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\u6587\u7ae0\u6765\u6e90\u4e8e\u4e92\u8054\u7f51:2025\u82f9\u679cAI\u5b66\u8005\u540d\u5355\u516c\u5e03\uff0c\u9ec4\u5b50\u742a\u3001\u5b54\u4ee4\u4e1c\u3001\u5317\u5927\u5409\u5609\u94ed\u3001\u6e05\u534e\u987e\u715c\u8d24\u7b4912\u4f4d\u5e74\u8f7b\u534e\u4eba\u5165\u9009<\/a><\/p>\n

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\u4ed6\u4eec\u90fd\u662f\u6765\u81ea\u5168\u7403\u7684\u5e74\u8f7b AI \u5b66\u672f\u65b0\u661f\u3002<\/section>\n<\/section>\n<\/blockquote>\n
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\u521a\u521a\uff0c\u82f9\u679c\u673a\u5668\u5b66\u4e60\u7814\u7a76\u4e2d\u5fc3\uff08Apple Machine Learning Research\uff09\u6b63\u5f0f\u516c\u5e03\u4e86 2025 \u5e74 AI\uff08\u4eba\u5de5\u667a\u80fd\uff09\u3001ML\uff08\u673a\u5668\u5b66\u4e60\uff09\u9886\u57df\u83b7\u5f97\u535a\u58eb\u751f\u5956\u5b66\u91d1\u7684\u300c\u82f9\u679c\u5b66\u8005\u300d\u540d\u5355\u3002<\/section>\n
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\u4eca\u5e74\u5171\u6709 21 \u4f4d\u5e74\u8f7b\u5b66\u8005\u83b7\u5f97\u4e86\u82f9\u679c\u5b66\u8005\u8ba1\u5212\u7684\u8d44\u52a9\uff0c\u534e\u4eba\u5360\u4e86\u4e00\u534a\u591a\u3002<\/section>\n
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\u82f9\u679c\u535a\u58eb\u5956\u5b66\u91d1\u65e8\u5728\u5956\u52b1\u548c\u652f\u6301\u8ba1\u7b97\u673a\u79d1\u5b66\u4e0e\u5de5\u7a0b\u9886\u57df\u6781\u5177\u6f5c\u529b\u7684\u535a\u58eb\u7814\u7a76\u751f\u5f00\u5c55\u7814\u7a76\uff0c\u6bcf\u5e74\u9881\u53d1\u4e00\u6b21\uff0c\u4eca\u5e74\u5df2\u662f\u7b2c\u516d\u5e74\u3002\u83b7\u5956\u8005\u4e0d\u4ec5\u53ef\u4ee5\u83b7\u5f97\u5956\u5b66\u91d1\u652f\u6301\uff0c\u8fd8\u80fd\u5f97\u5230\u82f9\u679c\u5b9e\u4e60\u673a\u4f1a\u548c\u82f9\u679c\u7814\u7a76\u5458\u7684\u5b66\u672f\u6307\u5bfc\u3002<\/section>\n
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\u5728\u53c2\u4e0e\u82f9\u679c\u7684\u5de5\u4f5c\u671f\u95f4\uff0c\u5386\u5e74\u7684\u5e74\u8f7b\u5b66\u8005\u5df2\u7ecf\u5171\u540c\u64b0\u5199\u4e86 50 \u591a\u7bc7\u9876\u4f1a\u8bba\u6587\u3002\u00a0<\/section>\n
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\u4ee5\u4e0b\u662f\u672c\u5e74\u5ea6\u83b7\u5f97\u5956\u5b66\u91d1\u7684\u90e8\u5206\u5b66\u8005\uff1a<\/section>\n
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Ruei-Che Chang<\/strong><\/section>\n
