{"id":"https://openalex.org/W4224310713","doi":"https://doi.org/10.1145/3485447.3512176","title":"Multimodal Continual Graph Learning with Neural Architecture Search","display_name":"Multimodal Continual Graph Learning with Neural Architecture Search","publication_year":2022,"publication_date":"2022-04-25","ids":{"openalex":"https://openalex.org/W4224310713","doi":"https://doi.org/10.1145/3485447.3512176"},"language":"en","primary_location":{"id":"doi:10.1145/3485447.3512176","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3485447.3512176","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3485447.3512176","source":{"id":"https://openalex.org/S4363608783","display_name":"Proceedings of the ACM Web Conference 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2022","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3485447.3512176","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074199725","display_name":"Jie Cai","orcid":"https://orcid.org/0000-0003-2191-8585"},"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":"Jie Cai","raw_affiliation_strings":["Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100757553","display_name":"Xin Wang","orcid":"https://orcid.org/0000-0001-9448-7689"},"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":"Xin Wang","raw_affiliation_strings":["Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064180153","display_name":"Chaoyu Guan","orcid":"https://orcid.org/0000-0001-9617-1653"},"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":"Chaoyu Guan","raw_affiliation_strings":["Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085770866","display_name":"Yateng Tang","orcid":"https://orcid.org/0009-0007-4190-227X"},"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":"Yateng Tang","raw_affiliation_strings":["Wechat, Tencent Inc., China"],"affiliations":[{"raw_affiliation_string":"Wechat, Tencent Inc., China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038610034","display_name":"Jin Xu","orcid":"https://orcid.org/0000-0001-6738-9979"},"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":"Jin Xu","raw_affiliation_strings":["Wechat, Tencent Inc., China"],"affiliations":[{"raw_affiliation_string":"Wechat, Tencent Inc., China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112239242","display_name":"Bin Zhong","orcid":null},"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":"Bin Zhong","raw_affiliation_strings":["Wechat, Tencent Inc., China"],"affiliations":[{"raw_affiliation_string":"Wechat, Tencent Inc., China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100339293","display_name":"Wenwu Zhu","orcid":"https://orcid.org/0000-0003-2236-9290"},"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":"Wenwu Zhu","raw_affiliation_strings":["Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5074199725"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":2.7249,"has_fulltext":true,"cited_by_count":27,"citation_normalized_percentile":{"value":0.91885732,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1292","last_page":"1300"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9976000189781189,"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"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9976000189781189,"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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9952999949455261,"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"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9865999817848206,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.7525837421417236},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.57970130443573},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5773882865905762},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5397009253501892},{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.4818788170814514},{"id":"https://openalex.org/keywords/multimodal-learning","display_name":"Multimodal learning","score":0.4536052644252777},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.44299840927124023},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.4268404245376587},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.36090558767318726},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3305560350418091}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7525837421417236},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.57970130443573},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5773882865905762},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5397009253501892},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.4818788170814514},{"id":"https://openalex.org/C2780660688","wikidata":"https://www.wikidata.org/wiki/Q25052564","display_name":"Multimodal learning","level":2,"score":0.4536052644252777},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.44299840927124023},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.4268404245376587},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.36090558767318726},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3305560350418091},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3485447.3512176","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3485447.3512176","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3485447.3512176","source":{"id":"https://openalex.org/S4363608783","display_name":"Proceedings