7ec3\u6587\u672c\u3002\u672c\u6587\u53d7\u6563\u5ea6\u968f\u673a\u6027\u7684\u542f\u53d1\uff0c\u5f15\u5165\u4e86\u4e00\u79cd\u57fa\u4e8e\u6563\u5ea6\u7684\u6821\u51c6\u65b9\u6cd5\uff0c\u6765\u6821\u51c6\u7528\u4e8e\u9884\u8bad\u7ec3\u6570\u636e\u68c0\u6d4b\u7684 token \u6982\u7387\u3002\u7814\u7a76\u8005\u8ba1\u7b97\u4e86 token \u6982\u7387\u5206\u5e03\u548c token \u9891\u7387\u5206\u5e03\u4e4b\u95f4\u7684\u4ea4\u53c9\u71b5\uff08\u5373\u6563\u5ea6\uff09\uff0c\u4ece\u800c\u5f97\u51fa\u68c0\u6d4b\u5f97\u5206\u3002\u6b64\u5916\u8fd8\u5f00\u53d1\u4e86\u4e00\u4e2a\u4e2d\u6587\u57fa\u51c6 \u2014PatentMIA\uff0c\u4ee5\u8bc4\u4f30 LLMs \u68c0\u6d4b\u65b9\u6cd5\u5728\u4e2d\u6587\u6587\u672c\u4e0a\u7684\u6027\u80fd\u3002\u5728\u82f1\u6587\u57fa\u51c6\u548c PatentMIA \u4e0a\u7684\u5b9e\u9a8c\u7ed3\u679c\u8868\u660e\uff0c\u672c\u6587\u63d0\u51fa\u7684\u65b9\u6cd5\u660e\u663e\u4f18\u4e8e\u73b0\u6709\u65b9\u6cd5\u3002<\/section>\n<section><a href=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-d16346dbfcbf366296eeba30047eefa2.png\" data-fancybox=\"images\" data-fancybox=\"gallery\"><img decoding=\"async\" src=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-d16346dbfcbf366296eeba30047eefa2.png\"><\/a><\/section>\n<section><strong>\u8bba\u6587 5\uff1a\u300aCoGen: Learning from Feedback with Coupled Comprehension and Generation\u300b<\/strong><\/section>\n<section><a href=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-b94ed16fa42e5e14919bdf0865afce42.png\" data-fancybox=\"images\" data-fancybox=\"gallery\"><img decoding=\"async\" src=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-b94ed16fa42e5e14919bdf0865afce42.png\"><\/a><\/section>\n<ul>\n<li>\n<section>\u4f5c\u8005\uff1aMustafa Omer Gul, Yoav Artzi<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1a\u5eb7\u5948\u5c14\u5927\u5b66<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/aclanthology.org\/2024.emnlp-main.721.pdf<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u63a2\u7d22\u8bed\u8a00\u7406\u89e3\u4e0e\u8bed\u8a00\u751f\u6210\u7684\u7ed3\u5408\uff0c\u4ee5\u6539\u5584\u53cc\u4eba\u53c2\u8003\u6e38\u620f\u4e2d\u7684\u4eba\u9645\u4e92\u52a8\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<section>\u6458\u8981\uff1a\u540c\u65f6\u5177\u5907\u8bed\u8a00\u7406\u89e3\u548c\u751f\u6210\u80fd\u529b\u7684\u7cfb\u7edf\u53ef\u4ee5\u4ece\u4e24\u8005\u4e4b\u95f4\u7684\u7d27\u5bc6\u8054\u7cfb\u4e2d\u83b7\u76ca\u3002\u672c\u6587\u5c06\u7406\u89e3\u548c\u751f\u6210\u529f\u80fd\u7ed3\u5408\u5728\u4e00\u8d77\uff0c\u91cd\u70b9\u5173\u6ce8\u4ece\u4e0e\u7528\u6237\u7684\u4e92\u52a8\u4e2d\u4e0d\u65ad\u5b66\u4e60\uff0c\u63d0\u51fa\u4e86\u5c06\u8fd9\u4e24\u79cd\u5b66\u4e60\u548c\u63a8\u7406\u80fd\u529b\u7d27\u5bc6\u7ed3\u5408\u7684\u6280\u672f\u3002\u7814\u7a76\u8005\u5c06\u7814\u7a76\u7f6e\u4e8e\u53cc\u4eba\u53c2\u8003\u6e38\u620f\u4e2d\uff0c\u5e76\u5728\u4e0e\u4eba\u7c7b\u7528\u6237\u7684\u6570\u5343\u6b21\u4e92\u52a8\u4e2d\u90e8\u7f72\u5404\u79cd\u6a21\u578b\uff0c\u540c\u65f6\u4ece\u4e92\u52a8\u53cd\u9988\u4fe1\u53f7\u4e2d\u5b66\u4e60\u3002\u7ed3\u679c\u53d1\u73b0\uff0c\u968f\u7740\u65f6\u95f4\u7684\u63a8\u79fb\uff0c\u6027\u80fd\u6709\u4e86\u663e\u8457\u63d0\u9ad8\uff0c\u4e0e\u65e0\u8026\u5408\u7cfb\u7edf\u76f8\u6bd4\uff0c\u7406\u89e3\u529b\u751f\u6210\u8026\u5408\u7684\u7edd\u5bf9\u6027\u80fd\u63d0\u9ad8\u4e86 