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\u6587\u7ae0\u6765\u6e90\u4e8e\u4e92\u8054\u7f51:2024 IBM\u535a\u58eb\u751f\u5956\u5b66\u91d1\u51fa\u7089\uff1a\u97e9\u8fdf\u3001\u5353\u8d8a\u3001\u5f20\u9038\u9a85\u3001\u51af\u5c1a\u5f6c\u7b49AI\u7814\u7a76\u8005\u5165\u9009<\/a><\/p>\n

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IBM \u535a\u58eb\u751f\u5956\u5b66\u91d1\uff08IBM PhD Fellowship Awards\uff09\u521a\u521a\u516c\u5e03\u4e86 2024 \u5e74\u7684\u83b7\u5956\u8005\u540d\u5355\u3002\u76f8\u8f83\u4e8e\u53bb\u5e74\uff0c\u4eca\u5e74\u7684\u83b7\u5956\u8005\u6570\u91cf\u5927\u5e45\u63d0\u5347\uff0c\u4ece 10 \u4eba\u589e\u81f3 24 \u4eba\uff0c\u5176\u4e2d\u534e\u4eba\u83b7\u5956\u8005\u6570\u91cf\u4e5f\u4ece\u53bb\u5e74\u7684 6 \u4eba\u5347\u81f3 9 \u4eba\u3002<\/section>\n
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\u636e\u4e86\u89e3\uff0cIBM \u535a\u58eb\u751f\u5956\u5b66\u91d1\u662f\u4e00\u4e2a\u9887\u6709\u5386\u53f2\u7684\u5956\u5b66\u91d1\uff0c\u81ea 1951 \u5e74\u4ee5\u6765\u5c31\u4e00\u76f4\u5728\u300c\u8868\u5f70\u548c\u5956\u52b1\u4e16\u754c\u5404\u5730\u7684\u4f18\u79c0\u535a\u58eb\u751f\u300d\u3002<\/section>\n
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\u4e5f\u56e0\u6b64\uff0c\u8fd9\u4e2a\u5956\u5b66\u91d1\u7684\u7ade\u4e89\u975e\u5e38\u6fc0\u70c8\uff0c\u6bcf\u5e74\u90fd\u6709\u5927\u91cf\u7533\u8bf7\u8005\u30022024 \u5e74 IBM \u535a\u58eb\u751f\u5956\u5b66\u91d1\u6536\u5230\u4e86\u6765\u81ea 11 \u4e2a\u56fd\u5bb6 \/ \u5730\u533a 76 \u6240\u5927\u5b66\u7684\u6570\u767e\u4efd\u7533\u8bf7\u3002\u7ecf\u7531 IBM \u7684\u6280\u672f\u4e13\u5bb6\u5ba1\u6838\uff0c\u6700\u7ec8\u9009\u51fa\u4e86\u8fd9\u4efd\u6709 24 \u4eba\u7684\u83b7\u5956\u8005\u540d\u5355\u3002\u8fd9\u4e9b\u83b7\u5956\u8005\u4e0d\u4ec5\u5df2\u6709\u5353\u8d8a\u7684\u5b66\u672f\u6210\u5c31\uff0c\u8fd8\u63d0\u4f9b\u4e86\u521b\u65b0\u7684\u7814\u7a76\u63d0\u6848\uff0c\u6d89\u53ca\u7684\u9886\u57df\u5305\u62ec\u534a\u5bfc\u4f53\u6280\u672f\u3001\u4eba\u5de5\u667a\u80fd\u3001\u6df7\u5408\u4e91\u8ba1\u7b97\u3001\u5b89\u5168\u3001\u91cf\u5b50\u8ba1\u7b97\u548c\u8d1f\u8d23\u4efb\u8ba1\u7b97\u7b49\u524d\u6cbf\u7814\u7a76\u9886\u57df\u3002<\/section>\n
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Andi Gu \u00a0\u54c8\u4f5b\u5927\u5b66<\/strong><\/section>\n
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\u4e2a\u4eba\u4e3b\u9875\uff1ahttps:\/\/andigu.github.io\/<\/section>\n
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Andi Gu \u662f\u54c8\u4f5b\u5927\u5b66\u91cf\u5b50\u79d1\u5b66\u4e0e\u5de5\u7a0b\u9879\u76ee\u7684\u535a\u58eb\u751f\uff0c\u7814\u7a76\u65b9\u5411\u662f\u91cf\u5b50\u4fe1\u606f\u4e0e\u7269\u7406\u5b66\u7684\u4ea4\u53c9\u9886\u57df\u3002\u4ed6\u672c\u79d1\u6bd5\u4e1a\u4e8e\u52a0\u5229\u798f\u5c3c\u4e9a\u5927\u5b66\u4f2f\u514b\u5229\u5206\u6821\u3002\u4ed6\u8868\u793a\uff1a\u300c\u603b\u4f53\u6765\u8bf4\uff0c\u6211\u5bf9\u590d\u6742\u6027\u95ee\u9898\u975e\u5e38\u611f\u5174\u8da3\u3002\u300d\u5176\u4e2d\u65e2\u6709\u7269\u7406\u7cfb\u7edf\u4e2d\u7684\u590d\u6742\u6027\uff0c\u4e5f\u5305\u542b\u8ba1\u7b97\u673a\u79d1\u5b66\u4e2d\u7684\u7b97\u6cd5\u590d\u6742\u6027\u3002<\/section>\n