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Ruei-Che Chang \u662f\u5bc6\u6b47\u6839\u5927\u5b66\u8ba1\u7b97\u673a\u79d1\u5b66\u4e13\u4e1a\u7684\u535a\u58eb\u7814\u7a76\u751f\uff0c\u5bfc\u5e08\u662f\u90ed\u5b89\u9e3f\uff08Anhong Guo\uff09\u3002\u4ed6\u7684\u7814\u7a76\u4e13\u6ce8\u4e8e\u8bbe\u8ba1\u4ea4\u4e92\u5f0f\u4eba\u673a\u4ea4\u4e92\u7cfb\u7edf\uff0c\u52a9\u529b\u73b0\u5b9e\u4e16\u754c\u7684\u65e0\u969c\u788d\u5efa\u8bbe\u3002\u4ed6\u7684\u7814\u7a76\u91cd\u70b9\u662f\u5f00\u53d1\u80fd\u591f\u7406\u89e3\u548c\u63cf\u8ff0\u76f2\u4eba\u6216\u89c6\u969c\u4eba\u58eb\u73b0\u5b9e\u4e16\u754c\u5468\u56f4\u73af\u5883\u7684\u667a\u80fd\u4f53\uff0c\u5176\u6280\u672f\u6838\u5fc3\u53ef\u4ee5\u9002\u5e94\u66f4\u5e7f\u6cdb\u7684\u73af\u5883\u3002<\/section>\n
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\u5728\u653b\u8bfb\u535a\u58eb\u5b66\u4f4d\u671f\u95f4\uff0c\u4ed6\u5728 Meta Reality Labs \u5b9e\u4e60\u3002\u5728\u6b64\u4e4b\u524d\uff0c\u4ed6\u66fe\u5728\u8fbe\u7279\u8305\u65af\u5b66\u9662\u83b7\u5f97\u8ba1\u7b97\u673a\u79d1\u5b66\u7855\u58eb\u5b66\u4f4d\uff0c\u5e76\u5728\u53f0\u6e7e\u6210\u529f\u5927\u5b66\u83b7\u5f97\u7535\u6c14\u5de5\u7a0b\u5b66\u58eb\u5b66\u4f4d\u3002<\/section>\n
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\u4e2a\u4eba\u4e3b\u9875\uff1ahttps:\/\/rueichechang.github.io\/<\/section>\n
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Cathy Mengying Fang<\/strong><\/section>\n
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Cathy Mengying Fang \u662f\u9ebb\u7701\u7406\u5de5\u5b66\u9662\uff08MIT\uff09\u5a92\u4f53\u5b9e\u9a8c\u5ba4\u6d41\u4f53\u4ea4\u4e92\u5c0f\u7ec4\uff08Fluid Interfaces Group\uff09\u535a\u58eb\u7814\u7a76\u751f\u3002\u5979\u7684\u7814\u7a76\u7acb\u8db3\u4e8e\u6280\u672f\u4e0e\u4eba\u7c7b\u4f53\u9a8c\u7684\u4ea4\u53c9\u9886\u57df\uff0c\u81f4\u529b\u4e8e\u6d88\u9664\u6570\u5b57\u4e0e\u7269\u7406\u4e16\u754c\u4e4b\u95f4\u7684\u754c\u9650\uff0c\u901a\u8fc7\u6df7\u5408\u73b0\u5b9e\uff08mixed reality\uff09\u3001\u4eba\u5de5\u667a\u80fd\uff08artificial intelligence\uff09\u548c\u53ef\u7a7f\u6234\u8bbe\u5907\uff08wearable devices\uff09\u7b49\u6280\u672f\uff0c\u63d0\u5347\u4eba\u7c7b\u4e0e\u73af\u5883\u7684\u4e92\u52a8\u65b9\u5f0f\u53ca\u81ea\u6211\u8ba4\u77e5\u3002<\/section>\n
