{"id":"https://openalex.org/W3190020173","doi":"https://doi.org/10.24963/ijcai.2021/309","title":"Learning Attributed Graph Representation with Communicative Message Passing Transformer","display_name":"Learning Attributed Graph Representation with Communicative Message Passing Transformer","publication_year":2021,"publication_date":"2021-08-01","ids":{"openalex":"https://openalex.org/W3190020173","doi":"https://doi.org/10.24963/ijcai.2021/309","mag":"3190020173"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2021/309","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2021/309","pdf_url":"https://www.ijcai.org/proceedings/2021/0309.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2021/0309.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100689463","display_name":"Jianwen Chen","orcid":"https://orcid.org/0000-0001-7999-2070"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianwen Chen","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-sen University"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075817762","display_name":"Shuangjia Zheng","orcid":"https://orcid.org/0000-0001-9747-4285"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuangjia Zheng","raw_affiliation_strings":["Galixir Technologies Ltd, Beijing","School of Computer Science and Engineering, Sun Yat-sen University"],"affiliations":[{"raw_affiliation_string":"Galixir Technologies Ltd, Beijing","institution_ids":[]},{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100631937","display_name":"Ying Song","orcid":"https://orcid.org/0000-0002-4685-7267"},"institutions":[{"id":"https://openalex.org/I142974352","display_name":"National Sun Yat-sen University","ror":"https://ror.org/00mjawt10","country_code":"TW","type":"education","lineage":["https://openalex.org/I142974352"]},{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN","TW"],"is_corresponding":false,"raw_author_name":"Ying Song","raw_affiliation_strings":["School of System Science and Engineering, Sun Yat-sen University","[School of System Science and Engineering, Sun Yat-Sen University]"],"affiliations":[{"raw_affiliation_string":"School of System Science and Engineering, Sun Yat-sen University","institution_ids":["https://openalex.org/I157773358","https://openalex.org/I142974352"]},{"raw_affiliation_string":"[School of System Science and Engineering, Sun Yat-Sen University]","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015329746","display_name":"Jiahua Rao","orcid":"https://orcid.org/0000-0002-6840-8198"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahua Rao","raw_affiliation_strings":["Galixir Technologies Ltd, Beijing","School of Computer Science and Engineering, Sun Yat-sen University"],"affiliations":[{"raw_affiliation_string":"Galixir Technologies Ltd, Beijing","institution_ids":[]},{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023539493","display_name":"Yuedong Yang","orcid":"https://orcid.org/0000-0002-6782-2813"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuedong Yang","raw_affiliation_strings":["Key Laboratory of Machine Intelligence and Advanced Computing, Sun Yat-sen University","School of Computer Science and Engineering, Sun Yat-sen University"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Intelligence and Advanced Computing, Sun Yat-sen University","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100689463"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":4.5241,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.95069979,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2242","last_page":"2248"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7411692142486572},{"id":"https://openalex.org/keywords/message-passing","display_name":"Message passing","score":0.6393354535102844},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5896531343460083},{"id":"https://openalex.org/keywords/inductive-bias","display_name":"Inductive bias","score":0.5016696453094482},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.49405935406684875},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4833900034427643},{"id":"https://openalex.org/keywords/molecular-graph","display_name":"Molecular graph","score":0.4652123749256134},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.44895848631858826},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.445330947637558},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3572177588939667},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.2654263377189636},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.13179093599319458}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7411692142486572},{"id":"https://openalex.org/C854659","wikidata":"https://www.wikidata.org/wiki/Q1859284","display_name":"Message passing","level":2,"score":0.6393354535102844},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5896531343460083},{"id":"https://openalex.org/C197352929","wikidata":"https://www.wikidata.org/wiki/Q1074074","display_name":"Inductive bias","level":4,"score":0.5016696453094482},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.49405935406684875},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4833900034427643},{"id":"https://openalex.org/C2780022179","wikidata":"https://www.wikidata.org/wiki/Q1986794","display_name":"Molecular graph","level":3,"score":0.4652123749256134},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.44895848631858826},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.445330947637558},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3572177588939667},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.2654263377189636},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.13179093599319458},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.24963/ijcai.2021/309","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2021/309","pdf_url":"https://www.ijcai.org/proceedings/2021/0309.