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\u97e9\u8fdf \u00a0\u4f0a\u5229\u8bfa\u4f0a\u5927\u5b66\u5384\u5df4\u7eb3 \u2014 \u9999\u69df\u5206\u6821<\/strong><\/section>\n
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\u4e2a\u4eba\u4e3b\u9875\uff1ahttps:\/\/glaciohound.github.io\/<\/section>\n
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\u97e9\u8fdf\uff08Chi Han\uff09\u7684\u957f\u671f\u7814\u7a76\u76ee\u6807\u662f\u53d1\u5c55\u8bed\u8a00\u6a21\u578b\u79d1\u5b66\uff08the science of language models\uff09\u3002\u4ed6\u8868\u793a\u81ea\u5df1\u7684\u7814\u7a76\u65b9\u5411\u662f\u89e3\u7b54\u8fd9\u4e9b\u95ee\u9898\uff1a\u6bcf\u4e2a\u9690\u85cf\u8868\u793a\u5728 LLM \u4e2d\u626e\u6f14\u4ec0\u4e48\u89d2\u8272\uff1f\u5b83\u4eec\u4f55\u65f6\u4f1a\u51fa\u73b0\u6545\u969c\u6216\u5bfc\u81f4\u8fdd\u53cd\u76f4\u89c9\u7684\u73b0\u8c61\uff1f\u6211\u4eec\u5982\u4f55\u8c03\u6574\u673a\u5236\u4ee5\u8d85\u8d8a\u5176\u56fa\u6709\u9650\u5236\u5e76\u66f4\u597d\u5730\u670d\u52a1\u4e8e\u4e0b\u6e38\u4efb\u52a1\uff1f<\/section>\n
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\u4e3a\u6b64\uff0c\u4ed6\u4e00\u76f4\u5728\u5bf9 LLM \u9690\u85cf\u8868\u793a LM \u8fdb\u884c\u7406\u8bba\u548c\u5b9e\u8bc1\u5206\u6790\uff0c\u65e8\u5728\u63d0\u4f9b\u89c1\u89e3\u5e76\u4e3a LM \u5f00\u53d1\u6709\u7528\u7684\u5de5\u5177\u548c\u89e3\u51b3\u65b9\u6848\u3002\u6b64\u5916\uff0cAI \u4e0e\u673a\u5668\u5b66\u4e60\u7684\u5305\u5bb9\u6027\u4e5f\u662f\u5176\u611f\u5174\u8da3\u7684\u8bfe\u9898\u3002<\/section>\n
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\u4ed6\u662f ACL 2024 \u6770\u51fa\u8bba\u6587\u300aWord Embeddings Are Steers for Language Models\u300b\u4ee5\u53ca NAACL 2024 \u6770\u51fa\u8bba\u6587\u300aLM-Infinite: Zero-Shot Extreme Length Generalization for Large Language Models\u300b\u7684\u7b2c\u4e00\u4f5c\u8005\u3002<\/section>\n
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\u53e6\u5916\uff0c\u97e9\u8fdf\u4e0d\u4ec5\u83b7\u5f97\u4e86 IBM \u535a\u58eb\u5956\u5b66\u91d1\uff0c\u4e5f\u83b7\u5f97\u4e86 2025-2026 \u5e74\u5ea6\u7684\u4e9a\u9a6c\u900a AICE \u535a\u58eb\u5956\u5b66\u91d1\u3002<\/section>\n
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\u97e9\u8fdf\u7684\u5bfc\u5e08\u662f Heng Ji\u3002\u6b64\u524d\uff0c\u4ed6\u4e8e\u6e05\u534e\u5927\u5b66\u59da\u73ed\u83b7\u5f97\u5b66\u58eb\u5b66\u4f4d\u3002\u9884\u8ba1 2026 \u5e74 6 \u6708\u6bd5\u4e1a\u3002<\/section>\n
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Chulin Xie \u00a0\u4f0a\u5229\u8bfa\u4f0a\u5927\u5b66\u5384\u5df4\u7eb3 \u2014 \u9999\u69df\u5206\u6821<\/strong><\/section>\n
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\u4e2a\u4eba\u4e3b\u9875\uff1ahttps:\/\/alphapav.github.io\/<\/section>\n
