{"id":"https://openalex.org/W3158304688","doi":"https://doi.org/10.1145/3532611","title":"Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution","display_name":"Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution","publication_year":2022,"publication_date":"2022-05-17","ids":{"openalex":"https://openalex.org/W3158304688","doi":"https://doi.org/10.1145/3532611","mag":"3158304688"},"language":"en","primary_location":{"id":"doi:10.1145/3532611","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3532611","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3532611","source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3532611","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047511618","display_name":"Fuxian Li","orcid":"https://orcid.org/0000-0002-9552-3239"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fuxian Li","raw_affiliation_strings":["Beijing National Research Center for Information Science and Technology (BNRist), Department of Electronic Engineering, Tsinghua University, Beijing 100084, China"],"affiliations":[{"raw_affiliation_string":"Beijing National Research Center for Information Science and Technology (BNRist), Department of Electronic Engineering, Tsinghua University, Beijing 100084, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100668035","display_name":"Jie Feng","orcid":"https://orcid.org/0000-0003-3279-7117"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Feng","raw_affiliation_strings":["Beijing National Research Center for Information Science and Technology (BNRist), Department of Electronic Engineering, Tsinghua University, Beijing 100084, China"],"affiliations":[{"raw_affiliation_string":"Beijing National Research Center for Information Science and Technology (BNRist), Department of Electronic Engineering, Tsinghua University, Beijing 100084, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003434396","display_name":"Huan Yan","orcid":"https://orcid.org/0000-0001-9626-5676"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huan Yan","raw_affiliation_strings":["Beijing National Research Center for Information Science and Technology (BNRist), Department of Electronic Engineering, Tsinghua University, Beijing 100084, China"],"affiliations":[{"raw_affiliation_string":"Beijing National Research Center for Information Science and Technology (BNRist), Department of Electronic Engineering, Tsinghua University, Beijing 100084, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018357954","display_name":"Guangyin Jin","orcid":"https://orcid.org/0000-0002-9837-6836"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangyin Jin","raw_affiliation_strings":["College of Systems Engineering, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Systems Engineering, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045825296","display_name":"Fan Yang","orcid":"https://orcid.org/0000-0002-3523-1138"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Yang","raw_affiliation_strings":["Tencent Inc., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tencent Inc., Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101439558","display_name":"Funing Sun","orcid":"https://orcid.org/0000-0002-1388-4541"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Funing Sun","raw_affiliation_strings":["Tencent Inc., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tencent Inc., Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044100655","display_name":"Depeng Jin","orcid":"https://orcid.org/0000-0003-0419-5514"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Depeng Jin","raw_affiliation_strings":["Beijing National Research Center for Information Science and Technology (BNRist), Department of Electronic Engineering, Tsinghua University, Beijing 100084, China"],"affiliations":[{"raw_affiliation_string":"Beijing National Research Center for Information Science and Technology (BNRist), Department of Electronic Engineering, Tsinghua University, Beijing 100084, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100355277","display_name":"Yong Li","orcid":"https://orcid.org/0000-0001-5617-1659"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Li","raw_affiliation_strings":["Beijing National Research Center for Information Science and Technology (BNRist), Department of Electronic Engineering, Tsinghua University, Beijing 100084, China"],"affiliations":[{"raw_affiliation_string":"Beijing National Research Center for Information Science and Technology (BNRist), Department of Electronic Engineering, Tsinghua University, Beijing 100084, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5047511618"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":49.1391,"has_fulltext":true,"cited_by_count":480,"citation_normalized_percentile":{"value":0.99992039,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"17","issue":"1","first_page":"1","last_page":"21"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9850000143051147,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.9835000038146973,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8209435939788818},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7047020196914673},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6579405069351196},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6379293203353882},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5757536292076111},{"id":"https://openalex.org/keywords/dynamic-network-analysis","display_name":"Dynamic network analysis","score":0.46224191784858704},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4372006356716156},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42466384172439575},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4201664626598358},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.41586366295814514},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.383887380361557},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3813381493091583},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.26749956607818604},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.11298823356628418}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8209435939788818},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7047020196914673},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6579405069351196},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6379293203353882},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5757536292076111},{"id":"https://openalex.org/C13540734","wikidata":"https://www.wikidata.org/wiki/Q5318996","display_name":"Dynamic network