26%\uff0c\u51c6\u786e\u7387\u63d0\u9ad8\u4e86 17%\u3002\u672c\u6587\u5206\u6790\u8fd8\u8868\u660e\uff0c\u8026\u5408\u5bf9\u7cfb\u7edf\u8bed\u8a00\u7684\u8d28\u91cf\u4ea7\u751f\u4e86\u91cd\u5927\u5f71\u54cd\uff0c\u4f7f\u5176\u660e\u663e\u66f4\u50cf\u4eba\u7c7b\u8bed\u8a00\u3002<\/section>\n<section><a href=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-5619bb6b927eca0cbf6889a9968a6856.png\" data-fancybox=\"images\" data-fancybox=\"gallery\"><img decoding=\"async\" src=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-5619bb6b927eca0cbf6889a9968a6856.png\"><\/a><\/section>\n<section><strong>\u6770\u51fa\u8bba\u6587<\/strong><\/section>\n<section><a href=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-a5b1cf4e93bf5106d9f3b93c5af3b71c.png\" data-fancybox=\"images\" data-fancybox=\"gallery\"><img decoding=\"async\" src=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-a5b1cf4e93bf5106d9f3b93c5af3b71c.png\"><\/a><\/section>\n<ul>\n<li>\n<section>\u8bba\u6587 1\uff1aFishing for Magikarp: Automatically Detecting Under-trained Tokens in Large Language Models<\/section>\n<\/li>\n<li>\n<section>\u4f5c\u8005\uff1aSander Land\u3001Max Bartolo<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1aCohere<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/www.alphaxiv.org\/abs\/2405.05417v1<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u6df1\u5165\u63a2\u8ba8\u4e86\u591a\u4e2a\u5f00\u6e90 LLM \u4e2d\u672a\u5145\u5206\u8bad\u7ec3\u7684 token \u6240\u5f15\u53d1\u7684\u95ee\u9898\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<ul>\n<li>\n<section>\u8bba\u6587 2\uff1aLearning to Retrieve lteratively for in-Context Learning<\/section>\n<\/li>\n<li>\n<section>\u4f5c\u8005\uff1aYunmo Chen, Tongfei Chen, Harsh Jhamtani, Patrick Xia, Richard Shin, Jason Eisner, Benjamin Van Durme<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1a\u5fae\u8f6f<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/arxiv.org\/abs\/2406.14739<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u63d0\u51fa\u4e86\u4e00\u79cd\u521b\u9020\u6027\u7684\u65b9\u6cd5\uff0c\u5c06 in-context leaming \u793a\u4f8b\u7684\u9009\u62e9\u5efa\u6a21\u4e3a\u9a6c\u5c14\u53ef\u592b\u51b3\u7b56\u8fc7\u7a0b\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<ul>\n<li>\n<section>\u8bba\u6587 3\uff1aMeasuring Psychological Depth in Language Models<\/section>\n<\/li>\n<li>\n<section>\u4f5c\u8005\uff1aFabrice Y Harel-Canada, Hanyu Zhou, Sreya Muppalla, Zeynep Senahan Yildiz, Miryung Kim, Amit Sahai, Nanyun Peng<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1a\u52a0\u5dde\u5927\u5b66\u6d1b\u6749\u77f6\u5206\u6821<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/arxiv.org\/abs\/2406.12680<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u63d0\u4f9b\u4e86\u4e00\u5957\u4ee5\u53d9\u4e8b\u7406\u8bba\u4e3a\u57fa\u7840\u7684\u6709\u7528\u6307\u6807\uff0c\u7528\u4e8e\u8bc4\u4f30 