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\u5979\u5df2\u83b7\u5f97\u9ebb\u7701\u7406\u5de5\u5b66\u9662\u7855\u58eb\u5b66\u4f4d\uff0c\u4ee5\u53ca\u5361\u5185\u57fa\u6885\u9686\u5927\u5b66\uff08Carnegie Mellon University\uff09\u673a\u68b0\u5de5\u7a0b\u548c\u4eba\u673a\u4ea4\u4e92\uff08Human-Computer Interaction\uff09\u4e13\u4e1a\u8363\u8a89\u5b66\u58eb\u5b66\u4f4d\u3002\u5728\u5b66\u672f\u63a2\u7d22\u4e4b\u5916\uff0c\u5979\u66fe\u5148\u540e\u5728\u5fae\u8f6f\uff08Microsoft\uff09\u3001\u82f9\u679c\uff08Apple\uff09\u3001IDEO \u548c Magic Leap \u7b49\u77e5\u540d\u4f01\u4e1a\u79ef\u7d2f\u5b9e\u8df5\u7ecf\u9a8c\u3002<\/section>\n
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\u4e2a\u4eba\u4e3b\u9875\uff1ahttps:\/\/cathy-fang.com\/about.html<\/section>\n
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\u987e\u715c\u8d24 \uff08Yuxian Gu\uff09<\/strong><\/section>\n
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\u987e\u715c\u8d24\uff08Yuxian Gu\uff09\u662f\u6e05\u534e\u5927\u5b66\u8ba1\u7b97\u673a\u79d1\u5b66\u4e0e\u6280\u672f\u7cfb\u4ea4\u4e92\u5f0f\u4eba\u5de5\u667a\u80fd\uff08CoAI\uff09\u8bfe\u9898\u7ec4\u7684\u56db\u5e74\u7ea7\u535a\u58eb\u751f\uff0c\u5e08\u4ece\u9ec4\u6c11\u70c8\u6559\u6388\u3002\u4ed6\u7684\u7814\u7a76\u805a\u7126\u4e8e\u8bed\u8a00\u6a21\u578b\u5168\u751f\u547d\u5468\u671f\u7684\u9ad8\u6548\u7b97\u6cd5\u5f00\u53d1\uff0c\u6db5\u76d6\u9884\u8bad\u7ec3\u3001\u4e0b\u6e38\u9002\u914d\u53ca\u63a8\u7406\u8fc7\u7a0b\u3002\u8fd1\u671f\uff0c\u4ed6\u7684\u5de5\u4f5c\u91cd\u70b9\u653e\u5728\u5927\u578b\u8bed\u8a00\u6a21\u578b (LLMs) \u7684\u6570\u636e\u7b56\u5212\u7b56\u7565\u7814\u7a76\u3001\u9ad8\u6548\u6a21\u578b\u67b6\u6784\u8bbe\u8ba1\uff0c\u4ee5\u53ca\u8fd0\u7528\u77e5\u8bc6\u84b8\u998f\u6280\u672f (knowledge distillation) \u8fdb\u884c\u8bed\u8a00\u6a21\u578b (LM) \u538b\u7f29\u3002\u6b64\u524d\uff0c\u4ed6\u66fe\u5728\u5fae\u8f6f\u4e9a\u6d32\u7814\u7a76\u9662\u5b9e\u4e60\uff0c\u7531\u8463\u529b\u535a\u58eb\u6307\u5bfc\u3002<\/section>\n
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\u4e2a\u4eba\u4e3b\u9875\uff1ahttps:\/\/t1101675.github.io\/<\/section>\n
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Tiancheng Hu<\/strong><\/section>\n
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Tiancheng Hu \u662f\u5251\u6865\u5927\u5b66\u8bed\u8a00\u6280\u672f\u5b9e\u9a8c\u5ba4\u7684\u8ba1\u7b97\u3001\u8ba4\u77e5\u4e0e\u8bed\u8a00\u65b9\u5411\u7684\u4e09\u5e74\u7ea7\u535a\u58eb\u751f\uff0c\u5e08\u4ece Nigel Collier \u6559\u6388\u3002\u4ed6\u7684\u7814\u7a76\u4e13\u6ce8\u4e8e\u6784\u5efa\u80fd\u591f\u771f\u5b9e\u6a21\u62df\u7fa4\u4f53\u548c\u4e2a\u4f53\u5c42\u9762\u4eba\u7c7b\u884c\u4e3a\u7684\u4eba\u5de5\u667a\u80fd (AI) \u7cfb\u7edf\uff0c\u76ee\u6807\u662f\u521b\u9020\u80fd\u591f\u771f\u6b63\u7406\u89e3\u5e76\u9002\u5e94\u5168\u7403\u591a\u6837\u5316\u4eba\u7c7b\u89c2\u70b9\u7684\u4eba\u5de5\u667a\u80fd\u3002<\/section>\n
