[{"data":1,"prerenderedAt":2726},["ShallowReactive",2],{"home":3,"group":56,"publications":187,"projects":2585,"authors":2620},{"_path":4,"_dir":5,"_draft":6,"_partial":6,"_locale":7,"title":8,"description":7,"photos":9,"body":44,"_type":50,"_id":51,"_source":52,"_file":53,"_stem":54,"_extension":55},"\u002Fsection\u002Fhome","section",false,"","Home",[10,13,16,19,22,24,26,29,32,35,38,41],{"link":11,"title":12},"photo\u002Fgroup_20250910.jpg","Group photo of the team on Teachers' Day 2025",{"link":14,"title":15},"photo\u002Fteam_baiwangshan_2024.jpg","Team building at Baiwangshan in 2024",{"link":17,"title":18},"photo\u002Fgroup_20240910.jpg","Group photo of the team on Teachers' Day 2024",{"link":20,"title":21},"photo\u002Ficlr2024_1.png","ICLR 2024",{"link":23,"title":21},"photo\u002Ficlr2024_2.jpeg",{"link":25,"title":21},"photo\u002Ficlr2024_3.jpeg",{"link":27,"title":28},"photo\u002Fwuxi_2024.jpg","Team building with AIR+ in Wuxi 2024",{"link":30,"title":31},"photo\u002Fbadminton_1.jpg","Xin Hong won the team championship in the university's faculty badminton competition",{"link":33,"title":34},"photo\u002Fbadminton_2.png","Team badminton activity",{"link":36,"title":37},"photo\u002Fatomlab.jpg","Professor Lan's birthday party in 2023",{"link":39,"title":40},"photo\u002Fgroup_2023.jpg","Group photo of the team on Teachers' Day 2023",{"link":42,"title":43},"photo\u002Fgroup_2022.jpg","Group photo of the team on Teachers' Day 2022",{"type":45,"children":46,"toc":47},"root",[],{"title":7,"searchDepth":48,"depth":48,"links":49},2,[],"markdown","content:section:home.md","content","section\u002Fhome.md","section\u002Fhome","md",{"_path":57,"_dir":58,"_draft":6,"_partial":6,"_locale":7,"group":59,"_id":182,"_type":183,"title":184,"_source":52,"_file":185,"_stem":186,"_extension":183},"\u002Fdata\u002Fgroup","data",[60,67,85,94,121,133],{"name":61,"members":62},"Professor",[63],{"name":64,"link":65,"image":66},"Yanyan Lan","https:\u002F\u002Fyanyanlan.com\u002F","\u002Fphoto\u002Flanyanyan.jpg",{"name":68,"members":69},"Postdoc",[70,74,78,82],{"name":71,"link":72,"image":73},"Xin Hong","https:\u002F\u002Fhongxin2019.github.io\u002F","\u002Fphoto\u002Fhongxin.png",{"name":75,"link":76,"image":77},"Yinjun Jia","https:\u002F\u002Febgu.github.io\u002F","\u002Fphoto\u002Fjiayinjun.jpeg",{"name":79,"link":80,"image":81},"Yuying Zhang",null,"\u002Fphoto\u002Fzhangyuying.jpeg",{"name":83,"link":80,"image":84},"Yunfan Jin","\u002Fphoto\u002Fjinyunfan.jpeg",{"name":86,"members":87},"Research Assistant",[88,91],{"name":89,"link":80,"image":90},"Wenyu Zhu","\u002Fphoto\u002Fzhuwenyu.jpeg",{"name":92,"link":80,"image":93},"Yida Cai","\u002Fphoto\u002Fcaiyida.jpeg",{"name":95,"members":96},"Phd Student",[97,101,105,109,112,115,118],{"name":98,"link":99,"image":100},"Yuyan Ni","https:\u002F\u002Fnyyxxx.github.io\u002F","\u002Fphoto\u002Fniyuyan.jpeg",{"name":102,"link":103,"image":104},"Haichuan Tan","https:\u002F\u002Fgithub.com\u002Fthchuan2001","\u002Fphoto\u002Ftanhaichuan.jpg",{"name":106,"link":107,"image":108},"Bowen Gao","https:\u002F\u002Fbowen-gao.github.io\u002F","\u002Fphoto\u002Fgaobowen.jpeg",{"name":110,"link":7,"image":111},"Bicheng Lin","\u002Fphoto\u002Flinbicheng.jpeg",{"name":113,"link":7,"image":114},"Quan Li","\u002Fphoto\u002Fliquan.png",{"name":116,"link":7,"image":117},"Kelin Wu","\u002Fphoto\u002Fwukelin.jpeg",{"name":119,"link":7,"image":120},"Dapeng Jiang","\u002Fphoto\u002Fjiangdapeng.jpeg",{"name":122,"members":123},"Intern",[124,127,130],{"name":125,"link":7,"image":126},"Yuanhuan Mo","\u002Fphoto\u002Fmoyuanhuan.jpeg",{"name":128,"link":7,"image":129},"Zitao Chen","\u002Fphoto\u002Fchenzitao.jpeg",{"name":131,"link":7,"image":132},"Haoming Kong","\u002Fphoto\u002Fkonghaoming.jpeg",{"name":134,"members":135},"Alumni",[136,139,142,146,149,152,155,158,160,162,165,168,171,174,177,180],{"name":137,"link":7,"image":138},"Xingsi Xie","\u002Fphoto\u002Fxiexingsi.jpeg",{"name":140,"link":7,"image":141},"Jianhui Wang","\u002Fphoto\u002Fwangjianhui.jpeg",{"name":143,"link":144,"image":145},"Shikun Feng","https:\u002F\u002Fgithub.com\u002Ffengshikun","\u002Fphoto\u002Ffengshikun.png",{"name":147,"link":7,"image":148},"Yanwen Huang","\u002Fphoto\u002Fhuangyanwen.jpeg",{"name":150,"link":80,"image":151},"Hongliang Li","\u002Fphoto\u002Flihongliang.jpeg",{"name":153,"link":7,"image":154},"Jiaxin Zheng","\u002Fphoto\u002Fzhengjiaxin.jpeg",{"name":156,"link":7,"image":157},"Yuanle Mo","\u002Fphoto\u002Fmoyuanle.jpeg",{"name":159,"link":80},"Gaochao Liu",{"name":161,"link":7},"Minghao Li",{"name":163,"link":7,"image":164},"Minsi Ren","\u002Fphoto\u002Frenminsi.jpeg",{"name":166,"link":7,"image":167},"Bo Qiang","\u002Fphoto\u002Fqiangbo.jpg",{"name":169,"link":170},"Shuzi Niu","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=BpV8PgsAAAAJ",{"name":172,"link":173},"Yadong Zhu","https:\u002F\u002Fwww.yadongzhu.com\u002F",{"name":175,"link":176},"Liang Pang","https:\u002F\u002Fpl8787.github.io\u002F",{"name":178,"link":179},"Hainan Zhang","https:\u002F\u002Fzhanghainan.github.io\u002F",{"name":181,"link":7},"Jianing Li","content:data:group.yaml","yaml","Group","data\u002Fgroup.yaml","data\u002Fgroup",{"_path":188,"_dir":58,"_draft":6,"_partial":6,"_locale":7,"publications":189,"_id":2581,"_type":183,"title":2582,"_source":52,"_file":2583,"_stem":2584,"_extension":183},"\u002Fdata\u002Fpublications",[190,211,255,271,288,305,321,342,358,377,389,399,416,431,445,459,490,508,520,530,543,556,570,583,601,617,632,647,664,684,698,713,726,770,788,802,816,831,843,857,871,886,899,914,927,946,959,973,986,999,1013,1028,1042,1055,1068,1082,1125,1139,1152,1165,1183,1199,1220,1232,1245,1257,1270,1282,1294,1308,1320,1336,1348,1361,1374,1387,1399,1411,1424,1437,1448,1459,1470,1481,1494,1505,1517,1529,1541,1553,1564,1578,1588,1599,1611,1624,1633,1646,1655,1666,1677,1686,1696,1707,1717,1728,1738,1750,1761,1773,1788,1802,1814,1833,1845,1856,1867,1879,1891,1903,1916,1928,1942,1953,1964,1977,1989,2002,2013,2025,2039,2053,2070,2082,2094,2106,2119,2130,2144,2156,2168,2179,2190,2200,2212,2224,2236,2248,2260,2271,2282,2293,2305,2318,2330,2340,2351,2362,2371,2387,2399,2411,2421,2434,2445,2456,2469,2483,2495,2506,2519,2532,2544,2557,2569],{"title":191,"topic":192,"figure":194,"selected":195,"authors":196,"venue":204,"links":207},"Drugging the Undruggable: Benchmarking and Modeling Fragment-Based Screening",[193],"AI4Science","\u002Fimage\u002FFragBench.png",true,[197,198,199,75,89,200,201,147,140,125,202,203,64],"Haichuan Tan*","Bowen Gao*","Jiaxin Li","Wenxuan Xie","Yihong Liu","Ya-Qin Zhang","Wei-Ying Ma",{"name":205,"year":206,"link":7},"ICLR",2026,[208],{"name":209,"link":210},"Paper","https:\u002F\u002Fopenreview.net\u002Fforum?id=MMLAvR1juf&referrer=%5BAuthor+Console%5D%28%2Fgroup%3Fid%3DICLR.cc%2F2026%2FConference%2FAuthors%23your-submissions%29",{"title":212,"topic":213,"figure":214,"selected":195,"authors":215,"venue":236,"links":239,"highlights":253},"Deep contrastive learning enables genome-wide virtual screening",[193],"\u002Fimage\u002Fdrugclip_sci.png",[216,217,218,219,220,89,102,221,222,223,147,224,225,226,227,228,229,230,231,232,233,234,235],"Yinjun Jia†","Bowen Gao†","Jiaxin Tan†","Jiqing Zheng†","Xin Hong†","Yuan Xiao","Liping Tan","Hongyi Cai","Zhiheng Deng","Xiangwei Wu","Yue Jin","Yafei Yuan","Jiekang Tian","Wei He","Weiying Ma","Yaqin Zhang","Lei Liu*","Chuangye Yan*","Wei Zhang*","Yanyan Lan*",{"name":237,"year":206,"link":238},"Science","https:\u002F\u002Fwww.science.org\u002Fdoi\u002F10.1126\u002Fscience.ads9530",[240,241,244,247,250],{"name":209,"link":238},{"name":242,"link":243},"Preprint","https:\u002F\u002Fwww.biorxiv.org\u002Fcontent\u002F10.1101\u002F2024.09.02.610777",{"name":245,"link":246},"Project Page","https:\u002F\u002Fdrugclip.com",{"name":248,"link":249},"GenomeScreenDB","https:\u002F\u002Fdrug-the-whole-genome.yanyanlan.com\u002F",{"name":251,"link":252},"Code","https:\u002F\u002Fgithub.com\u002FTHU-ATOM\u002FDrug-The-Whole-Genome",[254],{"name":237,"link":7},{"title":256,"topic":257,"figure":258,"selected":195,"authors":259,"venue":262,"links":264,"highlights":269},"Learning Protein-Ligand Binding in Hyperbolic Space",[193],"\u002Fimage\u002Fhypseek_atom_lab.png",[260,261,198,71,202,203,64],"Jianhui Wang*","Wenyu Zhu*",{"name":263,"year":206,"link":80},"AAAI",[265,267,268],{"name":209,"link":266},"https:\u002F\u002Farxiv.org\u002Fpdf\u002F2508.15480",{"name":245,"link":7},{"name":251,"link":7},[270],{"name":7,"link":7},{"title":272,"topic":273,"figure":274,"selected":195,"authors":275,"venue":276,"links":280,"highlights":286},"AANet: Virtual Screening under Structural Uncertainty via Alignment and Aggregation",[193],"\u002Fimage\u002Faanet_atom_lab.png",[261,260,198,75,102,203,202,64],{"name":277,"year":278,"link":279},"Neurips",2025,"https:\u002F\u002Fneurips.cc\u002F",[281,283,284],{"name":209,"link":282},"https:\u002F\u002Farxiv.org\u002Fpdf\u002F2506.05768",{"name":245,"link":7},{"name":251,"link":285},"https:\u002F\u002Fgithub.com\u002FWiley-Z\u002FAANet",[287],{"name":7,"link":7},{"title":289,"topic":290,"figure":291,"authors":292,"venue":297,"links":300,"highlights":303},"Manipulating 3D Molecules in a Fixed-Dimensional SE(3)-Equivariant Latent Space",[193],"\u002Fimage\u002FMolFLAE.png",[293,294,295,296,64],"Zitao Chen*","Yinjun Jia*","Zitong Tian*","Wei-ying Ma",{"name":298,"year":278,"link":299},"NeruIPS","https:\u002F\u002Fopenreview.net\u002Fforum?id=6xL4MRFeJo",[301],{"name":209,"link":302},"https:\u002F\u002Farxiv.org\u002Fpdf\u002F2506.00771",[304],{"name":7,"link":7},{"title":306,"topic":307,"figure":308,"selected":195,"authors":309,"venue":313,"links":314,"highlights":319},"CIDD: Collaborative Intelligence for Structure-Based Drug Design Empowered by LLMs",[193],"\u002Fimage\u002Fcidd_atom_lab.png",[198,310,311,200,312,102,203,202,64],"Yanwen Huang*","Yiqiao Liu","Bowei He",{"name":277,"year":278,"link":279},[315,317,318],{"name":209,"link":316},"https:\u002F\u002Farxiv.org\u002Fpdf\u002F2503.01376",{"name":245,"link":7},{"name":251,"link":7},[320],{"name":7,"link":7},{"title":322,"topic":323,"figure":324,"selected":195,"authors":325,"venue":332,"links":334,"highlights":340},"Straight-Line Diffusion Model for Efficient 3D Molecular Generation",[193],"\u002Fimage\u002FSLDM.gif",[326,327,328,329,330,203,331,64],"Yuyan Ni*","Shikun Feng*","Haohan Chi","Bowen Zheng","Huan-ang Gao","Zhi-Ming Ma",{"name":277,"year":278,"link":333},"https:\u002F\u002Fopenreview.net\u002Fforum?id=waHF2ekuf2",[335,337,338],{"name":209,"link":336},"https:\u002F\u002Farxiv.org\u002Fabs\u002F2503.02918",{"name":245,"link":7},{"name":251,"link":339},"https:\u002F\u002Fgithub.com\u002Ffengshikun\u002FSLDM",[341],{"name":7,"link":7},{"title":343,"topic":344,"figure":345,"selected":195,"authors":346,"venue":350,"links":352,"highlights":356},"FIGRDock: Fast Interaction-Guided Regression for Flexible Docking",[193],"\u002Fimage\u002Ffigrdock_atom_lab.png",[327,347,348,98,89,106,203,349,64],"Bicheng Lin*","Yuanhuan Mo*","Haitao Li",{"name":277,"year":278,"link":351},"https:\u002F\u002Fopenreview.net\u002Fforum?id=HuMpsxL9C9",[353,354,355],{"name":209,"link":351},{"name":245,"link":7},{"name":251,"link":7},[357],{"name":7,"link":7},{"title":359,"topic":360,"figure":361,"selected":195,"authors":362,"venue":370,"links":372,"highlights":375},"CPSea: Large-scale cyclic peptide-protein complex dataset for machine learning in cyclic peptide design",[193],"\u002Fimage\u002Fcpsea.png",[363,364,75,365,366,367,368,369,64],"Ziyi Yang","Hanyuan Xie","Xiangzhe Kong","Jiqing Zheng","Ziting Zhang","Yang Liu","Lei Liu",{"name":277,"year":278,"link":371},"https:\u002F\u002Fneurips.cc\u002Fvirtual\u002F2025\u002Fposter\u002F121780",[373],{"name":209,"link":374},"https:\u002F\u002Fopenreview.net\u002Fforum?id=CfOsKx3jF8",[376],{"name":7,"link":7},{"title":378,"topic":379,"figure":380,"selected":195,"authors":381,"venue":382,"links":385,"highlights":387},"Revisiting Sampling Strategies for Molecular Generation",[193],"\u002Fimage\u002Fstomax5.PNG",[98,143,203,331,64],{"name":383,"year":278,"link":384},"ICML GenBio workshop","https:\u002F\u002Fopenreview.net\u002Fforum?id=ID6GjrJaJx",[386],{"name":209,"link":384},[388],{"name":7,"link":7},{"title":390,"topic":391,"figure":392,"selected":195,"authors":393,"venue":394,"links":396},"Multi-Granular Contrastive Alignment and Fusion for Fragment-Enhanced Virtual Screening",[193],"\u002Fimage\u002Ffragclip_atom_lab.png",[197,198,199,147,89,140,75,125,203,202,64],{"name":383,"year":278,"link":395},"https:\u002F\u002Fgenbio-workshop.github.io\u002F2025\u002F",[397],{"name":209,"link":398},"https:\u002F\u002Fopenreview.net\u002Fforum?id=Pt18WpGHHn",{"title":400,"topic":401,"figure":402,"selected":195,"authors":403,"venue":408,"links":409,"highlights":414},"How