LLM \u7684\u53d9\u4e8b\u5199\u4f5c\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<ul>\n<li>\n<section>\u8bba\u6587 4\uff1aDo LLMs Plan Like Human Writers? Comparing Journalist Coverage of Press Releases with LLMs<\/section>\n<\/li>\n<li>\n<section>\u4f5c\u8005\uff1aAlexander Spangher, Nanyun Peng, Sebastian Gehrmann, Mark Dredze<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1a\u5357\u52a0\u5229\u798f\u5c3c\u4e9a\u5927\u5b66\u3001\u52a0\u5dde\u5927\u5b66\u6d1b\u6749\u77f6\u5206\u6821\u3001\u5f6d\u535a\u793e<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/openreview.net\/forum?id=E3VS45jxPR<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u63d0\u51fa\u4e86\u4e00\u79cd\u901a\u8fc7\u5c06 LLM \u4e0e\u65b0\u95fb\u8bb0\u8005\u8fdb\u884c\u6bd4\u8f83\u6765\u8bc4\u4f30 LLM \u7684\u65b9\u6cd5\u548c\u6570\u636e\u96c6<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<ul>\n<li>\n<section>\u8bba\u6587 5\uff1aWords Worth a Thousand Pictures: Measuring and Understanding Perceptual Variability inText-to-mage Generation<\/section>\n<\/li>\n<li>\n<section>\u4f5c\u8005\uff1aRaphael Tang, Crvstina Zhang, Lixinyu Xu, Yao Lu, Wenvan Li, Pontus Stenetor, Jimmy Lin, Ferhan Ture<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1aComcast AI Technologies\u3001\u6ed1\u94c1\u5362\u5927\u5b66\u3001\u4f26\u6566\u5927\u5b66\u5b66\u9662\u3001\u54e5\u672c\u54c8\u6839\u5927\u5b66<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/arxiv.org\/pdf\/2406.08482<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u4e3a\u6587\u672c\u5230\u56fe\u50cf\u7684\u751f\u6210\u63d0\u51fa\u4e86\u4e00\u79cd\u7ecf\u4eba\u5de5\u6821\u51c6\u7684\u53ef\u53d8\u6027\u6d4b\u91cf\u65b9\u6cd5\uff0c\u5e76\u5bf9\u5b9e\u9645\u5f71\u54cd\u8fdb\u884c\u4e86\u5168\u9762\u7684\u5b66\u79d1\u95f4\u5206\u6790\u548c\u8ba8\u8bba\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<ul>\n<li>\n<section>\u8bba\u6587 6\uff1aFinding Blind Spots in Evaluator LLMs with Interpretable Checklists<\/section>\n<\/li>\n<li>\n<section>\u4f5c\u8005\uff1aSumanth Doddapaneni, Mohammed Safi Ur Rahman Khan, Sshubam Verma, Mitesh M Khapra<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1aNilekani Centre at AI4Bharat\u3001\u5370\u5ea6\u7406\u5de5\u5b66\u9662<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/arxiv.org\/abs\/2406.13439<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u5173\u4e8e\u4f7f\u7528 LLM \u4f5c\u4e3a\u8bc4\u4f30\u8005\u7684\u7814\u7a76\uff0c\u4fe1\u606f\u4e30\u5bcc\uff0c\u53d1\u4eba\u6df1\u7701\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<ul>\n<li>\n<section>\u8bba\u6587 7\uff1aGoldCoin: Grounding Large Language Models in Privacy Laws via Contextual Integrity Theory<\/section>\n<\/li>\n<li>\n<section>\u4f5c\u8005\uff1aWei Fan, Haoran Li, Zheye Deng, Weiqi Wang, Yanggiu