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\u4ed6\u5df2\u83b7\u5f97\u82cf\u9ece\u4e16\u8054\u90a6\u7406\u5de5\u5b66\u9662\u7535\u6c14\u5de5\u7a0b\u4e0e\u4fe1\u606f\u6280\u672f\u7855\u58eb\u5b66\u4f4d\uff0c\u4ee5\u53ca\u5fb7\u514b\u8428\u65af\u5927\u5b66\u8fbe\u62c9\u65af\u5206\u6821\u7535\u6c14\u5de5\u7a0b\u7406\u5b66\u5b66\u58eb\u5b66\u4f4d\u3002\u5176\u7855\u58eb\u8bba\u6587\u7814\u7a76\u7f8e\u56fd\u653f\u6cbb\u65b0\u95fb\u4e2d\u7684\u5f15\u8ff0\u7528\u6cd5\u3002\u4ed6\u66fe\u5728 Carlos Busso \u6559\u6388\u7684\u6307\u5bfc\u4e0b\u7814\u7a76\u5229\u7528 3D \u6570\u636e\u8fdb\u884c\u9a7e\u9a76\u5458\u5934\u90e8\u59ff\u6001\u4f30\u8ba1\uff0c\u79ef\u7d2f\u4e86\u5b9d\u8d35\u7684\u5b9e\u8df5\u7ecf\u9a8c\u3002<\/section>\n
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\u4e2a\u4eba\u4e3b\u9875\uff1ahttps:\/\/tiancheng.hu\/<\/section>\n
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\u9ec4\u5b50\u742a\uff08Ziqi Huang\uff09<\/strong><\/section>\n
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\u9ec4\u5b50\u742a\u662f MMLab@NTU \u7684\u4e09\u5e74\u7ea7\u535a\u58eb\u751f\uff0c\u5e08\u4ece\u5218\u5b50\u7eac\u6559\u6388\uff0c2022 \u5e74\u672c\u79d1\u6bd5\u4e1a\u4e8e\u65b0\u52a0\u5761\u5357\u6d0b\u7406\u5de5\u5927\u5b66\u3002\u5979\u5728 CVPR\u3001ICCV\u3001ECCV\u3001SIGGRAPH Asia\u3001TPAMI \u7b49\u56fd\u9645\u9876\u7ea7\u4f1a\u8bae\u4e0e\u671f\u520a\u4e0a\u53d1\u8868\u591a\u7bc7\u7814\u7a76\u6210\u679c\u3002\u5176\u7814\u7a76\u65b9\u5411\u4e3a\u89c6\u89c9\u751f\u6210\u6a21\u578b\uff0c\u91cd\u70b9\u5173\u6ce8\u751f\u6210\u3001\u7f16\u8f91\u53ca\u76f8\u5173\u7cfb\u7edf\u7684\u8bc4\u4f30\u65b9\u6cd5\u3002\u81f4\u529b\u4e8e\u6784\u5efa\u4ee5\u4eba\u4e3a\u4e2d\u5fc3\u7684\u89c6\u89c9\u751f\u6210\u6846\u67b6\uff0c\u63d0\u5347\u6a21\u578b\u4e0e\u4eba\u7c7b\u610f\u56fe\u7684\u5bf9\u9f50\u4e0e\u4ea4\u4e92\u80fd\u529b\uff0c\u63a8\u52a8\u66f4\u76f4\u89c2\u3001\u7075\u6d3b\u7684\u89c6\u89c9\u5185\u5bb9\u521b\u4f5c\u3002\u5979\u7684\u7814\u7a76\u6210\u679c\u5982 Collaborative Diffusion \u548c ReVersion \u53d7\u5230\u793e\u533a\u5e7f\u6cdb\u5173\u6ce8\uff1b\u4e3b\u5bfc\u7684 VBench \u7cfb\u5217\u5de5\u4f5c\u5df2\u6210\u4e3a\u89c6\u9891\u751f\u6210\u9886\u57df\u7684\u6743\u5a01\u8bc4\u6d4b\u4f53\u7cfb\uff0c\u88ab\u5b66\u672f\u754c\u548c\u5de5\u4e1a\u754c\u5e7f\u6cdb\u91c7\u7528\uff0c\u534f\u52a9\u63a8\u52a8\u548c\u6307\u5f15\u89c6\u9891\u751f\u6210\u9886\u57df\u7684\u53d1\u5c55\u3002<\/section>\n