Good is AlphaFold3 at Ranking Drug Binding Affinities?",[193],"\u002Fimage\u002Falpharank.png",[404,198,294,89,405,406,407,140,64],"Xin Hong*","Qixuan Chen","Xiaohe Tian","Zhengyi Zhong",{"name":383,"year":278,"link":395},[410,412,413],{"name":209,"link":411},"https:\u002F\u002Fwww.biorxiv.org\u002Fcontent\u002F10.1101\u002F2025.05.27.656341v1.full.pdf",{"name":245,"link":7},{"name":251,"link":7},[415],{"name":7,"link":7},{"title":417,"topic":418,"figure":419,"selected":195,"authors":420,"venue":422,"links":424,"highlights":429},"UniGEM: A Unified Approach to Generation and Property Prediction for Molecules",[193],"\u002Fimage\u002FUNIGEM.jpg",[143,98,421,331,203,64],"Yan Lu",{"name":205,"year":278,"link":423},"https:\u002F\u002Fopenreview.net\u002Fforum?id=Lb91pXwZMR",[425,427,428],{"name":209,"link":426},"https:\u002F\u002Farxiv.org\u002Fabs\u002F2410.10516",{"name":245,"link":7},{"name":251,"link":7},[430],{"name":7,"link":7},{"title":432,"topic":433,"figure":434,"selected":195,"authors":435,"venue":437,"links":439,"highlights":443},"Reframing Structure-Based Drug Design Model Evaluation via Metrics Correlated to Practical Needs",[193],"\u002Fimage\u002Fsbdd_bench.jpg",[198,197,147,163,436,203,202,64],"Xiao Huang",{"name":205,"year":278,"link":438},"https:\u002F\u002Fopenreview.net\u002Fforum?id=RyWypcIMiE",[440,441,442],{"name":209,"link":438},{"name":245,"link":7},{"name":251,"link":7},[444],{"name":7,"link":7},{"title":446,"topic":447,"figure":448,"selected":195,"authors":449,"venue":451,"links":453,"highlights":457},"Redefining the task of Bioactivity Prediction",[193],"\u002Fimage\u002Fsiu.png",[310,198,75,450,203,202,64],"Hongbo Ma",{"name":205,"year":278,"link":452},"https:\u002F\u002Fopenreview.net\u002Fpdf?id=S8gbnkCgxZ",[454,455,456],{"name":209,"link":452},{"name":245,"link":7},{"name":251,"link":7},[458],{"name":7,"link":7},{"title":460,"topic":461,"figure":462,"selected":195,"authors":463,"venue":480,"links":483,"highlights":488},"A foundation model of transcription across human cell types",[193],"\u002Fimage\u002FGET.jpg",[464,465,466,467,468,469,470,471,472,473,474,475,64,476,477,478,479],"Xi Fu","Shentong Mo","Alejandro Buendia","Anouchka P. Laurent","Anqi Shao","Maria del Mar Alvarez-Torres","Tianji Yu","Jimin Tan","Jiayu Su","Romella Sagatelian","Adolfo A. Ferrando","Alberto Ciccia","David M. Owens","Teresa Palomero","Eric P. Xing","Raul Rabadan",{"name":481,"year":278,"link":482},"Nature","https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41586-024-08391-z",[484,485,487],{"name":209,"link":482},{"name":245,"link":486},"https:\u002F\u002Fgithub.com\u002FGET-Foundation\u002Fget_model",{"name":251,"link":486},[489],{"name":7,"link":7},{"title":491,"topic":492,"figure":493,"selected":195,"authors":494,"venue":497,"links":501},"Pre-training with Fractional Denoising to Enhance Molecular Property Prediction",[193],"\u002Fimage\u002Ffrad.png",[326,327,71,495,203,331,496,64],"Yuancheng Sun","Qiwei Ye",{"name":498,"year":499,"link":500},"Nature Machine Intelligence",2024,"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs42256-024-00900-z",[502,504,506],{"name":209,"link":503},"https:\u002F\u002Farxiv.org\u002Fabs\u002F2407.11086",{"name":245,"link":505},"\u002Fproject\u002Ffrad\u002F",{"name":251,"link":507},"https:\u002F\u002Fgithub.com\u002Ffengshikun\u002FFradNMI",{"title":509,"topic":510,"figure":511,"selected":195,"authors":512,"venue":513,"links":516,"highlights":518},"UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning",[193],"\u002Fimage\u002Funicorn.jpeg",[143,98,161,147,203,64],{"name":514,"year":499,"link":515},"ICML","https:\u002F\u002Fopenreview.net\u002Fforum?id=2NfpFwJfKu",[517],{"name":209,"link":515},[519],{"name":7,"link":7},{"title":521,"topic":522,"figure":523,"selected":195,"authors":524,"venue":526,"links":527},"Rethinking Specificity in SBDD: Leveraging Delta Score and Energy-Guided Diffusion",[193],"\u002Fimage\u002Fsbe-diff.png",[198,525,98,147,166,331,203,64],"Minsi Ren*",{"name":514,"year":499,"link":80},[528],{"name":209,"link":529},"https:\u002F\u002Farxiv.org\u002Fabs\u002F2403.12987",{"title":531,"topic":532,"figure":533,"selected":195,"authors":534,"venue":535,"links":536},"Protein-ligand binding representation learning from fine-grained interactions",[193],"\u002Fimage\u002Fbindnet.jpeg",[143,161,75,203,64],{"name":205,"year":499,"link":80},[537,539,541],{"name":209,"link":538},"https:\u002F\u002Fopenreview.net\u002Fpdf?id=AXbN2qMNiW",{"name":245,"link":540},"\u002Fproject\u002Fbindnet",{"name":251,"link":542},"https:\u002F\u002Fgithub.com\u002Ffengshikun\u002FBindNet",{"title":544,"topic":545,"figure":546,"selected":195,"authors":547,"venue":548,"links":549},"Sliced Denoising: A Physics-Informed Molecular Pre-Training Method",[193],"\u002Fimage\u002Fslide_method.jpg",[98,143,203,331,64],{"name":205,"year":499,"link":80},[550,552,554],{"name":209,"link":551},"https:\u002F\u002Farxiv.org\u002Fabs\u002F2311.02124",{"name":245,"link":553},"\u002Fproject\u002Fslide",{"name":251,"link":555},"https:\u002F\u002Fgithub.com\u002Ffengshikun\u002FSliDe",{"title":557,"topic":558,"figure":559,"selected":195,"authors":560,"venue":561,"links":563,"highlights":568},"Self-supervised Pocket Pretraining via Protein Fragment-Surroundings Alignment",[193],"\u002Fimage\u002Fprofsa_data.png",[106,75,156,98,203,331,64],{"name":205,"year":499,"link":562},"https:\u002F\u002Farxiv.org\u002Fabs\u002F2310.07229",[564,566],{"name":209,"link":565},"https:\u002F\u002Farxiv.org\u002Fpdf\u002F2310.07229.pdf",{"name":245,"link":567},"\u002Fproject\u002Fprofsa",[569],{"name":7,"link":7},{"title":571,"topic":572,"figure":573,"selected":6,"authors":574,"venue":579,"links":580},"Multimodal Molecular Pretraining via Modality Blending",[193],"\u002Fimage\u002Fmoleblend.png",[575,576,98,143,64,577,578],"Qiying Yu","Yudi Zhang","Hao Zhou","Jingjing Liu",{"name":205,"year":499,"link":7},[581],{"name":209,"link":582},"https:\u002F\u002Farxiv.org\u002Fabs\u002F2307.06235",{"title":584,"topic":585,"figure":586,"selected":6,"authors":587,"venue":593,"links":596,"highlights":599},"Equivariant Flow Matching with Hybrid Probability Transport for 3D Molecule Generation",[193],"\u002Fimage\u002Fequifm.png",[588,589,590,591,64,592,577,203],"Yuxuan Song","Jingjing Gong","Minkai Xu","Ziyao Cao","Stefano Ermon",{"name":594,"year":595,"link":7},"NeurIPS",2023,[597],{"name":209,"link":598},"https:\u002F\u002Farxiv.org\u002Fabs\u002F2312.07168",[600],{"name":7,"link":7},{"title":602,"topic":603,"figure":604,"selected":195,"authors":605,"venue":607,"links":608,"highlights":615},"DrugCLIP: Contrastive Protein-Molecule Representation Learning for Virtual Screening",[193],"\u002Fimage\u002Fdrugclip.png",[106,166,102,163,75,606,578,296,64],"Minsi Lu",{"name":594,"year":595,"link":7},[609,611,613],{"name":209,"link":610},"https:\u002F\u002Farxiv.org\u002Fpdf\u002F2310.06367.pdf",{"name":245,"link":612},"\u002Fproject\u002Fdrugclip",{"name":251,"link":614},"https:\u002F\u002Fgithub.com\u002Fbowen-gao\u002FDrugCLIP",[616],{"name":7,"link":7},{"title":618,"topic":619,"figure":620,"selected":195,"authors":621,"venue":622,"links":623,"highlights":630},"Fractional Denoising for 3D Molecular Pre-training",[193],"\u002Fimage\u002FFrad_frame.jpeg",[143,98,331,203,64],{"name":514,"year":595,"link":7},[624,626,628],{"name":209,"link":625},"https:\u002F\u002Farxiv.org\u002Fpdf\u002F2307.10683.pdf",{"name":245,"link":627},"\u002Fproject\u002Ffrad",{"name":251,"link":629},"https:\u002F\u002Fgithub.com\u002Ffengshikun\u002Ffrad",[631],{"name":7,"link":7},{"title":633,"topic":634,"figure":635,"selected":195,"authors":636,"venue":637,"links":638,"highlights":645},"Coarse-to-Fine: a Hierarchical Diffusion Model for Molecule Generation in 3D",[193],"\u002Fimage\u002Fhierdiff_framework.png",[166,588,590,589,106,577,230,64],{"name":514,"year":595,"link":7},[639,641,643],{"name":209,"link":640},"https:\u002F\u002Fbrowse.arxiv.org\u002Fpdf\u002F2305.13266.pdf",{"name":245,"link":642},"\u002Fproject\u002Fhierdiff",{"name":251,"link":644},"https:\u002F\u002Fgithub.com\u002Fqiangbo1222\u002FHierDiff",[646],{"name":7,"link":7},{"title":648,"topic":649,"figure":651,"authors":652,"venue":655,"links":657,"highlights":662},"Visual Reasoning: from State to Transformation",[650],"Multi-modal Learning","\u002Fimage\u002Fvisual_reasoning.jpg",[71,64,175,653,654],"Jiafeng Guo","Xueqi Cheng",{"name":656,"year":595,"link":7},"TPAMI",[658,660],{"name":209,"link":659},"https:\u002F\u002Farxiv.org\u002Fabs\u002F2305.01668",{"name":251,"link":661},"https:\u002F\u002Fgithub.com\u002Fhughplay\u002FTVR",[663],{"name":7,"link":7},{"title":665,"topic":666,"figure":668,"authors":669,"venue":677,"links":679,"highlights":682},"HiBERT: Detecting the Illogical Patterns with Hierarchical BERT for Multi-turn Dialogue Reasoning",[667],"Natural Language Processing","\u002Fimage\u002Fhibert.jpg",[670,178,671,672,673,674,675,676,64],"Xu Wang","Shuai Zhao","Hongshen Chen","Bo Cheng","Zhuoye Ding","Sulong Xu","Weipeng Yan",{"name":678,"year":595,"link":7},"Neurocomputing",[680],{"name":209,"link":681},"https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0925231222015430",[683],{"name":7,"link":7},{"title":685,"topic":686,"figure":687,"authors":688,"venue":691,"links":693,"highlights":696},"Multi-video Moment Ranking with Multimodal Clue",[650],"\u002Fimage\u002Fmvm.jpg",[689,175,64,690,654],"Danyang Hou","Huawei Shen",{"name":692,"year":595,"link":7},"arXiv",[694],{"name":209,"link":695},"https:\u002F\u002Farxiv.org\u002Fabs\u002F2301.13606",[697],{"name":7,"link":7},{"title":699,"topic":700,"figure":701,"authors":702,"venue":705,"links":706,"highlights":711},"Cross-Model Comparative Loss for Enhancing Neuronal Utility in Language Understanding",[667],"\u002Fimage\u002Fcmc.jpg",[703,175,704,64,690,654],"Yunchang Zhu","Kangxi Wu",{"name":692,"year":595,"link":7},[707,709],{"name":209,"link":708},"https:\u002F\u002Farxiv.org\u002Fabs\u002F2301.03765",{"name":251,"link":710},"https:\u002F\u002Fgithub.com\u002Fzycdev\u002FCmpLoss",[712],{"name":7,"link":7},{"title":714,"topic":715,"figure":716,"authors":717,"venue":719,"links":721,"highlights":724},"GET: A Foundation Model of Transcription Across Human Cell Types",[193],"\u002Fimage\u002Fget.jpg",[464,465,468,718,466,474,475,64,477,476,478],"Anouchka Laurent",{"name":720,"year":595,"link":7},"biorxiv",[722],{"name":209,"link":723},"https:\u002F\u002Fwww.biorxiv.org\u002Fcontent\u002F10.1101\u002F2023.09.24.559168v1.abstract",[725],{"name":7,"link":7},{"title":727,"topic":728,"figure":730,"authors":731,"venue":763,"links":765,"highlights":768},"Information Retrieval Meets Large Language Models: A Strategic Report from Chinese IR Community",[729],"Information Retrieval","\u002Fimage\u002Fir.jpg",[732,733,734,735,736,737,738,739,740,741,742,653,743,64,744,745,746,747,748,749,750,751,752,753,754,755,756,757,758,759,760,761,762],"Qingyao Ai","Ting Bai","Zhao Cao","Yi Chang","Jiawei Chen","Zhumin Chen","Zhiyong Cheng","Shoubin Dong","Zhicheng Dou","Fuli Feng","Shen Gao","Xiangnan He","Chenliang Li","Yiqun Liu","Ziyu Lyu","Weizhi Ma","Jun Ma","Zhaochun Ren","Pengjie Ren","Zhiqiang Wang","Mingwen Wang","Ji-Rong Wen","Le Wu","Xin Xin","Jun Xu","Dawei Yin","Peng Zhang","Fan Zhang","Weinan Zhang","Min Zhang","Xiaofei Zhu",{"name":764,"year":595,"link":7},"AI Open",[766],{"name":209,"link":767},"https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS2666651023000049",[769],{"name":7,"link":7},{"title":771,"selected":195,"topic":772,"figure":774,"authors":775,"venue":779,"links":781,"highlights":786},"When Does Group Invariant Learning Survive Spurious Correlations?",[773],"Machine Learning","\u002Fimage\u002Fdgi.jpg",[776,777,778,64],"Yimeng Chen","Ruibin Xiong","Zhiming Ma",{"name":594,"year":780,"link":7},2022,[782,784],{"name":209,"link":783},"https:\u002F\u002Fproceedings.neurips.cc\u002Fpaper_files\u002Fpaper\u002F2022\u002Fhash\u002F2e351740d4ec4200df6160f34cd181c3-Abstract-Conference.html",{"name":251,"link":785},"https:\u002F\u002Fgithub.com\u002FBeastlyprime\u002Fgroup-invariant-learning",[787],{"name":7,"link":7},{"title":789,"selected":195,"topic":790,"figure":791,"authors":792,"venue":795,"links":797,"highlights":800},"PEMP: Leveraging Physics Properties to Enhance Molecular Property Prediction",[193],"\u002Fimage\u002Fpemp.jpg",[495,776,747,793,794,778,203,64],"Wenhao Huang","Kang Liu",{"name":796,"year":780,"link":7},"CIKM",[798],{"name":209,"link":799},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fabs\u002F10.1145\u002F3511808.3557142",[801],{"name":7,"link":7},{"title":803,"topic":804,"figure":805,"authors":806,"venue":809,"links":811,"highlights":814},"Beyond Precision: A Study on Recall of Initial Retrieval with Neural Representations",[729],"\u002Fimage\u002Fbp.jpg",[807,653,808,64],"Yan Xiao","Yixing Fan",{"name":810,"year":780,"link":7},"CCIR",[812],{"name":209,"link":813},"https:\u002F\u002Flink.springer.com\u002Fchapter\u002F10.1007\u002F978-3-031-24755-2_7",[815],{"name":7,"link":7},{"title":817,"topic":818,"figure":819,"authors":820,"venue":822,"links":824,"highlights":829},"Elastic Information Bottleneck",[773],"\u002Fimage\u002Feib.jpg",[98,64,821,778],"Ao Liu",{"name":823,"year":780,"link":7},"Mathematics",[825,827],{"name":209,"link":826},"https:\u002F\u002Fwww.mdpi.com\u002F2227-7390\u002F10\u002F18\u002F3352",{"name":251,"link":828},"https:\u002F\u002Fgithub.com\u002Fnyyxxx\u002Felastic-information-bottleneck",[830],{"name":7,"link":7},{"title":832,"topic":833,"figure":834,"authors":835,"venue":836,"links":838,"highlights":841},"Region-based Cross-modal Retrieval",[650],"\u002Fimage\u002Frcr.jpg",[689,175,64,690,654],{"name":837,"year":780,"link":7},"IJCNN",[839],{"name":209,"link":840},"https:\u002F\u002Fieeexplore.ieee.org\u002Fabstract\u002Fdocument\u002F9892139",[842],{"name":7,"link":7},{"title":844,"topic":845,"figure":846,"authors":847,"venue":849,"links":850,"highlights":855},"UniMAP: Universal SMILES-Graph Representation Learning",[193],"\u002Fimage\u002Funimap.jpg",[143,848,230,64],"Lixin Yang",{"name":692,"year":595,"link":7},[851,853],{"name":209,"link":852},"https:\u002F\u002Farxiv.org\u002Fabs\u002F2310.14216",{"name":251,"link":854},"https:\u002F\u002Fgithub.com\u002Ffengshikun\u002FUniMAP",[856],{"name":7,"link":7},{"title":858,"selected":195,"topic":859,"figure":860,"authors":861,"venue":862,"links":864,"highlights":869},"LoL: A Comparative Regularization Loss Over Query Reformulation Losses for Pseudo-Relevance Feedback",[729],"\u002Fimage\u002Flol.png",[703,175,64,690,654],{"name":863,"year":780,"link":7},"SIGIR",[865,867],{"name":209,"link":866},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fabs\u002F10.1145\u002F3477495.3532017",{"name":251,"link":868},"https:\u002F\u002Fgithub.com\u002Fzycdev\u002FLoL",[870],{"name":7,"link":7},{"title":872,"topic":873,"figure":874,"authors":875,"venue":879,"links":881,"highlights":884},"From Spoken Dialogue to Formal Summary: An Utterance Rewriting for Dialogue Summarization",[667],"\u002Fimage\u002FReWriteSum.png",[876,178,672,674,877,64,878],"Yue Fang","Ba Long","Yanquan Zhou",{"name":880,"year":780,"link":7},"NAACL 2022",[882],{"name":209,"link":883},"https:\u002F\u002Faclanthology.org\u002F2022.naacl-main.283\u002F",[885],{"name":7,"link":7},{"title":887,"selected":195,"topic":888,"figure":889,"authors":890,"venue":891,"links":893,"highlights":897},"Uncertainty Calibration for Ensemble-Based Debiasing Methods",[773],"\u002Fimage\u002Fdebias1.png",[777,776,175,654,331,64],{"name":594,"year":892,"link":7},2021,[894,896],{"name":209,"link":895},"https:\u002F\u002Fproceedings.neurips.cc\u002Fpaper\u002F2021\u002Fhash\u002F71a8b2ffe0b594a5c1b3c28090384fd7-Abstract.html",{"name":251,"link":80},[898],{"name":7,"link":7},{"title":900,"selected":195,"topic":901,"figure":902,"authors":903,"venue":906,"links":909,"highlights":912},"Adaptive Bridge between Training and Inference for Dialogue Generation",[667],"\u002Fimage\u002Fadaptbridge.png",[904,178,905,672,674,64],"Haoran Xu","Yanyan Zou",{"name":907,"year":892,"link":908},"EMNLP","https:\u002F\u002Fwww.emnlp-ijcai.org\u002Fproceedings\u002F2021\u002Fpapers\u002F2021_papers\u002F7365\u002Findex.html",[910,911],{"name":209,"link":908},{"name":251,"link":7},[913],{"name":7,"link":7},{"title":915,"topic":916,"figure":917,"authors":918,"venue":919,"links":921,"highlights":925},"Match-ignition: Plugging PageRank Into Transformer for Long-form Text Matching",[729],"\u002Fimage\u002Fmatchign.png",[175,64,654],{"name":796,"year":892,"link":920},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002F10.1145\u002F3459645.3482233",[922,924],{"name":209,"link":923},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fabs\u002F10.1145\u002F3459637.3482450",{"name":251,"link":7},[926],{"name":7,"link":7},{"title":928,"topic":929,"figure":930,"authors":931,"venue":938,"links":940,"highlights":944},"Multi-modal Self-supervised Pre-training for Large-scale Genome Data",[193],"\u002Fimage\u002Fgenebert.png",[465,464,932,933,934,935,64,936,937],"Chenyang Hong","Yizhen Chen","Yuxuan Zheng","Xiangru Tang","Zhiqiang Shen","Eric Xing",{"name":939,"year":892},"NeurIPS Workshop",[941,943],{"name":209,"link":942},"https:\u002F\u002Fopenreview.net\u002Fforum?id=fdV-GZ4LPfn",{"name":251,"link":80},[945],{"name":7,"link":7},{"title":947,"topic":948,"figure":949,"authors":950,"venue":951,"links":953,"highlights":957},"FCM: A Fine-grained Comparison Model for Multi-turn Dialogue Reasoning",[667],"\u002Fimage\u002Ffcm.png",[670,178,671,905,672,674,673,64],{"name":952,"year":892},"EMNLP Findings",[954,956],{"name":209,"link":955},"https:\u002F\u002Faclanthology.org\u002F2021.findings-emnlp.362\u002F",{"name":251,"link":80},[958],{"name":7,"link":7},{"title":960,"topic":961,"figure":962,"authors":963,"venue":966,"links":967,"highlights":971},"Transductive Learning for Unsupervised Text Style Transfer",[667],"\u002Fimage\u002Ftransfer.png",[964,175,64,965,690,654],"Fei Xiao","Yan Wang",{"name":907,"year":892},[968,970],{"name":209,"link":969},"https:\u002F\u002Faclanthology.org\u002F2021.emnlp-main.195\u002F",{"name":251,"link":80},[972],{"name":7,"link":7},{"title":974,"topic":975,"figure":976,"authors":977,"venue":978,"links":979,"highlights":984},"Adaptive Information Seeking for Open-domain Question Answering",[667,729],"\u002Fimage\u002FAISO.png",[703,175,64,690,654],{"name":907,"year":892},[980,982],{"name":209,"link":981},"https:\u002F\u002Faclanthology.org\u002F2021.emnlp-main.293\u002F#:~:text=Information%20seeking%20is%20an%20essential%20step%20for%20open-domain,by%20recursively%20retrieving%20new%20evidence%20at%20each%20step.",{"name":251,"link":983},"https:\u002F\u002Fgithub.com\u002Fzycdev\u002FAISO",[985],{"name":7,"link":7},{"title":987,"topic":988,"figure":989,"authors":990,"venue":992,"links":993,"highlights":997},"Toward the Understanding of Deep Text Matching Models for Information Retrieval",[667,729],"\u002Fimage\u002Farc1.png",[991,64,175,653,654],"Lijuan Chen",{"name":692,"year":892},[994,996],{"name":209,"link":995},"https:\u002F\u002Farxiv.org\u002Fabs\u002F2108.07081",{"name":251,"link":80},[998],{"name":7,"link":7},{"title":1000,"topic":1001,"figure":1002,"authors":1003,"venue":1006,"links":1007,"highlights":1011},"A Discriminative Semantic Ranker for Question Retrieval",[667,729],"\u002Fimage\u002Fdensetrans.png",[1004,808,653,1005,64,654],"Yinqiong Cai","Ruqing Zhang",{"name":863,"year":892},[1008,1010],{"name":209,"link":1009},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fabs\u002F10.1145\u002F3471158.3472227",{"name":251,"link":80},[1012],{"name":7,"link":7},{"title":1014,"topic":1015,"figure":1016,"authors":1017,"venue":1020,"links":1022,"highlights":1026},"Augmenting Knowledge-Grounded Conversations with Sequential Knowledge Transition",[667],"\u002Fimage\u002F31_DuConv.png",[1018,178,672,674,1019,64],"Haolan Zhan","Yongjun Bao",{"name":1021,"year":892,"link":7},"NAACL",[1023,1025],{"name":209,"link":1024},"https:\u002F\u002Faclanthology.org\u002F2021.naacl-main.446.pdf",{"name":251,"link":80},[1027],{"name":7,"link":7},{"title":1029,"topic":1030,"figure":1031,"authors":1032,"venue":1034,"links":1036,"highlights":1040},"Sketch and Customize: A Counterfactual Story Generator",[667],"\u002Fimage\u002F32_story.png",[1033,175,64,965,653,654],"Changying Hao",{"name":263,"year":892,"link":1035},"https:\u002F\u002Fojs.aaai.org\u002Findex.php\u002FAAAI\u002Farticle\u002Fview\u002F17532\u002F17339",[1037,1038],{"name":209,"link":1035},{"name":251,"link":1039},"https:\u002F\u002Fgithub.com\u002Fying-A\u002FSandC",[1041],{"name":7,"link":7},{"title":1043,"topic":1044,"figure":1045,"authors":1046,"venue":1048,"links":1050,"highlights":1053},"Probing Product Description Generation via Posterior Distillation",[667],"\u002Fimage\u002F33_dataset.png",[1018,178,672,1047,674,1019,676,64],"Lei Shen",{"name":263,"year":892,"link":1049},"https:\u002F\u002Fojs.aaai.org\u002Findex.php\u002FAAAI\u002Farticle\u002Fview\u002F17682\u002F17489",[1051,1052],{"name":209,"link":1049},{"name":251,"link":7},[1054],{"name":7,"link":7},{"title":1056,"topic":1057,"figure":1058,"authors":1059,"venue":1062,"links":1064,"highlights":1066},"Learning to Truncate Ranked Lists for Information Retrieval",[729],"\u002Fimage\u002F34_attncut.png",[1060,1005,653,1061,64,654],"Chen Wu","Yixin Fan",{"name":263,"year":892,"link":1063},"https:\u002F\u002Fojs.aaai.org\u002Findex.php\u002FAAAI\u002Farticle\u002Fdownload\u002F16572\u002F16379",[1065],{"name":209,"link":1063},[1067],{"name":7,"link":80},{"title":1069,"topic":1070,"figure":1071,"authors":1072,"venue":1074,"links":1076,"highlights":1080},"A Linguistic Study on Relevance Modeling in Information Retrieval",[729],"\u002Fimage\u002F35.png",[808,653,1073,1005,64,654],"Xinyu Ma",{"name":1075,"year":892,"link":7},"WWW",[1077,1079],{"name":209,"link":1078},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fpdf\u002F10.1145\u002F3442381.3450009",{"name":251,"link":80},[1081],{"name":7,"link":7},{"title":1083,"selected":195,"topic":1084,"figure":1085,"authors":1086,"venue":1117,"links":1119,"highlights":1123},"WenLan: Bridging Vision and Language by Large-Scale Multi-Modal Pre-training",[650],"\u002Fimage\u002F36_wenlan.png",[1087,1088,1089,1090,1091,1092,1093,1094,1095,1096,1097,1098,1099,1100,1101,1102,1103,1104,71,1105,689,1106,1107,1108,1109,1110,1111,1112,1113,740,1114,64,1115,1116,753],"Yuqi Huo","Manli Zhang","Guangzhen Liu","Haoyu Lu","Yizhao Gao","Guoxing Yang","Jingyuan Wen","Heng Zhang","Baogui Xu","Weihao Zheng","Zongzheng Xi","Yueqian Yang","Anwen Hu","Jinming Zhao","Ruichen Li","Yida Zhao","Liang Zhang","Yuqing Song","Wanqing Cui","Yingyan Li","Junyi Li","Peiyu Liu","Zheng Gong","Chuhao Jin","Yuchong Sun","Shizhe Chen","Zhiwu Lu","Qin Jin","Wayne Xin Zhao","Ruihua Song",{"name":692,"year":892,"link":1118},"https:\u002F\u002Farxiv.org\u002Fabs\u002F2103.06561",[1120,1122],{"name":209,"link":1121},"https:\u002F\u002Farxiv.org\u002Fpdf\u002F2103.06561.pdf",{"name":251,"link":80},[1124],{"name":7,"link":80},{"title":1126,"topic":1127,"figure":1128,"authors":1129,"venue":1132,"links":1134,"highlights":1137},"Beyond Relevance: Trustworthy Answer Selection via Consensus Verification",[729],"\u002Fimage\u002F37_answer_selection.png",[1130,1005,653,808,1131,64,654],"Lixin Su","Jiangui Chen",{"name":1133,"year":892,"link":7},"WSDM",[1135],{"name":209,"link":1136},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fpdf\u002F10.1145\u002F3437963.3441781",[1138],{"name":7,"link":7},{"title":1140,"topic":1141,"figure":1142,"authors":1143,"venue":1145,"links":1148,"highlights":1150},"Information Retrieval: A View from the Chinese IR Community",[729],"\u002Fimage\u002F38_review.png",[737,654,739,740,653,1144,64],"Xuanjing Huang",{"name":1146,"year":892,"link":1147},"Frontiers of Computer Science","https:\u002F\u002Fjournal.hep.com.cn\u002Ffcs\u002FEN\u002Farticle\u002FdownloadArticleFile.do?attachType=PDF&id=26436",[1149],{"name":209,"link":1147},[1151],{"name":7,"link":80},{"title":1153,"topic":1154,"figure":1155,"authors":1156,"venue":1157,"links":1159,"highlights":1163},"Evaluating Natural Language Generation via Unbalanced Optimal Transport",[667],"\u002Fimage\u002F39.png",[776,64,777,175,778,654],{"name":1158,"year":892,"link":80},"IJCAI",[1160,1162],{"name":209,"link":1161},"https:\u002F\u002Fwww.researchgate.net\u002Fprofile\u002FYimeng-Chen-6\u002Fpublication\u002F342793325_Evaluating_Natural-Language-Generation-via-Unbalanced-Optimal-Transport\u002Flinks\u002F62b998d993242c74cad1a03f\u002FEvaluating-Natural-Language-Generation-via-Unbalanced-Optimal-Transport.pdf",{"name":251,"link":80},[1164],{"name":7,"link":80},{"title":1166,"topic":1167,"figure":1168,"authors":1169,"venue":1176,"links":1178,"highlights":1181},"Pre-trained Models: Past, Present and Future",[773],"\u002Fimage\u002F40_review.png",[1170,1171,1172,1173,1174,1087,1175],"Xu Han","Zhengyan Zhang","Ning Ding","Yuxian Gu","Xiao Liu","Jiezhong Qiu",{"name":764,"year":892,"link":1177},"https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS2666651021000231",[1179,1180],{"name":209,"link":1177},{"name":251,"link":7},[1182],{"name":7,"link":7},{"title":1184,"topic":1185,"figure":1186,"selected":195,"authors":1187,"venue":1188,"links":1191,"highlights":1197},"Transformation Driven Visual