Song<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1a\u9999\u6e2f\u79d1\u6280\u5927\u5b66\u8ba1\u7b97\u673a\u79d1\u5b66\u4e0e\u5de5\u7a0b\u7cfb<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/arxiv.org\/html\/2406.11149v1<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u63d0\u51fa\u4e86\u4e00\u4e2a\u6846\u67b6\uff0c\u8be5\u6846\u67b6\u5229\u7528\u9690\u79c1\u573a\u666f\u516c\u6b63\u7406\u8bba\uff08Contextual Integrity Theory) \u5c06\u5927\u578b\u8bed\u8a00\u6a21\u578b\u4e0e\u9690\u79c1\u6cd5\u5bf9\u9f50\uff0c\u589e\u5f3a\u4e86\u5b83\u4eec\u5728\u5404\u79cd\u4e0a\u4e0b\u6587\u4e2d\u68c0\u6d4b\u9690\u79c1\u98ce\u9669\u7684\u80fd\u529b\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<ul>\n<li>\n<section>\u8bba\u6587 8\uff1aVerification and Refinement of Natural Language Explanations through LLM-Symbolic Theorem Proving<\/section>\n<\/li>\n<li>\n<section>\u4f5c\u8005\uff1aXin Quan, Marco Valentino, Louise A. Dennis, Andre Freitas<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1a\u66fc\u5f7b\u65af\u7279\u5927\u5b66\u3001\u745e\u58eb Idiap \u7814\u7a76\u6240<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/aclanthology.org\/2024.emnlp-main.172.pdf<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u63d0\u51fa\u4e86\u4e00\u4e2a\u96c6\u6210 LLM \u548c\u5b9a\u7406\u8bc1\u660e\u7684\u795e\u7ecf\u7b26\u53f7\u6846\u67b6\uff0c\u4ee5\u63d0\u9ad8 NLl \u4efb\u52a1\u7684\u81ea\u7136\u8bed\u8a00\u89e3\u91ca\u7684\u8d28\u91cf\u548c\u903b\u8f91\u6709\u6548\u6027\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<ul>\n<li>\n<section>\u8bba\u6587 9\uff1aThe Zeno&#8217;s Paradox of&#8217;Low-Resource\u2019 Languages<\/section>\n<\/li>\n<li>\n<section>\u4f5c\u8005\uff1aHelina Hailu Niaatu, Atnafu Lambebo Tonia, Benjamin Rosman, Thamar Solorio, Monoit Choudhury<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1aMBZUAI \u7b49\u00a0<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/arxiv.org\/pdf\/2410.20817<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u4ed4\u7ec6\u7814\u7a76\u4e86\u300c\u4f4e\u8d44\u6e90\u8bed\u8a00\u610f\u5473\u7740\u4ec0\u4e48\u300d\u8fd9\u4e2a\u95ee\u9898\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<ul>\n<li>\n<section>\u8bba\u6587 10\uff1aWhen is Multilinguality a Curse? Language Modeling for 250 High- and Low-Resource Languages<\/section>\n<\/li>\n<li>\n<section>\u4f5c\u8005\uff1aTvler A.Chana. Catherine Arnett. Zhuowen Tu, Ben Bergen<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1a\u52a0\u5dde\u5927\u5b66\u5723\u8fed\u6208\u5206\u6821<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/arxiv.org\/pdf\/2311.09205<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u5bf9\u5f71\u54cd LLM \u8de8\u8bed\u8a00\u9884\u8bad\u7ec3\u548c\u6027\u80fd\u7684\u56e0\u7d20\u8fdb\u884c\u4e86\u5e7f\u6cdb\u800c\u4e25\u683c\u7684\u5b9e\u8bc1\u8c03\u67e5\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<ul>\n<li>\n<section>\u8bba\u6587 11\uff1aLanguage Models Learn Rare Phenomena from Less Rare Phenomena: The Case of the Missing AANNS<\/section>\n<\/li>\n<li>\n<section>\u4f5c\u8005\uff1aKanishka Misra, Kyle