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\u4e2a\u4eba\u4e3b\u9875\uff1ahttps:\/\/ziqihuangg.github.io<\/section>\n
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\u5409\u5609\u94ed\uff08Jiaming Ji\uff09<\/strong><\/section>\n
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\u5409\u5609\u94ed\uff0c\u5317\u4eac\u5927\u5b66\u4eba\u5de5\u667a\u80fd\u7814\u7a76\u9662\u535a\u58eb\u751f\u5728\u8bfb\uff0c\u5bfc\u5e08\u4e3a\u6768\u8000\u4e1c\u8001\u5e08\uff0c\u7814\u7a76\u65b9\u5411\u4e3a\u5f3a\u5316\u5b66\u4e60\u3001\u5927\u6a21\u578b\u7684\u5b89\u5168\u4e0e\u4ef7\u503c\u5bf9\u9f50\uff0c\u5728\u8ba1\u7b97\u673a\u9876\u7ea7\u4f1a\u8bae\u671f\u520a\u53d1\u8868\u53e3\u5934\u3001\u7126\u70b9\u8bba\u6587\u7b49\u5341\u4f59\u7bc7\uff0c\u8c37\u6b4c\u5b66\u672f\u5f15\u7528\u7d2f\u8ba1 2200 \u4f59\u6b21\uff0cGitHub \u5f00\u6e90\u7d2f\u8ba1\u83b7\u5f97 2W+ Stars\u3002\u66fe\u83b7\u9996\u6279\u56fd\u81ea\u7136\u535a\u58eb\u9752\u5e74\u57fa\u91d1\u8d44\u52a9\uff082023 \u5e74\u5ea6\u5317\u4eac\u5927\u5b66\u667a\u80fd\u5b66\u79d1\u552f\u4e00\uff09\uff0c\u83b7\u5317\u4eac\u5927\u5b66\u535a\u58eb\u6700\u9ad8\u7814\u7a76\u5956\u300c\u6821\u957f\u5956\u5b66\u91d1\u300d\uff0c \u9996\u5c4a\u4e2d\u56fd\u7535\u5b50\u5b66\u4f1a \u2014 \u817e\u8baf\u535a\u58eb\u751f\u79d1\u7814\u6fc0\u52b1\u8ba1\u5212\uff08\u5168\u56fd 17 \u4eba\uff09\uff0c\u83b7 NeurIPS\u201822 \u673a\u5668\u4eba\u7075\u5de7\u64cd\u4f5c\u6bd4\u8d5b\u51a0\u519b\uff0c\u7814\u7a76\u6210\u679c\u53ca\u6a21\u578b\u88ab OpenAI \u3001Meta \u5f15\u7528\uff0c\u88ab MIT Tech Review \u62a5\u9053\u3002\u00a0<\/section>\n
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\u4e2a\u4eba\u4e3b\u9875\uff1ahttps:\/\/jijiaming.com\/<\/section>\n
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\u5b54\u4ee4\u4e1c\uff08Lingdong Kong\uff09<\/strong><\/section>\n
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\u5b54\u4ee4\u4e1c\u662f\u65b0\u52a0\u5761\u56fd\u7acb\u5927\u5b66\u8ba1\u7b97\u673a\u7cfb\u7684\u4e09\u5e74\u7ea7\u535a\u58eb\u751f\uff0c\u5bfc\u5e08\u662f Wei Tsang Ooi \u6559\u6388\u548c\u5218\u5b50\u7eac\u6559\u6388\u3002\u4ed6\u7684\u7814\u7a76\u65b9\u5411\u4e3a 3D \u8ba1\u7b97\u673a\u89c6\u89c9\u548c\u6df1\u5ea6\u5b66\u4e60\uff0c\u53ca\u5176\u5728\u81ea\u52a8\u9a7e\u9a76\u3001\u673a\u5668\u4eba\u7b49\u573a\u666f\u7684\u5e94\u7528\u3002<\/section>\n