Reasoning",[650],"\u002Fimage\u002Ftvr.png",[71,64,175,653,654],{"name":1189,"year":892,"link":1190},"CVPR","https:\u002F\u002Fopenaccess.thecvf.com\u002Fcontent\u002FCVPR2021\u002Fpapers\u002FHong_Transformation_Driven_Visual_Reasoning_CVPR_2021_paper.pdf",[1192,1194,1196],{"name":209,"link":1193},"https:\u002F\u002Farxiv.org\u002Fpdf\u002F2011.13160.pdf",{"name":245,"link":1195},"https:\u002F\u002Fhongxin2019.github.io\u002FTVR",{"name":251,"link":661},[1198],{"name":7,"link":7},{"title":1200,"topic":1201,"figure":1202,"authors":1203,"venue":1212,"links":1215,"highlights":1218},"On Layer Normalization in the Transformer Architecture",[773],"\u002Fimage\u002F42_OLN.png",[777,1204,1205,1206,1207,1208,1209,64,1210,1211],"Yunchang Yang","Di He","Kai Zheng","Shuxin Zheng","Chen Xing","Huishuai Zhang","Liwei Wang","Tieyan Liu",{"name":514,"year":1213,"link":1214},2020,"https:\u002F\u002Fproceedings.mlr.press\u002Fv119\u002Fxiong20b\u002Fxiong20b.pdf",[1216,1217],{"name":209,"link":1214},{"name":251,"link":80},[1219],{"name":7,"link":7},{"title":1221,"topic":1222,"figure":1223,"authors":1224,"venue":1225,"links":1227,"highlights":1230},"On the Relation Between Quality-Diversity Evaluation and Distribution-Fitting Goal in Text Generation",[667],"\u002Fimage\u002F43.png",[181,64,653,654],{"name":514,"year":1213,"link":1226},"https:\u002F\u002Fproceedings.mlr.press\u002Fv119\u002Fli20h\u002Fli20h.pdf",[1228,1229],{"name":209,"link":1226},{"name":251,"link":80},[1231],{"name":7,"link":80},{"title":1233,"topic":1234,"figure":1235,"authors":1236,"venue":1237,"links":1239,"highlights":1243},"Continual Domain Adaptation for Machine Reading Comprehension",[667,729],"\u002Fimage\u002F44.png",[1130,653,1005,808,64,654],{"name":796,"year":1213,"link":1238},"https:\u002F\u002Fwww.cikm2020.org\u002F",[1240,1242],{"name":209,"link":1241},"https:\u002F\u002Farxiv.org\u002Fpdf\u002F2008.10874.pdf",{"name":251,"link":80},[1244],{"name":7,"link":7},{"title":1246,"topic":1247,"figure":1248,"authors":1249,"venue":1250,"links":1251,"highlights":1255},"Query Understanding via Intent Description Generation",[729],"\u002Fimage\u002F45.png",[1005,653,808,64,654],{"name":796,"year":1213,"link":7},[1252,1254],{"name":209,"link":1253},"https:\u002F\u002Farxiv.org\u002Fpdf\u002F2008.10889.pdf",{"name":251,"link":80},[1256],{"name":7,"link":7},{"title":1258,"topic":1259,"figure":1260,"authors":1261,"venue":1263,"links":1264,"highlights":1268},"Ranking Enhanced Dialogue Generation",[667],"\u002Fimage\u002F46.png",[1033,175,64,1262,653,654],"Fei Sun",{"name":796,"year":1213,"link":7},[1265,1267],{"name":209,"link":1266},"https:\u002F\u002Farxiv.org\u002Fpdf\u002F2008.05640.pdf",{"name":251,"link":80},[1269],{"name":7,"link":7},{"title":1271,"selected":195,"topic":1272,"figure":1273,"authors":1274,"venue":1275,"links":1276,"highlights":1280},"Beyond Language: Learning Commonsense from Images for Reasoning",[650],"\u002Fimage\u002F47.png",[1105,64,175,653,654],{"name":907,"year":1213,"link":7},[1277,1279],{"name":209,"link":1278},"https:\u002F\u002Farxiv.org\u002Fabs\u002F2010.05001",{"name":251,"link":80},[1281],{"name":7,"link":7},{"title":1283,"selected":195,"topic":1284,"figure":1285,"authors":1286,"venue":1287,"links":1288,"highlights":1292},"Modeling Topical Relevance for Multi-Turn Dialogue Generation",[667],"\u002Fimage\u002F48.png",[178,64,175,672,674,757],{"name":1158,"year":1213,"link":7},[1289,1291],{"name":209,"link":1290},"https:\u002F\u002Fwww.ijcai.org\u002Fproceedings\u002F2020\u002F0517.pdf",{"name":251,"link":80},[1293],{"name":7,"link":7},{"title":1295,"selected":195,"topic":1296,"figure":1297,"authors":1298,"venue":1301,"links":1302,"highlights":1306},"Reinforcement Learning to Rank with Pairwise Policy Gradient",[729],"\u002Fimage\u002F49.png",[756,1299,1300,64,757,654,753],"Zeng Wei","Long Xia",{"name":863,"year":1213,"link":7},[1303,1305],{"name":209,"link":1304},"https:\u002F\u002Fdrive.google.com\u002Ffile\u002Fd\u002F14MoG-C56urc0Hg7yu_r_y8fYEObPjL_m\u002Fview",{"name":251,"link":80},[1307],{"name":7,"link":7},{"title":1309,"topic":1310,"figure":1311,"authors":1312,"venue":1313,"links":1314,"highlights":1318},"User-Inspired Posterior Network for Recommendation Reason Generation",[729],"\u002Fimage\u002F50.png",[1018,178,672,1047,64,674,757],{"name":863,"year":1213,"link":7},[1315,1317],{"name":209,"link":1316},"https:\u002F\u002Farxiv.org\u002Fpdf\u002F2102.07919.pdf",{"name":251,"link":80},[1319],{"name":7,"link":7},{"title":1321,"topic":1322,"figure":1323,"authors":1324,"venue":1329,"links":1330,"highlights":1334},"Match²: A Matching Over Matching Model for Similar Question Identification",[729],"\u002Fimage\u002F51.png",[1325,808,653,1326,1005,64,654,1327,1328],"Zizhen Wang","Liu Yang","Hui Jiang","Xiaozhao Wang",{"name":863,"year":1213,"link":7},[1331,1333],{"name":209,"link":1332},"https:\u002F\u002Farxiv.org\u002Fpdf\u002F2006.11719.pdf",{"name":251,"link":80},[1335],{"name":7,"link":7},{"title":1337,"topic":1338,"figure":1339,"authors":1340,"venue":1341,"links":1342,"highlights":1346},"L2R²: Leveraging Ranking for Abductive Reasoning",[729],"\u002Fimage\u002F52.png",[703,175,64,654],{"name":863,"year":1213,"link":7},[1343,1345],{"name":209,"link":1344},"https:\u002F\u002Farxiv.org\u002Fpdf\u002F2005.11223",{"name":251,"link":80},[1347],{"name":7,"link":7},{"title":1349,"selected":195,"topic":1350,"figure":1351,"authors":1352,"venue":1354,"links":1355,"highlights":1359},"SetRank: Learning a Permutation-Invariant Ranking Model for Information Retrieval",[729],"\u002Fimage\u002F53.png",[175,756,732,64,654,1353],"Jirong Wen",{"name":863,"year":1213,"link":7},[1356,1358],{"name":209,"link":1357},"https:\u002F\u002Farxiv.org\u002Fpdf\u002F1912.05891",{"name":251,"link":80},[1360],{"name":7,"link":7},{"title":1362,"topic":1363,"figure":1364,"authors":1365,"venue":1366,"links":1368,"highlights":1372},"Dual-Factor Generation Model for Conversation",[667],"\u002Fimage\u002F54.png",[1005,653,808,64,654],{"name":1367,"year":1213,"link":7},"TOIS",[1369,1371],{"name":209,"link":1370},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fpdf\u002F10.1145\u002F3394052",{"name":251,"link":80},[1373],{"name":7,"link":7},{"title":1375,"topic":1376,"figure":1377,"authors":1378,"venue":1380,"links":1381,"highlights":1385},"Robust Reinforcement Learning with Wasserstein Constraint",[773],"\u002Fimage\u002F55.png",[1379,175,71,64,778,757],"Linfang Hou",{"name":692,"year":1213,"link":7},[1382,1384],{"name":209,"link":1383},"https:\u002F\u002Farxiv.org\u002Fabs\u002F2006.00945",{"name":251,"link":80},[1386],{"name":7,"link":7},{"title":1388,"topic":1389,"figure":1390,"authors":1391,"venue":1392,"links":1393,"highlights":1397},"Structure Learning for Headline Generation",[667],"\u002Fimage\u002F56.png",[1005,653,808,64,654],{"name":263,"year":1213,"link":7},[1394,1396],{"name":209,"link":1395},"https:\u002F\u002Fojs.aaai.org\u002Findex.php\u002FAAAI\u002Farticle\u002Fview\u002F6501",{"name":251,"link":80},[1398],{"name":7,"link":7},{"title":1400,"topic":1401,"figure":1402,"authors":1403,"venue":1404,"links":1405,"highlights":1409},"Label Distribution Augmented Maximum Likelihood Estimation for Reading Comprehension",[667],"\u002Fimage\u002F57.png",[1130,653,808,64,654],{"name":1133,"year":1213,"link":7},[1406,1408],{"name":209,"link":1407},"https:\u002F\u002Fjiafengguo.github.io\u002F2020\u002F2020-Label%20Distribution%20Augmented%20Maximum%20Likelihood%20Estimation%20for%20Reading%20Comprehension.pdf",{"name":251,"link":80},[1410],{"name":7,"link":7},{"title":1412,"topic":1413,"figure":1414,"authors":1415,"venue":1416,"links":1419,"highlights":1422},"Understanding and Improving Neural Ranking Models from a Term Dependence View",[729],"\u002Fimage\u002F482323_1_En_11_Fig1_HTML.webp",[808,653,64,654],{"name":1417,"year":1418,"link":7},"AIRS",2019,[1420],{"name":209,"link":1421},"https:\u002F\u002Flink.springer.com\u002Fchapter\u002F10.1007\u002F978-3-030-42835-8_11",[1423],{"name":7,"link":7},{"title":1425,"topic":1426,"figure":1427,"authors":1428,"venue":1430,"links":1432,"highlights":1435},"Trend-smooth: Accelerate Asynchronous SGD by Smoothing Parameters Using Parameter Trends",[773],"\u002Fimage\u002FTrend-smooth.jpg",[1429,653,808,64,654],"Guoxin Cui",{"name":1431,"year":1418,"link":7},"IEEE Access",[1433],{"name":209,"link":1434},"https:\u002F\u002Fieeexplore.ieee.org\u002Fabstract\u002Fdocument\u002F8883154",[1436],{"name":7,"link":7},{"title":1438,"topic":1439,"figure":1440,"authors":1441,"venue":1442,"links":1443,"highlights":1446},"Controlling Risk of Web Question Answering",[729],"\u002Fimage\u002Fcrwqa.png",[1130,653,1061,64,654],{"name":863,"year":1418,"link":7},[1444],{"name":209,"link":1445},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fabs\u002F10.1145\u002F3331184.3331261",[1447],{"name":7,"link":7},{"title":1449,"topic":1450,"figure":1451,"authors":1452,"venue":1453,"links":1454,"highlights":1457},"Outline Generation: Understanding the Inherent Content Structure of Documents",[729],"\u002Fimage\u002Foutlinegen.png",[1005,653,1061,64,654],{"name":863,"year":1418,"link":7},[1455],{"name":209,"link":1456},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fabs\u002F10.1145\u002F3331184.3331208",[1458],{"name":7,"link":7},{"title":1460,"topic":1461,"figure":1462,"authors":1463,"venue":1464,"links":1465,"highlights":1468},"An Adaptive Framework for Conversational Question Answering",[667],"\u002Fimage\u002Fadaptivecqa.png",[1130,653,1061,64,1005,654],{"name":263,"year":1418,"link":7},[1466],{"name":209,"link":1467},"https:\u002F\u002Faaai.org\u002Fojs\u002Findex.php\u002FAAAI\u002Farticle\u002Fview\u002F5157\u002F5030",[1469],{"name":7,"link":7},{"title":1471,"topic":1472,"figure":1473,"authors":1474,"venue":1475,"links":1476,"highlights":1479},"Differentiated Distribution Recovery for Neural Text Generation",[667],"\u002Fimage\u002Fddrntg.png",[181,64,653,756,654],{"name":263,"year":1418,"link":7},[1477],{"name":209,"link":1478},"https:\u002F\u002Faaai.org\u002Fojs\u002Findex.php\u002FAAAI\u002Farticle\u002Fdownload\u002F4639\u002F4517",[1480],{"name":7,"link":7},{"title":1482,"topic":1483,"figure":1484,"authors":1485,"venue":1488,"links":1489,"highlights":1492},"Teaching Machines to Extract Main Content for Machine Reading Comprehension",[667],"\u002Fimage\u002Ftmemcmrc.png",[1486,1487,756,653,64,654],"Zhaohui Li","Yue Feng",{"name":263,"year":1418,"link":7},[1490],{"name":209,"link":1491},"https:\u002F\u002Faaai.org\u002Fojs\u002Findex.php\u002FAAAI\u002Farticle\u002Fdownload\u002F5123\u002F4996",[1493],{"name":7,"link":7},{"title":1495,"topic":1496,"figure":1497,"authors":1498,"venue":1499,"links":1500,"highlights":1503},"HAS-QA: Hierarchical Answer Spans Model for Open-Domain Question Answering",[667],"\u002Fimage\u002Fhasqa.png",[175,64,653,756,1130,654],{"name":263,"year":1418,"link":7},[1501],{"name":209,"link":1502},"https:\u002F\u002Fojs.aaai.org\u002Findex.php\u002FAAAI\u002Farticle\u002Fview\u002F4664\u002F4542",[1504],{"name":7,"link":7},{"title":1506,"selected":195,"topic":1507,"figure":1508,"authors":1509,"venue":1510,"links":1512,"highlights":1515},"Recosa: Detecting the Relevant Contexts with Self-Attention for Multi-Turn Dialogue Generation",[667],"\u002Fimage\u002Frecosa.png",[178,64,175,653,654],{"name":1511,"year":1418,"link":80},"ACL",[1513],{"name":209,"link":1514},"https:\u002F\u002Farxiv.org\u002Fabs\u002F1907.05339",[1516],{"name":7,"link":7},{"title":1518,"topic":1519,"figure":1520,"authors":1521,"venue":1522,"links":1524,"highlights":1527},"Neighborhood Voting: A Novel Search Scheme for Hashing",[729],"\u002Fimage\u002Fnv.png",[807,653,64,756,654],{"name":796,"year":1523,"link":7},2018,[1525],{"name":209,"link":1526},"https:\u002F\u002Fjiafengguo.github.io\u002F2018\u002F2018-Neighborhood%20Voting-%20A%20Novel%20Search%20Scheme%20for%20Hashing.pdf",[1528],{"name":7,"link":7},{"title":1530,"topic":1531,"figure":1532,"authors":1533,"venue":1535,"links":1536,"highlights":1539},"Question Headline Generation for News Articles",[667],"\u002Fimage\u002Fdaseq2seq.png",[1005,653,808,64,756,1534,654],"Huanhuan Cao",{"name":796,"year":1523,"link":7},[1537],{"name":209,"link":1538},"https:\u002F\u002Fgsai.ruc.edu.cn\u002Fuploads\u002F20211006\u002Fc3f8689df8ff6c4dfd9050e0e2aef383.pdf",[1540],{"name":7,"link":7},{"title":1542,"topic":1543,"figure":1544,"authors":1545,"venue":1547,"links":1548,"highlights":1551},"Multi Page Search with Reinforcement Learning to Rank",[729],"\u002Fimage\u002Fmps.png",[1546,756,64,653,654,1130,1005,1061],"Wei Zeng",{"name":863,"year":1523,"link":7},[1549],{"name":209,"link":1550},"https:\u002F\u002Fjiafengguo.github.io\u002F2018\u002F2018-Multi%20Page%20Search%20with%20Reinforcement%20Learning%20to%20Rank.pdf",[1552],{"name":7,"link":7},{"title":1554,"topic":1555,"figure":1556,"authors":1557,"venue":1558,"links":1559,"highlights":1562},"Mqgrad: Reinforcement Learning of Gradient Quantization in Parameter Server",[773],"\u002Fimage\u002Fmqgrad.png",[1429,756,1546,64,653,654,1130,1005,1061],{"name":863,"year":1523,"link":7},[1560],{"name":209,"link":1561},"https:\u002F\u002Farxiv.org\u002Fpdf\u002F1804.08066",[1563],{"name":7,"link":7},{"title":1565,"topic":1566,"figure":1567,"authors":1568,"venue":1573,"links":1575},"A Question Type Driven Framework to Diversify Visual Question Generation",[650],"\u002Fimage\u002Fi2q_example.png",[1569,1570,1571,1572,64],"Zhihao Fan","Zhongyu Wei","Piji Li","Huang Xuanjing",{"name":1158,"year":1523,"link":1574},"https:\u002F\u002Fwww.ijcai.org\u002Fproceedings\u002F2018\u002F",[1576],{"name":209,"link":1577},"https:\u002F\u002Fwww.ijcai.org\u002Fproceedings\u002F2018\u002F0563.pdf",{"title":1579,"topic":1580,"figure":1581,"authors":1582,"venue":1583,"links":1585},"RI-Match: Integrating Both Representations and Interactions for Deep Semantic Matching",[667],"\u002Fimage\u002Frimatch_frame.png",[991,64,175,653,756,654],{"name":1417,"year":1523,"link":1584},"https:\u002F\u002Flink.springer.com\u002Fbook\u002F10.1007\u002F978-3-030-03520-4",[1586],{"name":209,"link":1587},"https:\u002F\u002Flink.springer.com\u002Fchapter\u002F10.1007\u002F978-3-030-03520-4_9",{"title":1589,"topic":1590,"figure":1591,"authors":1592,"venue":1594,"links":1596},"A Comparison Between Term-Based and Embedding-Based Methods for Initial Retrieval",[729],"\u002Fimage\u002Fcomparsion_initial_retrieval_chart.png",[1593,653,64,808,756,654],"Tonglei Guo",{"name":810,"year":1523,"link":1595},"https:\u002F\u002Flink.springer.com\u002Fbook\u002F10.1007\u002F978-3-030-01012-6",[1597],{"name":209,"link":1598},"https:\u002F\u002Flink.springer.com\u002Fchapter\u002F10.1007\u002F978-3-030-01012-6_3",{"title":1600,"topic":1601,"figure":1602,"authors":1603,"venue":1607,"links":1608},"A Deep Top-k Relevance Matching Model for Ad-hoc Retrieval",[773],"\u002Fimage\u002Ftopk_relevance_matching.png",[1604,1605,653,808,762,64,1606,654],"Zhou Yang","Qingfeng Lan","Yue Wang",{"name":810,"year":1523,"link":1595},[1609],{"name":209,"link":1610},"https:\u002F\u002Flink.springer.com\u002Fchapter\u002F10.1007\u002F978-3-030-01012-6_2",{"title":1612,"topic":1613,"figure":1614,"authors":1615,"venue":1618,"links":1619,"highlights":1622},"Text Matching with Monte Carlo Tree Search",[729,667],"\u002Fimage\u002FText_Matching_with_Monte_Carlo_Tree_Search.png",[1616,1617,756,653,64,654],"Yixuan He","Shuchang Tao",{"name":810,"year":1523,"link":1595},[1620],{"name":209,"link":1621},"https:\u002F\u002Flink.springer.com\u002Fchapter\u002F10.1007\u002F978-3-030-01012-6_4",[1623],{"name":7,"link":7},{"title":1625,"topic":1626,"figure":1627,"authors":1628,"venue":1629,"links":1630},"Reinforcing Coherence for Sequence to Sequence Model in Dialogue Generation",[667],"\u002Fimage\u002Freinforcing_coherence_example.png",[178,64,653,756,654],{"name":1158,"year":1523,"link":1574},[1631],{"name":209,"link":1632},"https:\u002F\u002Fwww.ijcai.org\u002Fproceedings\u002F2018\u002F0635.pdf",{"title":1634,"topic":1635,"figure":1636,"authors":1637,"venue":1638,"links":1640},"Learning to Control the Specificity in Neural Response Generation",[667],"\u002Fimage\u002Flearn_control_frame.png",[1005,653,64,756,654],{"name":1511,"year":1523,"link":1639},"https:\u002F\u002Faclanthology.org\u002Fvenues\u002Facl\u002F",[1641,1643],{"name":209,"link":1642},"https:\u002F\u002Faclanthology.org\u002FP18-1102.pdf",{"name":1644,"link":1645},"Video","https:\u002F\u002Fvimeo.com\u002F285802316",{"title":1647,"selected":195,"topic":1648,"figure":1649,"authors":1650,"venue":1651,"links":1652},"Tailored Sequence to Sequence Models to Different Conversation Scenarios",[667],"\u002Fimage\u002FMGL_CVaR_chart.png",[178,64,653,756,654],{"name":1511,"year":1523,"link":1639},[1653],{"name":209,"link":1654},"https:\u002F\u002Faclanthology.org\u002FP18-1137.pdf",{"title":1656,"topic":1657,"figure":1658,"authors":1659,"venue":1660,"links":1663},"Modeling the Parameter Interactions in Ranking SVM with Low-rank Approximation",[773],"\u002Fimage\u002Fparam_interaction_front.png",[756,1546,64,653,654],{"name":1661,"year":1418,"link":1662},"TKDE","https:\u002F\u002Fieeexplore.ieee.org\u002F",[1664],{"name":209,"link":1665},"https:\u002F\u002Fieeexplore.ieee.org\u002Fabstract\u002Fdocument\u002F8399140",{"title":1667,"topic":1668,"figure":1669,"authors":1670,"venue":1672,"links":1674},"Reducing Variance in Gradient Bandit Algorithm Using Antithetic Variates Method",[773],"\u002Fimage\u002Freduce_variance_chart.png",[1671,756,64,653,654],"Sihao Yu",{"name":863,"year":1523,"link":1673},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fproceedings\u002F10.1145\u002F3209978",[1675],{"name":209,"link":1676},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fabs\u002F10.1145\u002F3209978.3210068",{"title":1678,"topic":1679,"figure":1680,"authors":1681,"venue":1682,"links":1683},"From Greedy Selection to Exploratory Decision-Making: Diverse Ranking with Policy-Value Networks",[773],"\u002Fimage\u002Fm2div_frame.png",[1487,756,64,653,1546,654],{"name":863,"year":1523,"link":1673},[1684],{"name":209,"link":1685},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fabs\u002F10.1145\u002F3209978.3209979",{"title":1687,"topic":1688,"figure":1689,"authors":1690,"venue":1692,"links":1693},"Modeling Diverse Relevance Patterns in Ad-hoc Retrieval",[729],"\u002Fimage\u002Fhierarchical_neural_matching_frame.png",[808,653,64,756,1691,654],"ChengXiang Zhai",{"name":863,"year":1523,"link":1673},[1694],{"name":209,"link":1695},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fabs\u002F10.1145\u002F3209978.3209980",{"title":1697,"topic":1698,"figure":1699,"authors":1700,"venue":1703,"links":1704},"A Tree Search Algorithm for Sequence Labeling",[773],"\u002Fimage\u002Ftree_search_algorithm.png",[1701,756,64,653,1702,654],"Yadi Lao","Gao Sheng",{"name":692,"year":1523,"link":7},[1705],{"name":209,"link":1706},"https:\u002F\u002Farxiv.org\u002Fabs\u002F1804.10911",{"title":1708,"topic":1709,"figure":1710,"authors":1711,"venue":1712,"links":1714},"Fast Approximate Nearest Neighbor Search via K-diverse Nearest Neighbor Graph",[773],"\u002Fimage\u002Ffast_approximate_chart.png",[807,653,64,756,654],{"name":263,"year":1523,"link":1713},"https:\u002F\u002Fojs.aaai.org\u002Findex.php\u002FAAAI\u002Findex",[1715],{"name":209,"link":1716},"https:\u002F\u002Fojs.aaai.org\u002Findex.php\u002FAAAI\u002Farticle\u002Fview\u002F12138",{"title":1718,"topic":1719,"figure":1720,"authors":1721,"venue":1722,"links":1723,"highlights":1726},"Hierarchical Answer Selection Framework for Multi-passage Machine Reading Comprehension",[729,667],"\u002Fimage\u002FHierarchical_Answer_Selection_Framework.png",[1486,756,64,653,1487,654],{"name":810,"year":1523,"link":1595},[1724],{"name":209,"link":1725},"https:\u002F\u002Flink.springer.com\u002Fchapter\u002F10.1007\u002F978-3-030-01012-6_8",[1727],{"name":7,"link":7},{"title":1729,"topic":1730,"figure":7,"authors":1731,"venue":1733,"links":1734,"highlights":1736},"Sequence Tagging with Policy-Value Networks and Tree Search",[729,667],[1701,756,64,653,1732,654],"Sheng Gao",{"name":692,"year":1523,"link":7},[1735],{"name":209,"link":1706},[1737],{"name":7,"link":7},{"title":1739,"topic":1740,"figure":7,"authors":1741,"venue":1742,"links":1745,"highlights":1748},"Aggregating Neural Word Embeddings for Document Representation",[729,667],[1005,653,64,756,654],{"name":1743,"year":1523,"link":1744},"ECIR","https:\u002F\u002Flink.springer.com\u002Fbook\u002F10.1007\u002F978-3-319-76941-7",[1746],{"name":209,"link":1747},"https:\u002F\u002Flink.springer.com\u002Fchapter\u002F10.1007\u002F978-3-319-76941-7_23",[1749],{"name":7,"link":7},{"title":1751,"topic":1752,"figure":1753,"authors":1754,"venue":1755,"links":1756,"highlights":1759},"Spherical Paragraph Model",[729,667],"\u002Fimage\u002FSpherical_Paragraph_Model.png",[1005,653,64,756,654],{"name":1743,"year":1523,"link":1744},[1757],{"name":209,"link":1758},"https:\u002F\u002Flink.springer.com\u002Fchapter\u002F10.1007\u002F978-3-319-76941-7_22",[1760],{"name":7,"link":7},{"title":1762,"topic":1763,"figure":1764,"authors":1765,"venue":1766,"links":1768,"highlights":1771},"Generative Paragraph Vector",[729,667],"\u002Fimage\u002FGenerative_Paragraph_Vector.png",[1005,653,64,756,654],{"name":810,"year":1523,"link":1767},"https:\u002F\u002Flink.springer.com\u002Fchapter\u002F10.1007\u002F978-3-030-01012-6",[1769],{"name":209,"link":1770},"https:\u002F\u002Flink.springer.com\u002Fchapter\u002F10.1007\u002F978-3-030-01012-6_9",[1772],{"name":7,"link":7},{"title":1774,"topic":1775,"figure":1776,"authors":1777,"venue":1779,"links":1783,"highlights":1786},"Locally Smoothed Neural Networks",[773],"\u002Fimage\u002FLocally_smoothed_neural_networks.png",[1778,64,756,653,654],"Liang Peng",{"name":1780,"year":1781,"link":1782},"PMLR",2017,"http:\u002F\u002Fproceedings.mlr.press\u002F",[1784],{"name":209,"link":1785},"http:\u002F\u002Fproceedings.mlr.press\u002Fv77\u002Fpang17a\u002Fpang17a.pdf",[1787],{"name":7,"link":7},{"title":1789,"selected":195,"topic":1790,"figure":1791,"authors":1792,"venue":1793,"links":1795,"highlights":1798},"Learning Visual Features from Snapshots for Web Search",[773,729],"\u002Fimage\u002FLearning_visual_features.png",[808,653,64,756,1778,654],{"name":796,"year":1781,"link":1794},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fproceedings\u002F10.1145\u002F3132847",[1796],{"name":209,"link":1797},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fabs\u002F10.1145\u002F3132847.3132943",[1799],{"name":1800,"link":1801},"Best Full Paper Runner-ups","http:\u002F\u002Fwww.cikmconference.org\u002FCIKM2017\u002F",{"title":1803,"selected":195,"topic":1804,"figure":1805,"authors":1806,"venue":1808,"links":1809,"highlights":1812},"Deeprank: A New Deep Architecture for Relevance Ranking in Information Retrieval",[773,729],"\u002Fimage\u002FDeepRank.png",[1778,64,653,756,1807,654],"Jingfang Xu",{"name":796,"year":1781,"link":1794},[1810],{"name":209,"link":1811},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fabs\u002F10.1145\u002F3132847.3132914",[1813],{"name":7,"link":7},{"title":1815,"topic":1816,"figure":1817,"authors":1818,"venue":1825,"links":1828,"highlights":1831},"Using Local Clocks to Reproduce Concurrency Bugs",[773],"\u002Fimage\u002FUsing_local_clocks.png",[1819,1820,1821,1822,1823,64,1824],"Zhe Wang","Chenggang Wu","Pen-Chung Yew","Jeff Huang","Xiaobing Feng","Yunji Chen",{"name":1826,"year":1781,"link":1827},"TSE","https:\u002F\u002Fieeexplore.ieee.org\u002FXplore\u002Fhome.jsp",[1829],{"name":209,"link":1830},"https:\u002F\u002Fieeexplore.ieee.org\u002Fdocument\u002F8038023",[1832],{"name":7,"link":7},{"title":1834,"topic":1835,"figure":1836,"authors":1837,"venue":1838,"links":1840,"highlights":1843},"Adapting Markov Decision Process for Search Result Diversification",[729,667],"\u002Fimage\u002FAdapting_Markov_Decision_Process.png",[1300,756,64,653,1546,654],{"name":863,"year":1781,"link":1839},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fproceedings\u002F10.1145\u002F3077136",[1841],{"name":209,"link":1842},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fabs\u002F10.1145\u002F3077136.3080775",[1844],{"name":7,"link":7},{"title":1846,"topic":1847,"figure":1848,"authors":1849,"venue":1850,"links":1851,"highlights":1854},"Reinforcement Learning to Rank with Markov Decision Process",[729,667],"\u002Fimage\u002FReinforcement_learning_to_rank.png",[1299,756,64,653,654],{"name":863,"year":1781,"link":1839},[1852],{"name":209,"link":1853},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fabs\u002F10.1145\u002F3077136.3080685",[1855],{"name":7,"link":7},{"title":1857,"topic":1858,"figure":1859,"authors":1860,"venue":1861,"links":1862,"highlights":1865},"A Deep Investigation of Deep IR Models",[729,667],"\u002Fimage\u002FA_deep_investigation_of_deep_IR_models.png",[1778,64,653,756,654],{"name":863,"year":1781,"link":1839},[1863],{"name":209,"link":1864},"https:\u002F\u002Farxiv.org\u002Fabs\u002F1707.07700",[1866],{"name":7,"link":7},{"title":1868,"topic":1869,"figure":1870,"authors":1871,"venue":1872,"links":1874,"highlights":1877},"Learning for Search Result Diversification",[729],"\u002Fimage\u002F135_LSRD.png",[172,64,653,654,169],{"name":863,"year":1873,"link":7},2014,[1875],{"name":209,"link":1876},"http:\u002F\u002Fyadongzhu.com\u002Fpapers\u002FLearning%20for%20Search%20Result%20Diversification.pdf",[1878],{"name":7,"link":7},{"title":1880,"topic":1881,"figure":1882,"authors":1883,"venue":1884,"links":1886,"highlights":1889},"Position-Aware ListMLE: A Sequential Learning Process for