Mahowald<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1a\u5f97\u514b\u8428\u65af\u5927\u5b66\u5965\u65af\u6c40\u5206\u6821<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/arxiv.org\/pdf\/2403.19827<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u4ecb\u7ecd\u4e86\u4e00\u4e2a\u6709\u610f\u601d\u7684\u5b9e\u9a8c\u8bbe\u7f6e\uff0c\u6f14\u793a\u4e86 LLM \u5982\u4f55\u6cdb\u5316\u4ee5\u5b66\u4e60\u7f55\u89c1\u73b0\u8c61\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<ul>\n<li>\n<section>\u8bba\u6587 12\uff1aFool Me Once? Contrasting Textual and Visual Explanations in a Clinical Decision-Support Setting<\/section>\n<\/li>\n<li>\n<section>\u4f5c\u8005\uff1aMaxime Guillaume Kayser, Bayar Menzat, Cornelius Emde, Bogdan Alexandru Bercean, Alex Novak, Abdal\u00e1 Trinidad Espinosa Morgado, Bartlomiej Papiez, Susanne Gaube, Thomas Lukasiewicz, Oana-Maria Camburu<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1a\u725b\u6d25\u5927\u5b66\u3001\u7ef4\u4e5f\u7eb3\u6280\u672f\u5927\u5b66\u7b49<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/arxiv.org\/pdf\/2410.12284<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u8bc4\u4f30\u4e86\u4e34\u5e8a\u4eba\u4f53\u7814\u7a76\u4e2d\u4e0d\u540c\u7c7b\u578b\u89e3\u91ca\u7684\u6709\u7528\u6027\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<ul>\n<li>\n<section>\u8bba\u6587 13\uff1aThreshold-driven Pruning with Segmented Maximum Term Weights for Approximate Cluster-based Sparse Retrieval<\/section>\n<\/li>\n<li>\n<section>\u4f5c\u8005\uff1aYifan Qiao, Parker Carlson, Shanxiu He ,Yingrui Yang, Tao Yang<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1a\u52a0\u5dde\u5927\u5b66\u5723\u5df4\u5df4\u62c9\u5206\u6821<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/sites.cs.ucsb.edu\/~tyang\/papers\/2024EMNLP-CameraReady.pdf<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u63d0\u51fa\u4e86\u4e00\u4e2a probablistically-rank-safe \u7684\u52a8\u6001 pruning \u65b9\u6848\uff0c\u7528\u4e8e\u5feb\u901f\u7684\u57fa\u4e8e\u805a\u7c7b\u7684\u7a00\u758f\u68c0\u7d22\uff0c\u8fd9\u4e2a\u65b9\u6848\u5bf9\u4e8e\u5f53\u524d\u68c0\u7d22\u7cfb\u7edf\u548c RAG \u7ba1\u9053\u6765\u8bf4\u975e\u5e38\u91cd\u8981\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<ul>\n<li>\n<section>\u8bba\u6587 14\uff1aLearning Planning-based Reasoning by Trajectories Collection and Process Reward Synthesizing<\/section>\n<\/li>\n<li>\n<section>\u4f5c\u8005\uff1aFangkai Jiao, Chengwei Qin, Zhengyuan Liu, Nancy F. Chen, Shafig Joty<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1a\u65b0\u52a0\u5761\u5357\u6d0b\u7406\u5de5\u5927\u5b66\u3001\u65b0\u52a0\u5761\u4fe1\u606f\u901a\u8baf\u7814\u7a76\u9662\u3001Salesforce \u7814\u7a76\u9662<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/arxiv.org\/html\/2402.00658v2<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u901a\u8fc7\u5bf9\u5408\u6210\u6570\u636e\u63d0\u4f9b\u4e2d\u95f4\u57fa\u672c\u539f\u7406\u76d1\u7763\uff0c\u5e76\u5728 trajectory \u4e0a\u5e94\u7528 DPO\uff0c\u589e\u5f3a\u4e86 LLM \u7684\u63a8\u7406\u80fd\u529b\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<ul>\n<li>\n<section>\u8bba\u6587 15\uff1aAre Large Language Models Capable of Generating Human-Level Narratives?