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\u4ed6\u66fe\u4e8e\u82f1\u4f1f\u8fbe\u3001\u5b57\u8282\u8df3\u52a8\u548c\u4e0a\u6d77\u4eba\u5de5\u667a\u80fd\u5b9e\u9a8c\u5ba4\u7b49\u673a\u6784\u5b9e\u4e60\u3002\u4e00\u4f5c\u8bba\u6587\u53d1\u8868\u4e8e CVPR\u3001ICCV\u3001ECCV\u3001NeurIPS \u7b49\u56fd\u9645\u4f1a\u8bae\u4e2d\uff0c\u8c37\u6b4c\u5b66\u672f\u5f15\u7528\u8d85\u8fc7 2400 \u4f59\u6b21\u3002<\/section>\n
<\/a><\/section>\n
\u4e2a\u4eba\u4e3b\u9875\uff1ahttps:\/\/ldkong.com<\/section>\n
<\/section>\n
Tian (Sunny) Qin<\/strong><\/section>\n
<\/section>\n
Tian (Sunny) Qin \u662f\u54c8\u4f5b\u5927\u5b66\u7684\u4e00\u540d\u4e09\u5e74\u7ea7\u535a\u58eb\u751f\uff0c\u7531 David Alvarez-Melis \u548c Sham Kakade \u5171\u540c\u6307\u5bfc\u3002<\/section>\n
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\u5979\u7684\u7814\u7a76\u91cd\u70b9\u662f\u6570\u636e\u9a71\u52a8\u7684\u4eba\u5de5\u667a\u80fd\u548c\u57fa\u7840\u6a21\u578b\u79d1\u5b66\u3002\u901a\u8fc7\u5f00\u53d1\u5408\u6210\u6570\u636e\u751f\u6210\u65b9\u6cd5\u5e76\u6df1\u5316\u5bf9\u6a21\u578b\u5b66\u4e60\u52a8\u6001\u7684\u7406\u89e3\uff0c\u63d0\u9ad8\u5c0f\u578b\u8bed\u8a00\u6a21\u578b\u7684\u63a8\u7406\u80fd\u529b\u548c\u5206\u5e03\u5916\u6cdb\u5316\u80fd\u529b\u3002<\/section>\n
<\/a><\/section>\n
\u4e2a\u4eba\u4e3b\u9875\uff1ahttps:\/\/sunnytqin.github.io\/<\/section>\n
<\/section>\n
\u738b\u5e7f\u8f89\uff08Guanghui Wang\uff09<\/strong><\/section>\n
<\/section>\n
\u738b\u5e7f\u8f89\uff08Guanghui Wang\uff09\u662f\u4f50\u6cbb\u4e9a\u7406\u5de5\u5b66\u9662\u7684\u56db\u5e74\u7ea7\u535a\u58eb\u751f\uff0c\u5e08\u4ece Jacob Abernethy \u548c Vidya Muthukumar\u3002\u4ed6\u7684\u7814\u7a76\u5174\u8da3\u4e3b\u8981\u96c6\u4e2d\u5728\u673a\u5668\u5b66\u4e60\u7406\u8bba\u4e0e\u4f18\u5316\u9886\u57df\u3002\u76ee\u524d\uff0c\u4ed6\u4e3b\u8981\u81f4\u529b\u4e8e\u5f00\u53d1\u80fd\u591f\u9002\u5e94\u591a\u6837\u5316\u73af\u5883\u7684\u7a33\u5065\u4e14\u9ad8\u6548\u7684\u5e8f\u5217\u51b3\u7b56\u65b9\u6cd5\u3002<\/section>\n
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\u738b\u5e7f\u8f89\u4e8e 2020 \u5e74\u5728\u5357\u4eac\u5927\u5b66\u8ba1\u7b97\u673a\u79d1\u5b66\u4e0e\u6280\u672f\u7cfb\u83b7\u5f97\u4e86\u7855\u58eb\u5b66\u4f4d\uff0c\u5e08\u4ece\u5f20\u5229\u519b\u6559\u6388\u3002\u540c\u65f6\uff0c\u4ed6\u4e5f\u662f\u7531\u5468\u5fd7\u534e\u6559\u6388\u9886\u5bfc\u7684 LAMDA \u7814\u7a76\u5c0f\u7ec4\u7684\u4e00\u5458\u30022017 \u5e74\uff0c\u4ed6\u5728\u897f\u5b89\u7535\u5b50\u79d1\u6280\u5927\u5b66\u7535\u5b50\u5de5\u7a0b\u5b66\u9662\u83b7\u5f97\u4e86\u5b66\u58eb\u5b66\u4f4d\u3002<\/section>\n