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},{"id":"pmh:oai:research-repository.griffith.edu.au:10072/413941","is_oa":false,"landing_page_url":"http://hdl.handle.net/10072/413941","pdf_url":null,"source":{"id":"https://openalex.org/S4306402548","display_name":"Griffith Research Online (Griffith University, Queensland, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11701301","host_organization_name":"Griffith University","host_organization_lineage":["https://openalex.org/I11701301"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference output"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2021/309","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2021/309","pdf_url":"https://www.ijcai.org/proceedings/2021/0309.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.44999998807907104}],"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/G1477544716","display_name":null,"funder_award_id":"Guangdong","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/G2602136225","display_name":null,"funder_award_id":"2018B01","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/G5108781970","display_name":null,"funder_award_id":"61772566","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5178878423","display_name":null,"funder_award_id":"2020YFB0204803","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6069953956","display_name":null,"funder_award_id":"2018B0101","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6346021793","display_name":null,"funder_award_id":"2019B020228001","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"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3190020173.pdf","grobid_xml":"https://content.openalex.org/works/W3190020173.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W1738019091","https://openalex.org/W2290847742","https://openalex.org/W2594183968","https://openalex.org/W2606780347","https://openalex.org/W2785720803","https://openalex.org/W2962876364","https://openalex.org/W2964051675","https://openalex.org/W2964113829","https://openalex.org/W2964380716","https://openalex.org/W2968734407","https://openalex.org/W2972693922","https://openalex.org/W2986232138","https://openalex.org/W2987522751","https://openalex.org/W3000478925","https://openalex.org/W3007488165","https://openalex.org/W3014550317","https://openalex.org/W3034516664","https://openalex.org/W3034772996","https://openalex.org/W3095883070","https://openalex.org/W3198974858","https://openalex.org/W4286715520","https://openalex.org/W4297733535","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W1810370127","https://openalex.org/W2978729728","https://openalex.org/W1594946127","https://openalex.org/W4288966080","https://openalex.org/W3034516664","https://openalex.org/W4297817821","https://openalex.org/W3100116469","https://openalex.org/W3041877813","https://openalex.org/W3037162414","https://openalex.org/W2798932700"],"abstract_inverted_index":{"Constructing":[0],"appropriate":[1],"representations":[2],"of":[3,9],"molecules":[4,23],"lies":[5],"at":[6],"the":[7,72,90,104,108,128,135,143],"core":[8],"numerous":[10],"tasks":[11],"such":[12],"as":[13,24,115],"material":[14],"science,":[15],"chemistry,":[16],"and":[17,27,57,100,133,163],"drug":[18],"designs.":[19],"Recent":[20],"researches":[21],"abstract":[22],"attributed":[25],"graphs":[26],"employ":[28],"graph":[29,44,61,92,129],"neural":[30,86],"networks":[31],"(GNN)":[32],"for":[33],"molecular":[34,43,91],"representation":[35,93,177],"learning,":[36],"which":[37],"have":[38],"made":[39],"remarkable":[40],"achievements":[41],"in":[42],"modeling.":[45],"Albeit":[46],"powerful,":[47],"current":[48],"models":[49],"either":[50],"are":[51],"based":[52,102],"on":[53,65,103,151,156],"local":[54],"aggregation":[55],"operations":[56],"thus":[58],"miss":[59],"higher-order":[60],"properties":[62],"or":[63],"focus":[64],"only":[66],"node":[67],"information":[68],"without":[69],"fully":[70,117],"using":[71],"edge":[73],"information.":[74],"For":[75],"this":[76],"sake,":[77],"we":[78,120],"propose":[79],"a":[80,116,122,175],"Communicative":[81],"Message":[82],"Passing":[83],"Transformer":[84,105],"(CoMPT)":[85],"network":[87],"to":[88,126],"improve":[89],"by":[94,180],"reinforcing":[95],"message":[96,123,136],"interactions":[97],"between":[98],"nodes":[99],"edges":[101],"architecture.":[106],"Unlike":[107],"previous":[109],"transformer-style":[110],"GNNs":[111],"that":[112,142],"treat":[113],"molecule":[114],"connected":[118],"graph,":[119],"introduce":[121],"diffusion":[124],"mechanism":[125],"leverage":[127],"connectivity":[130],"inductive":[131],"bias":[132],"reduce":[134],"enrichment":[137],"explosion.":[138],"Extensive":[139],"experiments":[140],"demonstrated":[141],"proposed":[144],"model":[145],"obtained":[146],"superior":[147],"performances":[148],"(around":[149],"4%":[150],"average)":[152],"against":[153],"state-of-the-art":[154],"baselines":[155],"seven":[157],"chemical":[158,165],"property":[159],"datasets":[160,167],"(graph-level":[161],"tasks)":[162],"two":[164],"shift":[166],"(node-level":[168],"tasks).":[169],"Further":[170],"visualization":[171],"studies":[172],"also":[173],"indicated":[174],"better":[176],"capacity":[178],"achieved":[179],"our":[181],"model.":[182]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":2}],"updated_date":"2026-03-28T08:17:26.163206","created_date":"2021-08-16T00:00:00"}