<\/section>\n<\/li>\n<li>\n<section>\u4f5c\u8005\uff1aYufei Tian, Tenghao Huang,Miri Liu, Derek Jiang, Alexander Spangher, Muhao Chen, Jonathan May, Nanyun Peng<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1a\u52a0\u5dde\u5927\u5b66\u6d1b\u6749\u77f6\u5206\u6821\u3001\u5357\u52a0\u5229\u798f\u5c3c\u4e9a\u5927\u5b66\u3001\u52a0\u5dde\u5927\u5b66\u6234\u7ef4\u65af\u5206\u6821<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/arxiv.org\/pdf\/2407.13248<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u5f15\u5165\u4e86\u4e00\u4e2a\u6846\u67b6\uff0c\u5728\u8bdd\u8bed\uff08discourse\uff09\u5c42\u9762\u8bc4\u4f30 LLM \u751f\u6210\u7684\u53d9\u8ff0\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<ul>\n<li>\n<section>\u8bba\u6587 16\uff1aFormality is Favored: Unraveling the Learning Preferences of Large Language Models on Data with Conflicting Knowledge<\/section>\n<\/li>\n<li>\n<section>\u4f5c\u8005\uff1aJiahuan Li, Yiging Cao, Shuiian Huang, Jiajun Chen<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1a\u5357\u4eac\u5927\u5b66\u8ba1\u7b97\u673a\u8f6f\u4ef6\u65b0\u6280\u672f\u56fd\u5bb6\u91cd\u70b9\u5b9e\u9a8c\u5ba4<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/arxiv.org\/pdf\/2410.04784<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u7814\u7a76\u4e86 LLM \u5728\u8bad\u7ec3\u6570\u636e\u4fe1\u606f\u76f8\u4e92\u51b2\u7a81\u7684\u60c5\u51b5\u4e0b\u5982\u4f55\u5b66\u4e60\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<ul>\n<li>\n<section>\u8bba\u6587 17\uff1aOATH-Frames: Characterizing Online Attitudes Towards Homelessness with LLM Assistants<\/section>\n<\/li>\n<li>\n<section>\u4f5c\u8005\uff1aJaspreet Ranjit, Brihi Joshi, Rebecca Dorn, Laura Petry, Olga Koumoundouros, Jayne Bottarini, Peichen Liu, Eric Rice, Swabha Swayamdipta<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1a\u5357\u52a0\u5229\u798f\u5c3c\u4e9a\u5927\u5b66\u8ba1\u7b97\u673a\u79d1\u5b66\u7cfb\u3001<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/aclanthology.org\/2024.emnlp-main.724.pdf<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u5728\u9886\u57df\u4e13\u5bb6\u548c LLM \u52a9\u7406\u7684\u5e2e\u52a9\u4e0b\uff0c\u5bf9\u516c\u4f17\u5bf9\u65e0\u5bb6\u53ef\u5f52\u8005\u7684\u6001\u5ea6\u8fdb\u884c\u5927\u89c4\u6a21\u5206\u6790\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<ul>\n<li>\n<section>\u8bba\u6587 18\uff1aSUPER: Evaluating Agents on Setting Up and Executing Tasks from Research Repositories<\/section>\n<\/li>\n<li>\n<section>\u4f5c\u8005\uff1aBen Bogin, Kejuan Yang, Shashank Gupta, Kyle Richardson, Erin Bransom, Peter Clark, Ashish Sabharwal, Tushar