Ranking",[729],"\u002Fimage\u002F136_MQ2007_list.png",[64,172,653,169,654],{"name":1885,"year":1873,"link":7},"UAI",[1887],{"name":209,"link":1888},"https:\u002F\u002Fwww.researchgate.net\u002Fprofile\u002FYanyan-Lan\u002Fpublication\u002F287206663_Position-Aware_ListMLE_A_Sequential_Learning_Process_for_Ranking\u002Flinks\u002F567358fd08ae04d9b099d7fb\u002FPosition-Aware-ListMLE-A-Sequential-Learning-Process-for-Ranking.pdf",[1890],{"name":7,"link":7},{"title":1892,"topic":1893,"figure":1894,"authors":1895,"venue":1897,"links":1898,"highlights":1901},"BTM: Topic Modeling Over Short Texts",[667],"\u002Fimage\u002F137_BTM.png",[654,1896,64,653],"Xiaohui Yan",{"name":1661,"year":1873,"link":7},[1899],{"name":209,"link":1900},"https:\u002F\u002Fwww.researchgate.net\u002Fprofile\u002FYanyan-Lan\u002Fpublication\u002F269940995_BTM_Topic_modeling_over_short_texts\u002Flinks\u002F567353a808ae04d9b099d797\u002FBTM-Topic-modeling-over-short-texts.pdf",[1902],{"name":7,"link":7},{"title":1904,"topic":1905,"figure":1906,"authors":1907,"venue":1910,"links":1911,"highlights":1914},"Name Disambiguation by Collective Classification",[729],"\u002Fimage\u002F138_NameDisambiguation.png",[1908,653,64,1909,654],"Zhongxiang Chen","Lei Cao",{"name":1417,"year":1873,"link":7},[1912],{"name":209,"link":1913},"https:\u002F\u002Fjiafengguo.github.io\u002F2014\u002F2014-Name%20Disambiguation%20by%20Collective%20Classification.pdf",[1915],{"name":7,"link":7},{"title":1917,"topic":1918,"figure":1919,"authors":1920,"venue":1922,"links":1923,"highlights":1926},"Local Linear Matrix Factorization for Document Modeling",[729],"\u002Fimage\u002F139_LLMF.png",[1921,653,64,654],"Lu Bai",{"name":1743,"year":1873,"link":7},[1924],{"name":209,"link":1925},"https:\u002F\u002Fjiafengguo.github.io\u002F2014\u002F2014-Local%20Linear%20Matrix%20Factorization%20for%20Document%20Modeling.pdf",[1927],{"name":7,"link":7},{"title":1929,"topic":1930,"figure":1931,"authors":1932,"venue":1934,"links":1937,"highlights":1940},"A Novel Relational Learning-to-Rank Approach for Topic-Focused Multi-Document Summarization",[729],"\u002Fimage\u002F140_sequential_ranking.png",[172,64,653,1933,654],"Pan Du",{"name":1935,"year":1936,"link":7},"ICDM",2013,[1938],{"name":209,"link":1939},"https:\u002F\u002Fjiafengguo.github.io\u002F2013\u002F2013-A%20Novel%20Relational%20Learning-to-Rank%20Approach%20for%20Topic-Focused%20Multi-document%20Summarization.pdf",[1941],{"name":7,"link":7},{"title":1943,"topic":1944,"figure":1945,"authors":1946,"venue":1947,"links":1948,"highlights":1951},"Is Top-k Sufficient for Ranking?",[729],"\u002Fimage\u002F141_IsTop-k.png",[64,169,653,654],{"name":796,"year":1936,"link":7},[1949],{"name":209,"link":1950},"https:\u002F\u002Fjiafengguo.github.io\u002F2013\u002F2013-Is%20Top-k%20Sufficient%20for%20Ranking%3F.pdf",[1952],{"name":7,"link":7},{"title":1954,"topic":1955,"figure":1956,"authors":1957,"venue":1958,"links":1959,"highlights":1962},"Stochastic Rank Aggregation",[729],"\u002Fimage\u002F142_Stochastic_Rank.png",[169,64,653,654],{"name":692,"year":1936,"link":7},[1960],{"name":209,"link":1961},"https:\u002F\u002Farxiv.org\u002Fftp\u002Farxiv\u002Fpapers\u002F1309\u002F1309.6852.pdf",[1963],{"name":7,"link":7},{"title":1965,"topic":1966,"figure":1967,"authors":1968,"venue":1971,"links":1972,"highlights":1975},"Informational Friend Recommendation in Social Media",[729],"\u002Fimage\u002F143_Informational_Friend.png",[1969,64,653,1970,654],"Shengxian Wan","Chaosheng Fan",{"name":863,"year":1936,"link":7},[1973],{"name":209,"link":1974},"https:\u002F\u002Fjiafengguo.github.io\u002F2013\u002F2013-Informational%20friend%20recommendation%20in%20social%20media.pdf",[1976],{"name":7,"link":7},{"title":1978,"topic":1979,"figure":1980,"authors":1981,"venue":1983,"links":1984,"highlights":1987},"Collaborative Factorization for Recommender Systems",[729],"\u002Fimage\u002F144_Collaborative_Factorization.png",[1970,64,653,1982,654],"Zuoquan Lin",{"name":863,"year":1936,"link":7},[1985],{"name":209,"link":1986},"https:\u002F\u002Fwww.researchgate.net\u002Fprofile\u002FYanyan-Lan\u002Fpublication\u002F262222055_Collaborative_factorization_for_recommender_systems\u002Flinks\u002F56735a4508aedbbb3f9f979a\u002FCollaborative-factorization-for-recommender-systems.pdf",[1988],{"name":7,"link":7},{"title":1990,"selected":195,"topic":1991,"figure":1992,"authors":1993,"venue":1994,"links":1995,"highlights":1998},"A Biterm Topic Model for Short Texts",[667],"\u002Fimage\u002F145_Biterm_Topic.png",[1896,653,64,654],{"name":1075,"year":1936,"link":7},[1996],{"name":209,"link":1997},"http:\u002F\u002Fxiaohuiyan.github.io\u002Fpaper\u002FBTM-WWW13.pdf",[1999],{"name":2000,"link":2001},"Most Influential WWW Papers","https:\u002F\u002Fwww.paperdigest.org\u002F2022\u002F05\u002Fmost-influential-www-papers-2022-05\u002F",{"title":2003,"topic":2004,"figure":2005,"authors":2006,"venue":2007,"links":2008,"highlights":2011},"Group Sparse Topical Coding: From Code to Topic",[729],"\u002Fimage\u002F146_Group_Sparse.png",[1921,653,64,654],{"name":1133,"year":1936,"link":7},[2009],{"name":209,"link":2010},"https:\u002F\u002Fjiafengguo.github.io\u002F2013\u002F2013-Group%20Sparse%20Topical%20Coding:%20From%20Code%20to%20Topic.pdf",[2012],{"name":7,"link":7},{"title":2014,"topic":2015,"figure":2016,"authors":2017,"venue":2019,"links":2020,"highlights":2023},"Recommending High Utility Query via Session-Flow Graph",[729],"\u002Fimage\u002F147_Recommending_High.png",[762,653,654,64,2018],"Wolfgang Nejdl",{"name":1743,"year":1936,"link":7},[2021],{"name":209,"link":2022},"https:\u002F\u002Fjiafengguo.github.io\u002F2013\u002F2013-Recommending%20High%20Utility%20Query%20via%20Session-Flow%20Graph.pdf",[2024],{"name":7,"link":7},{"title":2026,"selected":195,"figure":2027,"topic":2028,"authors":2029,"venue":2031,"links":2032,"highlights":2037},"MatchZoo: A Toolkit for Deep Text Matching","\u002Fimage\u002Fmatchzoo-logo.png",[729],[808,175,2030,653,64,654],"JianPeng Hou",{"name":692,"year":1781,"link":80},[2033,2035],{"name":209,"link":2034},"https:\u002F\u002Farxiv.org\u002Fabs\u002F1707.07270",{"name":251,"link":2036},"https:\u002F\u002Fgithub.com\u002FNTMC-Community\u002FMatchZoo",[2038],{"name":7,"link":7},{"title":2040,"figure":2041,"topic":2042,"authors":2043,"venue":2046,"links":2048,"highlights":2051},"Query Ranking Model for Search Engine Query Recommendation","\u002Fimage\u002FQuery_Ranking_Model.png",[729],[2044,2045,653,64],"JianGuo Wang","Joshua Zhexue Huang",{"name":2047,"year":1781,"link":80},"IJMLC",[2049],{"name":209,"link":2050},"https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs13042-015-0362-5",[2052],{"name":7,"link":7},{"title":2054,"figure":2055,"topic":2056,"authors":2057,"venue":2064,"links":2065,"highlights":2068},"Efficient Delivery Policy to Minimize User Traffic Consumption in Guaranteed Advertising","\u002Fimage\u002FEfficient_Delivery_Policy.png",[773],[2058,2059,2060,2061,64,2062,2063],"Jia Zhang","Zheng Wang","Qian Li","Jialin Zhang","Qiang Li","Xiaoming Sun",{"name":263,"year":1781,"link":80},[2066],{"name":209,"link":2067},"https:\u002F\u002Farxiv.org\u002Fabs\u002F1611.07599",[2069],{"name":7,"link":7},{"title":2071,"figure":2072,"topic":2073,"authors":2074,"venue":2075,"links":2077,"highlights":2080},"Modeling Users' Search Sessions for High Utility Query Recommendation","\u002Fimage\u002FModeling_Users_Search_Sessions.png",[729],[653,762,64,654],{"name":2076,"year":1781,"link":80},"Information Retrieval Journal",[2078],{"name":209,"link":2079},"https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10791-016-9287-1",[2081],{"name":7,"link":7},{"title":2083,"topic":2084,"authors":2085,"venue":2086,"links":2089,"highlights":2092,"figure":7},"Directly Optimize Diversity Evaluation Measures: A New Approach to Search Result Diversification",[729],[756,1300,64,653,654],{"name":2087,"year":1781,"link":2088},"TIST","https:\u002F\u002Fdl.acm.org\u002Ftoc\u002Ftist\u002F2017\u002F8\u002F3",[2090],{"name":209,"link":2091},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002F10.1145\u002F2983921",[2093],{"name":7,"link":7},{"title":2095,"figure":2096,"topic":2097,"authors":2098,"venue":2099,"links":2101,"highlights":2104},"Academic Access Data Analysis for Literature Recommendation","\u002Fimage\u002FAcademic_Access_Data_Analysis.png",[729],[808,653,64,756,654],{"name":810,"year":1781,"link":2100},"https:\u002F\u002Fwww.springer.com\u002Fseries\u002F558",[2102],{"name":209,"link":2103},"https:\u002F\u002Flink.springer.com\u002Fchapter\u002F10.1007\u002F978-3-319-68699-8_4",[2105],{"name":7,"link":7},{"title":2107,"topic":2108,"authors":2109,"venue":2112,"links":2114,"highlights":2117,"figure":7},"Dynamic-K Recommendation with Personalized Decision Boundary",[729],[2110,653,64,2111],"Yan Gao","Huaming Liao",{"name":810,"year":1781,"link":2113},"https:\u002F\u002Flink.springer.com\u002Fbook\u002F10.1007\u002F978-3-319-68699-8",[2115],{"name":209,"link":2116},"https:\u002F\u002Flink.springer.com\u002Fchapter\u002F10.1007\u002F978-3-319-68699-8_2",[2118],{"name":7,"link":7},{"title":2120,"figure":2121,"topic":2122,"authors":2123,"venue":2124,"links":2125,"highlights":2128},"Neural Or Statistical: An Empirical Study on Language Models for Chinese Input Recommendation on Mobile","\u002Fimage\u002FNeural_or_Statistical.png",[667],[178,64,653,756,654],{"name":810,"year":1781,"link":2113},[2126],{"name":209,"link":2127},"https:\u002F\u002Flink.springer.com\u002Fchapter\u002F10.1007\u002F978-3-319-68699-8_1",[2129],{"name":7,"link":7},{"title":2131,"figure":2132,"topic":2133,"authors":2134,"venue":2136,"links":2139,"highlights":2142},"An Incremental Model on Search Engine Query Recommendation","\u002Fimage\u002FAn_Incremental_Model.png",[729],[2044,2045,2135,653,64],"Dingming Wu",{"name":678,"year":2137,"link":2138},2016,"https:\u002F\u002Fwww.sciencedirect.com\u002Fjournal\u002Fneurocomputing\u002Fvol\u002F218\u002Fsuppl\u002FC",[2140],{"name":209,"link":2141},"https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fabs\u002Fpii\u002FS0925231216310037",[2143],{"name":7,"link":7},{"title":2145,"figure":2146,"topic":2147,"authors":2148,"venue":2149,"links":2151,"highlights":2154},"Sparse Word Embeddings Using L1 Regularized Online Learning","\u002Fimage\u002FSparse_Word_Embeddings.png",[667],[1262,653,64,756,654],{"name":1158,"year":2137,"link":2150},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fproceedings\u002F10.5555\u002F3060832",[2152],{"name":209,"link":2153},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002F10.5555\u002F3060832.3061029",[2155],{"name":7,"link":7},{"title":2157,"figure":2158,"topic":2159,"authors":2160,"venue":2161,"links":2163,"highlights":2166},"Modeling Document Novelty with Neural Tensor Network for Search Result Diversification","\u002Fimage\u002FModeling_Document_Novelty.png",[729],[1300,756,64,653,654],{"name":863,"year":2137,"link":2162},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fproceedings\u002F10.1145\u002F2911451",[2164],{"name":209,"link":2165},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002F10.1145\u002F2911451.2911498",[2167],{"name":7,"link":7},{"title":2169,"figure":2170,"topic":2171,"authors":2172,"venue":2173,"links":2174,"highlights":2177},"A Study of Matchpyramid Models on Ad-Hoc Retrieval","\u002Fimage\u002FA_Study_of_Matchpyramid_Models.png",[729],[175,64,653,756,654],{"name":692,"year":2137,"link":80},[2175],{"name":209,"link":2176},"https:\u002F\u002Farxiv.org\u002Fabs\u002F1606.04648",[2178],{"name":7,"link":7},{"title":2180,"figure":2181,"selected":195,"topic":2182,"authors":2183,"venue":2184,"links":2185,"highlights":2188},"Match-SRNN: Modeling the Recursive Matching Structure with Spatial RNN","\u002Fimage\u002Fmatch_srnn.png",[729],[1969,64,756,653,175,654],{"name":692,"year":2137,"link":80},[2186],{"name":209,"link":2187},"https:\u002F\u002Farxiv.org\u002Fabs\u002F1604.04378",[2189],{"name":7,"link":7},{"title":2191,"topic":2192,"authors":2193,"venue":2194,"links":2196,"highlights":2198,"figure":7},"Semantic Regularities in Document Representations",[667],[1262,653,64,756,654],{"name":692,"year":2137,"link":2195},"https:\u002F\u002Farxiv.org\u002Fpdf\u002F1603.07603.pdf",[2197],{"name":209,"link":2195},[2199],{"name":7,"link":7},{"title":2201,"topic":2202,"figure":2203,"authors":2204,"venue":2205,"links":2207,"highlights":2210},"Inside Out: Two Jointly Predictive Models for Word Representations and Phrase Representations",[667],"\u002Fimage\u002F111_Framework_for_BEING_model_and_SEING_model.png",[1262,653,64,756,654],{"name":263,"year":2137,"link":2206},"https:\u002F\u002Fojs.aaai.org\u002Findex.php\u002FAAAI\u002Farticle\u002Fview\u002F10338",[2208],{"name":209,"link":2209},"https:\u002F\u002Fojs.aaai.org\u002Findex.php\u002FAAAI\u002Farticle\u002Fview\u002F10338\u002F10197",[2211],{"name":7,"link":7},{"title":2213,"topic":2214,"figure":2215,"authors":2216,"venue":2217,"links":2219,"highlights":2222},"SPAN: Understanding a Question with Its Support Answers",[667],"\u002Fimage\u002F112_CSM Model_SPAN_Model.png",[175,64,653,756,654],{"name":263,"year":2137,"link":2218},"https:\u002F\u002Fojs.aaai.org\u002Findex.php\u002FAAAI\u002Farticle\u002Fview\u002F9928",[2220],{"name":209,"link":2221},"https:\u002F\u002Fojs.aaai.org\u002Findex.php\u002FAAAI\u002Farticle\u002Fview\u002F9928\u002F9787",[2223],{"name":7,"link":7},{"title":2225,"selected":195,"topic":2226,"figure":2227,"authors":2228,"venue":2229,"links":2231,"highlights":2234},"Text Matching As Image Recognition",[667],"\u002Fimage\u002F113_MatchPyramid_on_Text_Matching.png",[175,64,653,756,1969,654],{"name":263,"year":2137,"link":2230},"https:\u002F\u002Fojs.aaai.org\u002Findex.php\u002FAAAI\u002Farticle\u002Fview\u002F10341",[2232],{"name":209,"link":2233},"https:\u002F\u002Fojs.aaai.org\u002Findex.php\u002FAAAI\u002Farticle\u002Fview\u002F10341\u002F10200",[2235],{"name":7,"link":7},{"title":2237,"selected":195,"topic":2238,"figure":2239,"authors":2240,"venue":2241,"links":2243,"highlights":2246},"A Deep Architecture for Semantic Matching with Multiple Positional Sentence Representations",[667],"\u002Fimage\u002F114_Illustration_of_MV-LSTM.png",[1969,64,653,756,175,654],{"name":263,"year":2137,"link":2242},"https:\u002F\u002Fojs.aaai.org\u002Findex.php\u002FAAAI\u002Farticle\u002Fview\u002F10342",[2244],{"name":209,"link":2245},"https:\u002F\u002Fjiafengguo.github.io\u002F2016\u002F2016-Your%20Cart%20tells%20You-Inferring%20Demographic%20Attributes%20from%20Purchase%20Data.pdf",[2247],{"name":7,"link":7},{"title":2249,"topic":2250,"figure":2251,"authors":2252,"venue":2254,"links":2256,"highlights":2258},"Your Cart Tells You: Inferring Demographic Attributes from Purchase Data",[729],"\u002Fimage\u002F115_Architecture_of_SNE.png",[2253,653,64,756,175,654],"Pengfei Wang",{"name":1133,"year":2137,"link":2255},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fabs\u002F10.1145\u002F2835776.2835783",[2257],{"name":209,"link":2255},[2259],{"name":7,"link":7},{"title":2261,"topic":2262,"figure":2263,"authors":2264,"venue":2265,"links":2266,"highlights":2269},"A Study of MatchPyramid Models on Ad-hoc Retrieval",[729],"\u002Fimage\u002F116_Model_structure_of_MatchPyramid.png",[175,64,653,756,654],{"name":692,"year":1936,"link":7},[2267],{"name":209,"link":2268},"https:\u002F\u002Farxiv.org\u002Fpdf\u002F1606.04648.pdf",[2270],{"name":7,"link":7},{"title":2272,"topic":2273,"figure":2274,"authors":2275,"venue":2276,"links":2278,"highlights":2280},"Factorizing Sequential and Historical Purchase Data for Basket Recommendation",[729],"\u002Fimage\u002F117_Contiguous_sequential_patterns_mined_from_a_single_user.png",[2253,653,64,756,654],{"name":1417,"year":2137,"link":2277},"https:\u002F\u002Flink.springer.com\u002Fchapter\u002F10.1007\u002F978-3-319-48051-0_18",[2279],{"name":209,"link":2277},[2281],{"name":7,"link":7},{"title":2283,"topic":2284,"figure":2285,"authors":2286,"venue":2287,"links":2289,"highlights":2291},"Multi-task Representation Learning for Demographic Prediction",[729],"\u002Fimage\u002F118_Structure_of_MTRL.png",[2253,653,64,756,654],{"name":1417,"year":2137,"link":2288},"https:\u002F\u002Flink.springer.com\u002Fchapter\u002F10.1007\u002F978-3-319-30671-1_7",[2290],{"name":209,"link":2288},[2292],{"name":7,"link":7},{"title":2294,"topic":2295,"figure":2296,"authors":2297,"venue":2298,"links":2301,"highlights":2303},"Recommending High-utility Search Engine Queries via a Query-recommending Model",[729],"\u002Fimage\u002F119_query_reformulation_graph.png",[2044,2045,653,64],{"name":678,"year":2299,"link":2300},2015,"https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fabs\u002Fpii\u002FS0925231215005573",[2302],{"name":209,"link":2300},[2304],{"name":7,"link":7},{"title":2306,"topic":2307,"authors":2308,"venue":2312,"links":2314,"highlights":2316,"figure":7},"Modeling Parameter Interactions in Ranking SVM",[773],[2309,756,64,653,2310,2311,654],"Yaogong Zhang","Maoqiang Xie","Yalou Huang",{"name":796,"year":2299,"link":2313},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fabs\u002F10.1145\u002F2806416.2806595",[2315],{"name":209,"link":2313},[2317],{"name":7,"link":7},{"title":2319,"topic":2320,"figure":2321,"authors":2322,"venue":2323,"links":2325,"highlights":2328},"Next Basket Recommendation with Neural Networks",[773],"\u002Fimage\u002F121_NN_Rec_model.png",[1969,64,2253,653,756,654],{"name":2324,"year":2299,"link":7},"RecSys",[2326],{"name":209,"link":2327},"https:\u002F\u002Fceur-ws.org\u002FVol-1441\u002Frecsys2015_poster15.pdf",[2329],{"name":7,"link":7},{"title":2331,"topic":2332,"authors":2333,"venue":2334,"links":2335,"highlights":2338,"figure":7},"Learning Maximal Marginal Relevance Model via Directly Optimizing Diversity Evaluation Measures",[729,667],[1300,756,64,653,654],{"name":863,"year":2299,"link":7},[2336],{"name":209,"link":2337},"https:\u002F\u002Fjiafengguo.github.io\u002F2015\u002F2015-Learning%20Maximal%20Marginal%20Relevance%20Model%20via%20Directy%20Optimizing%20Diversity%20Evaluation%20Measures.pdf",[2339],{"name":7,"link":7},{"title":2341,"figure":2342,"topic":2343,"authors":2344,"venue":2345,"links":2346,"highlights":2349},"Learning Hierarchical Representation Model for Next-Basket Recommendation","\u002Fimage\u002F123.jpg",[729],[2253,653,64,756,1969,654],{"name":863,"year":2299,"link":7},[2347],{"name":209,"link":2348},"https:\u002F\u002Fjiafengguo.github.io\u002F2015\u002F2015-Learning%20Hierarchical%20Representation%20Model%20for%20Next%20Basket%20Recommendation.pdf",[2350],{"name":7,"link":7},{"title":2352,"figure":2353,"topic":2354,"authors":2355,"venue":2356,"links":2357,"highlights":2360},"Which Noise Affects Algorithm Robustness for Learning to Rank","\u002Fimage\u002F124.jpg",[729],[169,64,653,1969,654],{"name":2076,"year":2299,"link":7},[2358],{"name":209,"link":2359},"https:\u002F\u002Faclanthology.org\u002FP15-1014.pdf",[2361],{"name":7,"link":7},{"title":2352,"topic":2363,"authors":2364,"venue":2365,"links":2366,"highlights":2369,"figure":7},[729],[169,64,653,1969,654],{"name":2076,"year":2299,"link":7},[2367],{"name":209,"link":2368},"https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10791-015-9253-3",[2370],{"name":7,"link":7},{"title":2372,"figure":2373,"topic":2374,"authors":2375,"venue":2380,"links":2382,"highlights":2385},"ReCBuLC: Reproducing Concurrency Bugs Using Local Clocks","\u002Fimage\u002F126.jpg",[729],[2376,1820,2377,2378,1821,1822,1823,64,1824,2379],"Xiang Yuan","Zhenjiang Wang","Jianjun Li","Yong Guan",{"name":2381,"year":2299,"link":7},"ICSE",[2383],{"name":209,"link":2384},"https:\u002F\u002Fd1wqtxts1xzle7.cloudfront.net\u002F89494293\u002Frecbulc-libre.pdf?1660249970=&response-content-disposition=inline%3B+filename%3DReCBuLC_Reproducing_Concurrency_Bugs_Usi.pdf&Expires=1698472560&Signature=UndnYHjEfSvu7ZdaPUp35ppxEGmv~AaZBan1pOeM4wQFzqX3S4Lt50dDD7VvraXdLQigkgQZwY8Y2K1k3kMkZWuThZuqhijAkFYQ7kiFo5wsAqYs-TUap1MCZXg~jtb4N8dgpoklVfYj-5MPeBJ0WgplJMXDwdD7Sxl32FjqBUojsKlC-bVuYdpOwgk7kUjlRXPVDmJeAr379x8sNt1kUKugo5UNQkIvVXXqzQo1SznOJpYaJeoVBtAL~k-vOeIufVYviKoo7aEPHU2Gr6cjrlzhCGCzFUhkCW~gUOUXLK2mpIleWQmhsF3xG2PerAUUqCJLPqsnK-vq7lmdTHzmPw__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA",[2386],{"name":7,"link":7},{"title":2388,"figure":2389,"topic":2390,"authors":2391,"venue":2392,"links":2394,"highlights":2397},"Topic-focused Dynamic Information Filtering in Social Media","\u002Fimage\u002F127.jpg",[729],[172,64,653,654],{"name":692,"year":2299,"link":2393},"https:\u002F\u002Farxiv.org\u002Fabs\u002F1504.04945",[2395],{"name":209,"link":2396},"https:\u002F\u002Farxiv.org\u002Fpdf\u002F1504.04945.pdf",[2398],{"name":7,"link":7},{"title":2400,"figure":2401,"topic":2402,"authors":2403,"venue":2404,"links":2406,"highlights":2409},"Structural Learning of Diverse Ranking","\u002Fimage\u002F128.jpg",[729],[172,64,653,654],{"name":692,"year":2299,"link":2405},"https:\u002F\u002Farxiv.org\u002Fabs\u002F1504.04596",[2407],{"name":209,"link":2408},"https:\u002F\u002Farxiv.org\u002Fpdf\u002F1504.04596.pdf",[2410],{"name":7,"link":7},{"title":2412,"figure":2401,"topic":2413,"authors":2414,"venue":2415,"links":2416,"highlights":2419},"A Probabilistic Model for Bursty Topic Discovery in Microblogs",[729],[1896,653,64,756,654],{"name":263,"year":2299,"link":7},[2417],{"name":209,"link":2418},"https:\u002F\u002Fojs.aaai.org\u002Findex.php\u002FAAAI\u002Farticle\u002Fdownload\u002F9199\u002F9058",[2420],{"name":7,"link":7},{"title":2422,"topic":2423,"authors":2424,"venue":2427,"links":2429,"highlights":2432,"figure":7},"Listwise Approach for Rank Aggregation in Crowdsourcing",[729],[169,64,653,654,2425,2426],"Lei Yu","Guoping Long",{"name":2428,"year":2299,"link":7},"ACM International Conference on Web Search and Data Mining",[2430],{"name":209,"link":2431},"https:\u002F\u002Fjiafengguo.github.io\u002F2015\u002F2015-Listwise%20Approach%20for%20Rank%20Aggregation%20in%20Crowdsourcing.pdf",[2433],{"name":7,"link":7},{"title":2435,"topic":2436,"authors":2437,"venue":2438,"links":2440,"highlights":2443,"figure":7},"Text Content Analysis for Web Big Data",[729],[654,64],{"name":2439,"year":2299,"link":7},"BDCC",[2441],{"name":209,"link":2442},"https:\u002F\u002Fwww.mdpi.com\u002F2504-2289\u002F4\u002F1\u002F1",[2444],{"name":7,"link":7},{"title":2446,"figure":2447,"topic":2448,"authors":2449,"venue":2450,"links":2451,"highlights":2454},"Modeling Retail Transaction Data for Personalized Shopping Recommendation","\u002Fimage\u002F132.jpg",[729],[2253,653,64],{"name":796,"year":1873,"link":7},[2452],{"name":209,"link":2453},"https:\u002F\u002Fjiafengguo.github.io\u002F2014\u002F2014-Modeling%20Retail%20Transaction%20Data%20for%20Personalized%20Shopping%20Recommendation.pdf",[2455],{"name":7,"link":7},{"title":2457,"figure":2458,"topic":2459,"authors":2460,"venue":2462,"links":2464,"highlights":2467},"Personalized Paper Recommendation in Online Social Scholar System","\u002Fimage\u002F133.jpg",[729],[2461,653,64,1909],"Huan Xue",{"name":2463,"year":1873,"link":7},"ASONAM",[2465],{"name":209,"link":2466},"https:\u002F\u002Fjiafengguo.github.io\u002F2014\u002F2014-Personalized%20paper%20recommendation%20in%20online%20social%20scholar%20system.pdf",[2468],{"name":7,"link":7},{"title":2470,"topic":2471,"authors":2472,"venue":2478,"links":2480,"figure":7},"What Makes Data Robust: A Data Analysis in Learning to Rank",[729],[2473,2474,2475,2476,2477],"Niu, Shuzi","Lan, Yanyan","Guo, Jiafeng","Cheng, Xueqi","Geng, Xiubo",{"name":863,"pages":2479,"year":1873},"1191-1194",[2481],{"name":209,"link":2482},"https:\u002F\u002Fjiafengguo.github.io\u002F2014\u002F2014-What%20Makes%20Data%20Robust:%20A%20Data%20Analysis%20in%20Learning%20to%20Rank.pdf",{"title":2484,"topic":2485,"figure":2486,"authors":2487,"venue":2488,"links":2490,"highlights":2493},"More Than Relevance: High Utility Query Recommendation by Mining Users' Search Behaviors",[729],"\u002Fimage\u002FMore_Than_Relevance.png",[762,653,654,64],{"name":796,"year":2489,"link":7},2012,[2491],{"name":209,"link":2492},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fabs\u002F10.1145\u002F2396761.2398523",[2494],{"name":7,"link":7},{"title":2496,"topic":2497,"figure":2498,"authors":2499,"venue":2500,"links":2501,"highlights":2504},"A New Probabilistic Model for Top-k Ranking Problem",[729],"\u002Fimage\u002FTop_k_CPS.png",[169,64,653,654],{"name":796,"year":2489,"link":7},[2502],{"name":209,"link":2503},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fabs\u002F10.1145\u002F2396761.2398681",[2505],{"name":7,"link":7},{"title":2507,"selected":195,"topic":2508,"figure":2509,"authors":2510,"venue":2511,"links":2512,"highlights":2515},"Top-k Learning to Rank: Labeling, Ranking and Evaluation",[729],"\u002Fimage\u002FFocusedNet.png",[169,653,64,654],{"name":863,"year":2489,"link":7},[2513],{"name":209,"link":2514},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fabs\u002F10.1145\u002F2348283.2348384",[2516],{"name":2517,"link":2518},"Best Student Paper Awards","https:\u002F\u002Fsigir.org\u002Fawards\u002Fbest-student-paper-awards\u002F",{"title":2520,"topic":2521,"figure":2522,"authors":2523,"venue":2526,"links":2527,"highlights":2530},"Exploring and Exploiting Proximity Statistic for Information Retrieval Model",[729],"\u002Fimage\u002FBM25PF.png",[172,2524,653,64,654,2525],"Yuanhai Xue","Xiaoming