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Chulin Xie \u7684\u7814\u7a76\u65b9\u5411\u4e3b\u8981\u662f\u53ef\u4fe1\u673a\u5668\u5b66\u4e60\u548c\u4f18\u5316\uff0c\u672c\u79d1\u6bd5\u4e1a\u4e8e\u6d59\u6c5f\u5927\u5b66\u3002\u5979\u662f NeurIPS 2023 \u6770\u51fa\u8bba\u6587\u300aDecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models\u300b\u7684\u5171\u4e00\u4f5c\u8005\uff0c\u8be5\u8bba\u6587\u4e3a\u8bc4\u4f30 GPT \u7684\u53ef\u4fe1\u5ea6\u6784\u5efa\u4e86\u4e00\u4e2a\u7cfb\u7edf\u6027\u7684\u57fa\u51c6\u3002<\/section>\n

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\u5218\u7f61 \u00a0\u5723\u6bcd\u5927\u5b66<\/strong><\/section>\n
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\u4e2a\u4eba\u4e3b\u9875\uff1ahttps:\/\/liugangcode.github.io\/<\/section>\n
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\u5218\u7f61\uff08Gang Liu\uff09\u662f\u5723\u6bcd\u5927\u5b66\u8ba1\u7b97\u673a\u79d1\u5b66\u4e0e\u5de5\u7a0b\u4e13\u4e1a\u56db\u5e74\u7ea7\u535a\u58eb\u751f\u3002\u4ed6\u4e8e 2021 \u5e74\u5728\u4e2d\u56fd\u897f\u5357\u5927\u5b66\u83b7\u5f97\u8f6f\u4ef6\u5de5\u7a0b\u5b66\u58eb\u5b66\u4f4d\u3002<\/section>\n
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\u4ed6\u7684\u7814\u7a76\u65b9\u5411\u5305\u62ec\u56fe\u673a\u5668\u5b66\u4e60\u7684\u6570\u636e\u548c\u5b66\u4e60\u57fa\u7840\u3001\u56fe\u673a\u5668\u5b66\u4e60\u7684\u6a21\u578b\u57fa\u7840\uff08\u5305\u62ec\u751f\u6210\u5f0f\u6a21\u578b\u3001\u591a\u6a21\u6001\u5206\u5b50\u8868\u5f81\u5b66\u4e60\u3001\u591a\u6a21\u6001\u5927\u578b\u8bed\u8a00\u6a21\u578b\uff09\u3001\u5c06\u56fe\u673a\u5668\u5b66\u4e60\u7528\u4e8e\u79d1\u5b66\u53d1\u73b0\uff08\u5c24\u5176\u662f\u65b0\u6750\u6599\uff09\u3002<\/section>\n

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Hao-Yu Lan \u00a0\u666e\u6e21\u5927\u5b66<\/strong><\/section>\n
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Hao-Yu Lan \u662f\u666e\u6e21\u5927\u5b66\u7535\u6c14\u4e0e\u8ba1\u7b97\u673a\u5de5\u7a0b\u7cfb\u5728\u8bfb\u535a\u58eb\uff0c\u7814\u7a76\u65b9\u5411\u662f\u8d85\u8d8a CMOS \u65f6\u4ee3\u7684\u3001\u57fa\u4e8e\u4e8c\u7ef4\u534a\u5bfc\u4f53\u7684\u7eb3\u7c73\u7535\u5b50\u5b66\u3002\u4ed6\u672c\u79d1\u6bd5\u4e1a\u4e8e\u6210\u529f\u5927\u5b66\uff0c\u540e\u5728\u53f0\u6e7e\u5927\u5b66\u53d6\u5f97\u7855\u58eb\u5b66\u4f4d\uff0c\u5e76\u5728\u53f0\u79ef\u7535\u62c5\u4efb\u8fc7\u7814\u53d1\u5de5\u7a0b\u5e08\u3002<\/section>\n
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\u9004\u90c1\u4efb \u534e\u76db\u987f\u5927\u5b66<\/strong><\/section>\n
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\u4e2a\u4eba\u4e3b\u9875\uff1ahttps:\/\/homes.cs.washington.edu\/~ypang2\/<\/section>\n