Khot<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1a\u827e\u4f26\u4eba\u5de5\u667a\u80fd\u7814\u7a76\u6240\u3001\u534e\u76db\u987f\u5927\u5b66<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/arxiv.org\/pdf\/2409.07440<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u521b\u65b0\u7684\u57fa\u51c6\u6d4b\u8bd5\uff0c\u7528\u4e8e\u8bc4\u4f30\u57fa\u4e8e\u5927\u578b\u8bed\u8a00\u6a21\u578b\uff08LLM\uff09\u7684\u667a\u80fd\u4f53\u80fd\u5426\u590d\u73b0\u6765\u81ea\u7814\u7a76\u5e93\u7684\u7ed3\u679c\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<ul>\n<li>\n<section>\u8bba\u6587 19\uff1aTowards Cross-Cultural Mlachine Translation with Retrieval-Augmented Generation from Multilingual Knowledge Graphs<\/section>\n<\/li>\n<li>\n<section>\u4f5c\u8005\uff1aSimone Conia, Daniel Lee, Min Li, Umar Faroog Minhas, Saloni Potdar, Yunyao Li<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1a\u7f57\u9a6c\u5927\u5b66\u3001Adobe\u3001\u82f9\u679c<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/arxiv.org\/pdf\/2410.14057<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u89e3\u51b3\u4e86\u7ffb\u8bd1\u4e0e\u6587\u5316\u76f8\u5173\u7684\u547d\u540d\u5b9e\u4f53\u7684\u6311\u6218\uff0c\u6311\u6218\u4e86\u4ee5\u524d\u5173\u4e8e\u5982\u4f55\u7ffb\u8bd1\u547d\u540d\u5b9e\u4f53\u7684\u89c2\u70b9\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<ul>\n<li>\n<section>\u8bba\u6587 20\uff1aWhich questions should l answer? Salience Prediction of Inquisitive Questions<\/section>\n<\/li>\n<li>\n<section>\u4f5c\u8005\uff1aYating Wu, Ritika Rajesh Mangla, Alex Dimakis, Greg Durrett, Junyi Jessy Li<\/section>\n<\/li>\n<li>\n<section>\u673a\u6784\uff1a\u5fb7\u514b\u8428\u65af\u5927\u5b66\u5965\u65af\u6c40\u5206\u6821\u3001 BespokeLabs.ai<\/section>\n<\/li>\n<li>\n<section>\u94fe\u63a5\uff1ahttps:\/\/arxiv.org\/abs\/2404.10917<\/section>\n<\/li>\n<li>\n<section>\u83b7\u5956\u7406\u7531\uff1a\u63d0\u51fa\u4e86\u4e00\u79cd\u9884\u6d4b\u8bed\u8a00\u654f\u611f\u95ee\u9898\u7a81\u51fa\u7a0b\u5ea6\u7684\u65b9\u6cd5\u548c\u6570\u636e\u96c6\uff0c\u4e3a\u8bed\u8a00\u793e\u533a\u5185\u5173\u4e8e\u4eba\u7c7b\u5982\u4f55\u5904\u7406\u4fe1\u606f\u548c\u4fe1\u606f\u5185\u5bb9\u7684\u8bdd\u8bed\u7ed3\u6784\u7684\u6301\u7eed\u8fa9\u8bba\u63d0\u4f9b\u4fe1\u606f\u3002<\/section>\n<\/li>\n<\/ul>\n<section><\/section>\n<section><sup>\u53c2\u8003\u94fe\u63a5\uff1a<\/sup><\/section>\n<section><em><sup>https:\/\/x.com\/emnlpmeeting\/status\/1857173122598010918<\/sup><\/em><\/section>\n<p>\u6587\u7ae0\u6765\u6e90\u4e8e\u4e92\u8054\u7f51:<a href=\"https:\/\/www.jiqizhixin.com\/articles\/2024-11-15-9\" target=\"_blank\">\u8fd9\u4e09\u5bb6\u56fd\u5185\u673a\u6784\u5408\u4f5c\u6210\u679c\uff0c\u65a9\u83b7EMNLP 2024\u6700\u4f73\u8bba\u6587\u5956\uff0c\u4e3b\u529e\u65b9\uff1a\u660e\u5e74\u82cf\u5dde\u89c1\uff01<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u6587\u7ae0\u6765\u6e90\u4e8e\u4e92\u8054\u7f51:\u8fd9\u4e09\u5bb6\u56fd\u5185\u673a\u6784\u5408\u4f5c\u6210\u679c [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[27],"tags":[70,71,65],"class_list":["post-36679","post","type-post","status-publish","format-standard","hentry","category-news","tag-agent","tag-rag","tag-65"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.4 - 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