analysis","level":2,"score":0.46224191784858704},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4372006356716156},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42466384172439575},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4201664626598358},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.41586366295814514},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.383887380361557},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3813381493091583},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.26749956607818604},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.11298823356628418},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3532611","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3532611","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3532611","source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3532611","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3532611","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3532611","source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8100000023841858,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G131200818","display_name":null,"funder_award_id":"U20B2060, U1936217, 61971267, and 61972223","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3188007771","display_name":null,"funder_award_id":"U20B2060","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3710896277","display_name":null,"funder_award_id":"61971267","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3734416573","display_name":null,"funder_award_id":"61972223","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4872662616","display_name":null,"funder_award_id":"U1936217","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5517038434","display_name":null,"funder_award_id":"2020YFB","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G6308271066","display_name":null,"funder_award_id":"2020YFB2104005","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G6867336257","display_name":null,"funder_award_id":"U1936217, 61971267, 61972223","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3158304688.pdf","grobid_xml":"https://content.openalex.org/works/W3158304688.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W2064675550","https://openalex.org/W2069508080","https://openalex.org/W2101491865","https://openalex.org/W2108400301","https://openalex.org/W2112796928","https://openalex.org/W2157331557","https://openalex.org/W2313953460","https://openalex.org/W2519887557","https://openalex.org/W2528639018","https://openalex.org/W2613328025","https://openalex.org/W2626778328","https://openalex.org/W2756203131","https://openalex.org/W2808535700","https://openalex.org/W2896686593","https://openalex.org/W2903871660","https://openalex.org/W2904813135","https://openalex.org/W2904832339","https://openalex.org/W2949888546","https://openalex.org/W2950304420","https://openalex.org/W2950817888","https://openalex.org/W2951927893","https://openalex.org/W2952042565","https://openalex.org/W2953170998","https://openalex.org/W2963124587","https://openalex.org/W2963358464","https://openalex.org/W2963858333","https://openalex.org/W2965341826","https://openalex.org/W2989847038","https://openalex.org/W2996451395","https://openalex.org/W2996847713","https://openalex.org/W2997848713","https://openalex.org/W2998559444","https://openalex.org/W3000386982","https://openalex.org/W3012562343","https://openalex.org/W3028192203","https://openalex.org/W3035580605","https://openalex.org/W3038981236","https://openalex.org/W3080253043","https://openalex.org/W3084616068","https://openalex.org/W3093761440","https://openalex.org/W3103427490","https://openalex.org/W3103720336","https://openalex.org/W3146166473","https://openalex.org/W4241115065","https://openalex.org/W4285667588","https://openalex.org/W4297733535"],"related_works":["https://openalex.org/W2086397253","https://openalex.org/W2133122801","https://openalex.org/W600422426","https://openalex.org/W2007156430","https://openalex.org/W3081478936","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W2785612136","https://openalex.org/W4239306820","https://openalex.org/W2099529706"],"abstract_inverted_index":{"Traffic":[0],"prediction":[1,92],"is":[2,12,65,141],"the":[3,15,37,76,81,116,129,186],"cornerstone":[4],"of":[5,17,40,69,118,164,189],"intelligent":[6,21],"transportation":[7],"system.":[8],"Accurate":[9],"traffic":[10,22,91,206],"forecasting":[11],"essential":[13],"for":[14,32,182,210],"applications":[16],"smart":[18],"cities,":[19],"i.e.,":[20],"management":[23],"and":[24,108,132,175,193,201,213],"urban":[25],"planning.":[26],"Although":[27],"various":[28],"methods":[29,74],"are":[30,54,104,121,153,208,231],"proposed":[31],"spatio-temporal":[33],"modeling,":[34],"they":[35],"ignore":[36],"dynamic":[38,110,119,138,165],"characteristics":[39,111],"correlations":[41],"among":[42,72],"locations":[43],"on":[44,75,218],"road":[45],"network.":[46],"Meanwhile,":[47],"most":[48],"Recurrent":[49,98],"Neural":[50],"Network":[51,99],"based":[52],"works":[53],"not":[55],"efficient":[56],"enough":[57],"due":[58],"to":[59,106,136,155,160,172],"their":[60],"recurrent":[61],"operations.":[62],"Additionally,":[63],"there":[64],"a":[66,89,157,179,197,202],"severe":[67],"lack":[68],"fair":[70,211],"comparison":[71,212],"different":[73],"same":[77],"datasets.":[78],"To":[79],"address":[80],"above":[82],"challenges,":[83],"in":[84],"this":[85],"article,":[86],"we":[87,150,152,177],"propose":[88],"novel":[90],"framework,":[93],"named":[94],"Dynamic":[95],"Graph":[96],"Convolutional":[97],"(DGCRN).":[100],"In":[101],"DGCRN,":[102],"hyper-networks":[103],"designed":[105],"leverage":[107],"extract":[109],"from":[112],"node":[113,130],"attributes,":[114],"while":[115],"parameters":[117],"filters":[120],"generated":[122],"at":[123,167,233],"each":[124,168],"time":[125,169],"step.":[126,170],"We":[127],"filter":[128],"embeddings":[131],"then":[133],"use":[134],"them":[135],"generate":[137],"graph,":[139],"which":[140],"integrated":[142],"with":[143],"pre-defined":[144],"static":[145],"graph.":[146],"As":[147],"far":[148],"as":[149],"know,":[151],"first":[154],"employ":[156,178],"generation":[158],"method":[159],"model":[161,224],"fine":[162],"topology":[163],"graph":[166],"Furthermore,":[171],"enhance":[173],"efficiency":[174],"performance,":[176],"training":[180],"strategy":[181],"DGCRN":[183],"by":[184],"restricting":[185],"iteration":[187],"number":[188],"decoder":[190],"during":[191],"forward":[192],"backward":[194],"propagation.":[195],"Finally,":[196],"reproducible":[198],"standardized":[199],"benchmark":[200],"brand":[203],"new":[204],"representative":[205],"dataset":[207],"opened":[209],"further":[214],"research.":[215],"Extensive":[216],"experiments":[217],"three":[219],"datasets":[220],"demonstrate":[221],"that":[222],"our":[223],"outperforms":[225],"15":[226],"baselines":[227],"consistently.":[228],"Source":[229],"codes":[230],"available":[232],"https://github.com/tsinghua-fib-lab/Traffic-Benchmark":[234],".":[235]},"counts_by_year":[{"year":2026,"cited_by_count":21},{"year":2025,"cited_by_count":179},{"year":2024,"cited_by_count":161},{"year":2023,"cited_by_count":87},{"year":2022,"cited_by_count":28},{"year":2021,"cited_by_count":4}],"updated_date":"2026-04-12T07:58:50.170612","created_date":"2025-10-10T00:00:00"}