<\/a><\/section>\n
\u4e2a\u4eba\u4e3b\u9875\uff1ahttps:\/\/guanghui-wang-gatech.github.io\/<\/section>\n
<\/section>\n
\u738b\u5609\u5bb8\uff08Jiachen (Tianhao) Wang\uff09<\/strong><\/section>\n
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\u738b\u5609\u5bb8\uff08Jiachen (Tianhao) Wang\uff09\u662f\u666e\u6797\u65af\u987f\u5927\u5b66\u7684\u535a\u58eb\u7814\u7a76\u751f\uff0c\u4ed6\u7684\u5bfc\u5e08\u662f Prateek Mittal \u6559\u6388\uff0c\u5e76\u4e14\u4e0e Ruoxi Jia \u6559\u6388\u4fdd\u6301\u5bc6\u5207\u5408\u4f5c\u3002\u4ed6\u7684\u7814\u7a76\u4e13\u6ce8\u4e8e\u4ece\u6570\u636e\u89d2\u5ea6\u51fa\u53d1\u7684\u53ef\u4fe1\u673a\u5668\u5b66\u4e60\u3002\u6700\u8fd1\uff0c\u4ed6\u81f4\u529b\u4e8e\u5f00\u53d1\u9002\u7528\u4e8e\u57fa\u7840\u6a21\u578b\u7684\u6570\u636e\u5f52\u56e0\u4e0e\u4f18\u5316\u6280\u672f\u3002\u4ed6\u8fd0\u7528\u7edf\u8ba1\u5b66\u548c\u535a\u5f08\u8bba\u7684\u5de5\u5177\u6765\u5206\u6790\u8bad\u7ec3\u6570\u636e\u4e0e\u6a21\u578b\u884c\u4e3a\u4e4b\u95f4\u7684\u590d\u6742\u8054\u7cfb\u3002<\/section>\n
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2024 \u5e74\uff0c\u4ed6\u88ab\u9009\u4e3a\u6570\u636e\u79d1\u5b66\u65b0\u661f\u3002<\/section>\n
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\u4e2a\u4eba\u4e3b\u9875\uff1ahttps:\/\/tianhaowang.netlify.app\/<\/section>\n
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\u8c22\u82e5\u5b87\uff08Ruoyu (Roy) Xie\uff09<\/strong><\/section>\n
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\u8c22\u82e5\u5b87\uff08Roy Xie\uff09\u662f\u675c\u514b\u5927\u5b66\u7684\u535a\u58eb\u7814\u7a76\u751f\uff0c\u5bfc\u5e08\u662f Bhuwan Dhingra\u3002\u4ed6\u7684\u7814\u7a76\u4e13\u6ce8\u4e8e\u63d0\u5347\u5927\u578b\u8bed\u8a00\u6a21\u578b\u7684\u6548\u7387\u548c\u9c81\u68d2\u6027\u3002\u4ed6\u7684\u5de5\u4f5c\u4e3b\u8981\u7814\u7a76\u4e0a\u4e0b\u6587\u538b\u7f29\uff0c\u5305\u62ec\u4fe1\u606f\u5145\u8db3\u6027\u68c0\u6d4b\u548c\u5185\u5bb9\u7b26\u53f7\u5316\uff0c\u8fd9\u4e9b\u7814\u7a76\u5728\u68c0\u7d22\u589e\u5f3a\u578b\u751f\u6210\u548c\u667a\u80fd\u4f53\u7cfb\u7edf\u4e2d\u6709\u5e94\u7528\u4ef7\u503c\u3002<\/section>\n