Yu",{"name":1417,"year":2489,"link":7},[2528],{"name":209,"link":2529},"https:\u002F\u002Flink.springer.com\u002Fchapter\u002F10.1007\u002F978-3-642-35341-3_1",[2531],{"name":7,"link":7},{"title":2533,"selected":195,"topic":2534,"figure":2535,"authors":2536,"venue":2538,"links":2539,"highlights":2542},"Statistical Consistency of Ranking Methods in a Rank-differentiable Probability Space",[729,773],"\u002Fimage\u002FRDPS.png",[64,653,654,2537],"Tie-Yan Liu",{"name":594,"year":2489,"link":7},[2540],{"name":209,"link":2541},"https:\u002F\u002Fproceedings.neurips.cc\u002Fpaper\u002F2012\u002Ffile\u002F3435c378bb76d4357324dd7e69f3cd18-Paper.pdf",[2543],{"name":7,"link":7},{"title":2545,"selected":195,"topic":2546,"figure":2547,"authors":2548,"venue":2550,"links":2552,"highlights":2555},"Generalization Analysis of Listwise Learning-to-rank Algorithms",[729,773],"\u002Fimage\u002FGeneralization_Analysis.png",[64,2537,778,2549],"Hang Li",{"name":514,"year":2551,"link":7},2009,[2553],{"name":209,"link":2554},"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002Fabs\u002F10.1145\u002F1553374.1553449",[2556],{"name":7,"link":7},{"title":2558,"topic":2559,"figure":2560,"authors":2561,"venue":2563,"links":2564,"highlights":2567},"Ranking Measures and Loss Functions in Learning to Rank",[729,773],"\u002Fimage\u002FRanking_Measures.png",[2562,2537,64,778,2549],"Wei Chen",{"name":594,"year":2551,"link":7},[2565],{"name":209,"link":2566},"https:\u002F\u002Fproceedings.neurips.cc\u002Fpaper\u002F2009\u002Ffile\u002F2f55707d4193dc27118a0f19a1985716-Paper.pdf",[2568],{"name":7,"link":7},{"title":2570,"selected":195,"topic":2571,"figure":2572,"authors":2573,"venue":2574,"links":2576,"highlights":2579},"Query-level Stability and Generalization in Learning to Rank",[729,773],"\u002Fimage\u002FIRSVM.png",[64,2537,778,2549],{"name":514,"year":2575,"link":7},2008,[2577],{"name":209,"link":2578},"http:\u002F\u002Fmachinelearning.org\u002Farchive\u002Ficml2008\u002Fpapers\u002F179.pdf",[2580],{"name":7,"link":7},"content:data:publications.yaml","Publications","data\u002Fpublications.yaml","data\u002Fpublications",{"_path":2586,"_dir":58,"_draft":6,"_partial":6,"_locale":7,"projects":2587,"_id":2616,"_type":183,"title":2617,"_source":52,"_file":2618,"_stem":2619,"_extension":183},"\u002Fdata\u002Fprojects",[2588,2597],{"title":2589,"figure":2590,"authors":2591,"links":2595},"Drug The Whole Genome","\u002Fimage\u002Fscreening.png",[75,106,2592,71,89,102,221,147,226,227,228,230,231,2593,2594,64],"Jiaxin Tan","Chuangye Ye","Wei Zhang",[2596],{"name":245,"link":249},{"title":2598,"figure":2599,"authors":2600,"links":2603,"highlights":2612},"AIRFold","\u002Fimage\u002Fpsp_sm.gif",[71,150,589,588,75,2601,2602,102,64],"Keyue Qiu","Han Tang",[2604,2606,2609],{"name":245,"link":2605},"\u002Fproject\u002Fairfold",{"name":2607,"link":2608},"Official News","https:\u002F\u002Fair.tsinghua.edu.cn\u002Finfo\u002F1007\u002F1807.htm",{"name":2610,"link":2611},"QbitAI Interview","https:\u002F\u002Fwww.qbitai.com\u002F2022\u002F09\u002F37783.html",[2613],{"name":2614,"link":2615},"Ranked first in the CAMEO 3D Structure Prediction Challenge","https:\u002F\u002Fwww.cameo3d.org\u002Fmodeling\u002Ftargets\u002F1-month\u002F?to_date=2022-08-20","content:data:projects.yaml","Projects","data\u002Fprojects.yaml","data\u002Fprojects",{"_path":2621,"_dir":58,"_draft":6,"_partial":6,"_locale":7,"authors":2622,"_id":2722,"_type":183,"title":2723,"_source":52,"_file":2724,"_stem":2725,"_extension":183},"\u002Fdata\u002Fauthors",{"Alberto Ciccia":2623,"Anqi Shao":2624,"Ba Long":2625,"Bo Cheng":2626,"Bo Qiang":2627,"Bowen Gao":107,"Changying Hao":2628,"Chaosheng Fan":2629,"ChengXiang Zhai":2630,"Chenggang Wu":2631,"Chenyang Hong":2632,"Dawei Yin":2633,"Dingming Wu":2634,"Eric Xing":2635,"Fei Sun":2636,"Fei Xiao":2637,"Gao Sheng":2638,"Haichuan Tan":103,"Hainan Zhang":179,"Hang Li":2639,"Hao Zhou":2640,"Haolan Zhan":2641,"Haoran Xu":2642,"Hongshen Chen":2643,"Huang Xuanjing":2644,"Huanhuan Cao":2645,"Huawei Shen":2646,"Jeff Huang":2647,"Ji-Rong Wen":2648,"Jia Zhang":2649,"Jiafeng Guo":2650,"JianPeng Hou":2651,"Jingjing Gong":2652,"Jingjing Liu":2653,"Jirong Wen":2648,"Jun Xu":2654,"Kang Liu":2655,"Lei Shen":2656,"Liang Pang":176,"Liang Peng":176,"Linfang Hou":2657,"Liu Yang":2658,"Lixin Su":2659,"Long Xia":2660,"Minkai Xu":2661,"Minsi Lu":2662,"Minsi Ren":2663,"Pan Du":2664,"Pen-Chung Yew":2665,"Piji Li":2666,"Qingfeng Lan":2667,"Qingyao Ai":2668,"Ruibin Xiong":2669,"Ruqing Zhang":2670,"Sheng Gao":2671,"Shengxian Wan":2672,"Shentong Mo":2673,"Shikun Feng":144,"Shuai Zhao":2674,"Shuchang Tao":2675,"Shuzi Niu":170,"Sihao Yu":2676,"Tie-Yan Liu":2677,"Wanqing Cui":2678,"Wei Chen":2679,"Wei Zeng":2680,"Wei-Ying Ma":2681,"Wei-ying Ma":2681,"Weipeng Yan":2682,"Weizhi Ma":2683,"Wenhao Huang":2684,"Wolfgang Nejdl":2685,"Xi Fu":2686,"Xiangru Tang":2687,"Xiaobing Feng":2688,"Xiaofei Zhu":2689,"Xiaohui Yan":2690,"Xiaoming Sun":2691,"Xiaoming Yu":2692,"Xin Hong":72,"Xu Wang":2693,"Xueqi Cheng":2694,"Ya-Qin Zhang":2695,"Yadi Lao":107,"Yadong Zhu":173,"Yan Wang":2696,"Yan Xiao":2697,"Yanquan Zhou":2698,"Yanyan Lan":65,"Yanyan Zou":2699,"Yimeng Chen":2700,"Yinjun Jia":76,"Yinqiong Cai":2701,"Yixin Fan":2702,"Yixing Fan":2703,"Yizhen Chen":2704,"Yongjun Bao":2705,"Yuanhai Xue":2706,"Yue Fang":2707,"Yue Feng":2708,"Yunchang Zhu":2709,"Yunji Chen":2710,"Yuxuan Song":2711,"Yuyan Ni":99,"Zeng Wei":2712,"Zhaohui Li":2713,"Zhe Wang":2714,"Zheng Wang":2715,"Zhi-Ming Ma":2716,"Zhihao Fan":2717,"Zhiming Ma":2716,"Zhiqiang Shen":2718,"Zhongyu Wei":2719,"Zhuoye Ding":2720,"Zizhen Wang":2721},"https:\u002F\u002Fscholar.google.co.jp\u002Fcitations?user=8zeIWAEAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fscholar.google.co.jp\u002Fcitations?user=QNjKrEkAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=oXpIT2QAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fscholar.google.co.jp\u002Fcitations?user=C57XAcEAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fscholar.google.com\u002Fcitations?hl=en&user=7FQInvgAAAAJ","https:\u002F\u002Fdl.acm.org\u002Fprofile\u002F99659589827","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=bydF2IkAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=YU-baPIAAAAJ","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=EbGAcnUAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=B5G-yjUAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fwww.yindawei.com\u002F","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=oRbQlsEAAAAJ","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=5pKTRxEAAAAJ&hl=zh-CN&oi=sra","http:\u002F\u002Fofey.me\u002F","https:\u002F\u002Faclanthology.org\u002Fpeople\u002Ff\u002Ffei-xiao\u002F","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=V1q9QpgAAAAJ","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=nTl5mSwAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fzhouh.github.io\u002F","https:\u002F\u002Fscholar.google.com\u002Fcitations?hl=zh-CN&user=nZc5CU4AAAAJ&view_op=list_works&sortby=pubdate","https:\u002F\u002Faclanthology.org\u002Fpeople\u002Fh\u002Fhaoran-xu\u002F","https:\u002F\u002Fwww.chenhongshen.com\u002F","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=RGsMgZA4H78C","https:\u002F\u002Fdblp.org\u002Fpid\u002F48\u002F5943.html","http:\u002F\u002Fwww.ict.cas.cn\u002Fsourcedb_2018_ict_cas\u002Fcn\u002Fjssrck\u002F201402\u002Ft20140221_4037648.html","https:\u002F\u002Fengineering.tamu.edu\u002Fcse\u002Fprofiles\u002Fhuang-jeff.html","https:\u002F\u002Fgsai.ruc.edu.cn\u002Fenglish\u002Fjrwen","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=ElUqcbEAAAAJ","http:\u002F\u002Fwww.bigdatalab.ac.cn\u002Fgjf\u002F","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=2Sp3OuMAAAAJ","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=MayCLqYAAAAJ&hl=en","https:\u002F\u002F0-scholar-google-com.brum.beds.ac.uk\u002Fcitations?user=BzJ_GboAAAAJ&hl=en","https:\u002F\u002Fgsai.ruc.edu.cn\u002F~junxu","https:\u002F\u002Fscholar.google.co.jp\u002Fcitations?user=DtZCfl0AAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=pU8oCuIAAAAJ&hl=en&oi=sra","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=UYbdhvgAAAAJ&hl=en&oi=sra","https:\u002F\u002Fsites.google.com\u002Fsite\u002Flyangwww\u002F","https:\u002F\u002Flixinsu.github.io\u002F","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=NRwerBAAAAAJ&hl=en","https:\u002F\u002Fminkaixu.com\u002F","https:\u002F\u002Flms19.github.io\u002F","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=SodlECMAAAAJ&hl=en","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=huum220AAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=tTFUl48AAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=88ZlyicAAAAJ","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=jKD9jpoAAAAJ","http:\u002F\u002Fwww.thuir.cn\u002Fgroup\u002F~aiqy\u002F","https:\u002F\u002Fscholar.google.co.jp\u002Fcitations?user=P3GLUqQAAAAJ&hl=zh-CN","https:\u002F\u002Fdaqingchong.github.io\u002F","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=V1q9QpgAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=ue3ca0AAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=6aYncPAAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Faclanthology.org\u002Fpeople\u002Fs\u002Fshuai-zhao\u002F","https:\u002F\u002Ftaoshuchang.github.io\u002F","https:\u002F\u002Fdl.acm.org\u002Fprofile\u002F99659281344","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=Nh832fgAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fdblp.org\u002Fpid\u002F260\u002F2159.html","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=9kcYIgwAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fieeexplore.ieee.org\u002Fauthor\u002F37087101788","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=SToCbu8AAAAJ&hl=en","https:\u002F\u002Fdblp.uni-trier.de\u002Fpid\u002F216\u002F8297.html","https:\u002F\u002Fscholar.google.co.jp\u002Fcitations?user=FO3lHi4AAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fscholar.google.co.jp\u002Fcitations?user=OdE3MsQAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=LC62bdYAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fscholar.google.co.jp\u002Fcitations?user=j6fDfDIAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=gGcRkpYAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=XAJAiZEAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=OgZPm2MAAAAJ","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=KZuRKHsAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=WKpSlhQAAAAJ&hl=en&oi=sra","https:\u002F\u002Flink.springer.com\u002Fsearch?dc.creator=Xiaoming%20Yu","https:\u002F\u002Fscholar.google.co.jp\u002Fcitations?user=LdtcZ7QAAAAJ&hl=zh-CN&oi=sra","http:\u002F\u002Fwww.ict.cas.cn\u002Fsourcedb_2018_ict_cas\u002Fcn\u002Fjssrck\u002F200909\u002Ft20090917_2496598.html","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=mDOMfxIAAAAJ&hl=en","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=L6viCbQAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fscholar.google.co.jp\u002Fcitations?user=8iXtpTgAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Faclanthology.org\u002Fpeople\u002Fy\u002Fyanquan-zhou\u002F","https:\u002F\u002Faclanthology.org\u002Fpeople\u002Fy\u002Fyanyan-zou\u002F","https:\u002F\u002Fbeastlyprime.github.io\u002F2022\u002F06\u002Fwelcome-about-me\u002F","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=kZCdJZQAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=w5kGcUsAAAAJ&hl=en&oi=sra","https:\u002F\u002Ffaneshion.github.io\u002F","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=dnZwP6YAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=OSqoLFAAAAAJ&hl=zh-CN","https:\u002F\u002Flink.springer.com\u002Fsearch?dc.creator=Yuanhai%20Xue","https:\u002F\u002Faclanthology.org\u002Fpeople\u002Fy\u002Fyue-fang\u002F","https:\u002F\u002Ffengyue-leah.github.io\u002F","https:\u002F\u002Fdblp.org\u002Fpid\u002F266\u002F1504.html","http:\u002F\u002Fnovel.ict.ac.cn\u002Fychen\u002F","https:\u002F\u002Fyuxuansong.com\u002F","https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Fzheng-wei-60623069\u002F?originalSubdomain=cn","http:\u002F\u002Fzhaohuilee.com\u002F","https:\u002F\u002Fzhexwang.github.io\u002F","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=705qVrYAAAAJ","http:\u002F\u002Fhomepage.amss.ac.cn\u002Fresearch\u002FhomePage\u002F8eb59241e2e74d828fb84eec0efadba5\u002FmyHomePage.html","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=xfqnSacAAAAJ","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=DGr0fVoAAAAJ&hl=zh-CN&oi=sra","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=AjLDxxgAAAAJ","https:\u002F\u002Fdatascience.jd.com\u002Fpage\u002FZhuoyeDing.html","https:\u002F\u002Fscholar.google.com\u002Fcitations?user=pK9sS0EAAAAJ&hl=en&oi=sra","content:data:authors.yaml","Authors","data\u002Fauthors.yaml","data\u002Fauthors",1776485711294]