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\u9004\u90c1\u4efb\uff08Rock Yuren Pang\uff09\u662f\u534e\u76db\u987f\u5927\u5b66 Paul G. Allen \u8ba1\u7b97\u673a\u79d1\u5b66\u4e0e\u5de5\u7a0b\u5b66\u9662\u7684\u4e94\u5e74\u7ea7\u535a\u58eb\u751f\u3002\u4ed6\u7684\u7814\u7a76\u4e3b\u9898\u662f\u8d1f\u8d23\u4efb\u7684\u4eba\u5de5\u667a\u80fd\u548c\u4eba\u673a\u4ea4\u4e92\uff0c\u76ee\u6807\u662f\u5c06\u8d1f\u8d23\u4efb\u8ba1\u7b97\u7684\u76ee\u6807\u4e0e\u8ba1\u7b97\u7814\u7a76\u5b9e\u8df5\u7684\u73b0\u5b9e\u76f8\u7ed3\u5408\u3002\u4ed6\u8868\u793a\uff1a\u300c\u6211\u76ee\u524d\u7684\u7814\u7a76\u91cd\u5fc3\u662f\u6784\u5efa\u65b0\u5de5\u5177\uff0c\u4ee5\u652f\u6301\u7814\u7a76\u4eba\u5458\u548c\u4ece\u4e1a\u8005\u4e86\u89e3\u73b0\u6709\u7684\u5927\u89c4\u6a21\u504f\u89c1\uff0c\u5e76\u5229\u7528\u7fa4\u4f53\u667a\u6167\u9884\u6d4b\u6f5c\u5728\u7684\u4e0d\u5229\u5f71\u54cd\u3002\u300d\u4ed6\u8fd8\u5bf9\u53ef\u83b7\u5f97\u6027\u3001\u6570\u636e\u53ef\u89c6\u5316\u3001\u6280\u672f\u548c HCI \u7684\u8de8\u6587\u5316\u53ef\u7528\u6027\u611f\u5174\u8da3\u3002<\/section>\n
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\u9004\u90c1\u4efb\u662f\u4e00\u4f4d\u5c71\u4e1c\u7701\u9752\u5c9b\u7b2c\u4e8c\u4e2d\u5b66\u6821\u53cb\uff0c\u4e4b\u540e\u5728\u739b\u5361\u83b1\u65af\u7279\u5b66\u9662\u83b7\u5f97\u4e86\u6570\u5b66\u5b66\u58eb\u5b66\u4f4d\u3002<\/section>\n
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\u51af\u5c1a\u5f6c \u7f8e\u56fd\u534e\u76db\u987f\u5927\u5b66<\/strong><\/section>\n
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\u51af\u5c1a\u5f6c\uff08Shangbin Feng\uff09\u672c\u79d1\u5c31\u8bfb\u4e8e\u897f\u5b89\u4ea4\u901a\u5927\u5b66\uff0c\u73b0\u5728\u534e\u76db\u987f\u5927\u5b66\u653b\u8bfb\u535a\u58eb\u5b66\u4f4d\uff0c\u5e08\u4ece Yulia Tsvetkov\u3002\u4ed6\u7684\u7814\u7a76\u9886\u57df\u5305\u62ec\u81ea\u7136\u8bed\u8a00\u5904\u7406\u3001\u77e5\u8bc6\u56fe\u8c31\u3001\u793e\u4ea4\u7f51\u7edc\u5206\u6790\u7b49\u3002<\/section>\n
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2023 \u5e74\uff0c\u51af\u5c1a\u5f6c\u4ee5\u4e00\u4f5c\u8eab\u4efd\u64b0\u5199\u7684\u8bba\u6587\u300aFrom Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models\u300b\u62ff\u5230\u4e86 ACL 2023 \u6700\u4f73\u8bba\u6587\u5956\u30022024 \u5e74\uff0c\u4ed6\u7684\u4e00\u4f5c\u8bba\u6587\u300aDon’t Hallucinate, Abstain: Identifying LLM Knowledge Gaps via Multi-LLM Collaboration\u300b\u62ff\u5230\u4e86 ACL 2024 \u6770\u51fa\u8bba\u6587\u5956\u3002<\/section>\n
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\u4e2a\u4eba\u4e3b\u9875\uff1ahttps:\/\/bunsenfeng.github.io\/<\/section>\n
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\u5353\u8d8a \u00a0\u6fb3\u5927\u5229\u4e9a\u8499\u7eb3\u58eb\u5927\u5b66<\/strong><\/section>\n
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\u5353\u8d8a\uff08Terry Yue Zhuo\uff09 \u76ee\u524d\u5728 CSIRO \u7684 Data61 \u548c\u8499\u7eb3\u58eb\u5927\u5b66\u653b\u8bfb\u535a\u58eb\u5b66\u4f4d\u3002\u4ed6\u73b0\u4efb\u8ba1\u7b97\u673a\u667a\u80fd\u9879\u76ee\uff08Computer Intelligence Project\uff09\u7684\u8d1f\u8d23\u4eba\uff0c\u8fd9\u662f\u7531 Meta \u548c IBM \u7275\u5934\u7684 AI \u8054\u76df\uff08AI Alliance\uff09\u7684\u6838\u5fc3\u9879\u76ee\u3002<\/section>\n
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