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\u76ee\u524d\uff0c\u4ed6\u6b63\u5728\u63a2\u7d22\u5f3a\u5316\u5b66\u4e60\u65b9\u6cd5\uff0c\u4ee5\u63d0\u9ad8 LLM \u7684\u63a8\u7406\u6548\u7387\uff0c\u5c24\u5176\u662f\u5bf9\u4e8e\u6d89\u53ca\u957f\u5e8f\u5217\u7684\u590d\u6742\u4efb\u52a1\u3002<\/section>\n
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\u4e2a\u4eba\u4e3b\u9875\uff1ahttps:\/\/royxie.com\/<\/section>\n
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\u5f90\u8c6a\u98de\uff08Haofei Xu\uff09<\/strong><\/section>\n
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\u5f90\u8c6a\u98de\uff08Haofei Xu\uff09\u662f\u82cf\u9ece\u4e16\u8054\u90a6\u7406\u5de5\u5b66\u9662\uff08ETH Zurich\uff09\u548c\u56fe\u5bbe\u6839\u5927\u5b66\u7684\u535a\u58eb\u7814\u7a76\u751f\uff0c\u5bfc\u5e08\u662f Marc Pollefeys \u548c Andreas Geiger\u3002\u4ed6\u7684\u7814\u7a76\u4e13\u6ce8\u4e8e\u8ba1\u7b97\u673a\u89c6\u89c9\uff0c\u7279\u522b\u662f\u5bc6\u96c6\u5bf9\u5e94\u5173\u7cfb\u3001\u8fd0\u52a8\u3001\u4e09\u7ef4\u4ee5\u53ca\u89c6\u9891\u8868\u793a\u5b66\u4e60\u3002\u4ed6\u7684\u76ee\u6807\u662f\u63a8\u52a8\u901a\u7528\u667a\u80fd\u7cfb\u7edf\u7684\u53d1\u5c55\uff0c\u4ee5\u5b9e\u73b0\u4e09\u7ef4\u91cd\u5efa\u3001\u5408\u6210\u548c\u7406\u89e3\u3002<\/section>\n
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\u5f90\u8c6a\u98de\u5728\u653b\u8bfb\u7855\u58eb\u5b66\u4f4d\u671f\u95f4\u5c31\u8bfb\u4e8e\u4e2d\u56fd\u79d1\u5b66\u6280\u672f\u5927\u5b66\uff08USTC\uff09\uff0c\u5bfc\u5e08\u662f\u5f20\u4e3e\u52c7\uff08Juyong Zhang\uff09\u3002\u5728\u7855\u58eb\u9636\u6bb5\uff0c\u4ed6\u66fe\u4ea4\u6362\u5230\u65b0\u52a0\u5761\u5357\u6d0b\u7406\u5de5\u5927\u5b66\uff08NTU\uff09\uff0c\u5728\u90a3\u91cc\u4ed6\u53d7\u5230\u8521\u5251\u98de\uff08Jianfei Cai\uff09\u548c Jianmin Zheng \u7684\u6307\u5bfc\u3002\u6b64\u5916\uff0c\u4ed6\u8fd8\u66fe\u5728\u5fae\u8f6f\u4e9a\u6d32\u7814\u7a76\u9662\uff08MSRA\uff09\u5b9e\u4e60\uff0c\u671f\u95f4\u5f97\u5230\u4e86\u6768\u86df\u9f99\uff08Jiaolong Yang\uff09\u548c\u7ae5\u6b23\uff08Xin Tong\uff09\u7684\u6307\u5bfc\u3002<\/section>\n
<\/a><\/section>\n
\u4e2a\u4eba\u4e3b\u9875\uff1ahttps:\/\/haofeixu.github.io\/<\/section>\n
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\u5b8c\u6574\u83b7\u5956\u540d\u5355\u5982\u4e0b\uff1a<\/section>\n
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\u53c2\u8003\u94fe\u63a5\uff1ahttps:\/\/machinelearning.apple.com\/work-with-us#scholars<\/sup><\/em><\/section>\n

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