of the ACM Web Conference 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2022","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3485447.3512176","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3485447.3512176","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3485447.3512176","source":{"id":"https://openalex.org/S4363608783","display_name":"Proceedings of the ACM Web Conference 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2022","raw_type":"proceedings-article"},"sustainable_development_goals":[],"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/G119957897","display_name":null,"funder_award_id":"62102222","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1614471940","display_name":null,"funder_award_id":"2020AAA0","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program 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/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/G3720940119","display_name":null,"funder_award_id":"2020AAA0106300","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5848258319","display_name":null,"funder_award_id":"0 and","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"}],"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":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4224310713.pdf","grobid_xml":"https://content.openalex.org/works/W4224310713.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W1518233497","https://openalex.org/W1981974552","https://openalex.org/W2460144244","https://openalex.org/W2560647685","https://openalex.org/W2584535601","https://openalex.org/W2907492528","https://openalex.org/W2952542841","https://openalex.org/W2963588172","https://openalex.org/W2979826702","https://openalex.org/W2982108874","https://openalex.org/W3024534448","https://openalex.org/W3030364939","https://openalex.org/W3033585170","https://openalex.org/W3034723893","https://openalex.org/W3034943799","https://openalex.org/W3082291914","https://openalex.org/W3087775916","https://openalex.org/W3098366174","https://openalex.org/W3105297929","https://openalex.org/W3127228978","https://openalex.org/W3167098825","https://openalex.org/W3175546444","https://openalex.org/W4205324649","https://openalex.org/W4297971002"],"related_works":["https://openalex.org/W4389505417","https://openalex.org/W2962931510","https://openalex.org/W4380551887","https://openalex.org/W4285159263","https://openalex.org/W2904518532","https://openalex.org/W4280529741","https://openalex.org/W4293919860","https://openalex.org/W2963650472","https://openalex.org/W4387634401","https://openalex.org/W4401552326"],"abstract_inverted_index":{"Continual":[0,121],"graph":[1,33,58,67,88,106,240],"learning":[2,34,68,89],"is":[3,78,93,211,220],"rapidly":[4],"emerging":[5],"as":[6,17,46,48],"an":[7],"important":[8,225,265],"role":[9],"in":[10,55,104,112,221,267],"a":[11,117,182],"variety":[12],"of":[13,188,223,246],"real-world":[14,237],"applications":[15],"such":[16],"online":[18],"product":[19],"recommendation":[20],"systems":[21],"and":[22,43,60,90,133,155,193,218,258],"social":[23,153],"media.":[24],"While":[25],"achieving":[26],"great":[27,74],"success,":[28],"existing":[29],"works":[30],"on":[31],"continual":[32,66,87,105,239],"ignore":[35],"the":[36,49,56,83,101,130,134,162,175,228,244,247,256,269],"information":[37,53,85,154,157,226],"from":[38,227],"multiple":[39],"modalities":[40],"(e.g.,":[41],"visual":[42],"textual":[44],"features)":[45],"well":[47],"rich":[50],"dynamic":[51],"structural":[52],"hidden":[54],"ever-changing":[57],"data":[59],"evolving":[61,70],"tasks.":[62,200,230],"However,":[63],"considering":[64],"multimodal":[65,84,156,163,238],"with":[69,185,205],"topological":[71],"structures":[72],"poses":[73],"challenges:":[75],"i)":[76],"it":[77,92],"unclear":[79],"how":[80],"to":[81,95,160,170,213,242],"incorporate":[82],"into":[86,158],"ii)":[91],"nontrivial":[94],"design":[96],"models":[97],"that":[98,254],"can":[99],"capture":[100],"structure-evolving":[102],"dynamics":[103],"learning.":[107],"To":[108,144],"tackle":[109],"these":[110],"challenges,":[111],"this":[113],"paper":[114],"we":[115],"propose":[116],"novel":[118],"Multimodal":[119,139],"Structure-evolving":[120],"Graph":[122,140],"Learning":[123],"(MSCGL)":[124],"model,":[125],"which":[126],"continually":[127,168],"learns":[128],"both":[129,255],"model":[131,150,180,270],"architecture":[132],"corresponding":[135],"parameters":[136],"for":[137,167],"Adaptive":[138],"Neural":[141,189],"Network":[142],"(AdaMGNN).":[143],"be":[145],"concrete,":[146],"our":[147,178],"proposed":[148,248],"MSCGL":[149,179,249],"simultaneously":[151],"takes":[152],"account":[159],"build":[161],"graphs.":[164],"In":[165],"order":[166],"adapting":[169],"new":[171,183],"tasks":[172,263],"without":[173],"forgetting":[174],"old":[176],"ones,":[177],"explores":[181],"strategy":[184],"joint":[186],"optimization":[187],"Architecture":[190],"Search":[191],"(NAS)":[192],"Group":[194],"Sparse":[195],"Regularization":[196],"(GSR)":[197],"across":[198,261],"different":[199,262],"These":[201],"two":[202,236],"parts":[203],"interact":[204],"each":[206],"other":[207],"reciprocally,":[208],"where":[209],"NAS":[210],"expected":[212],"explore":[214],"more":[215],"promising":[216],"architectures":[217,257],"GSR":[219],"charge":[222],"preserving":[224],"previous":[229],"We":[231],"conduct":[232],"extensive":[233],"experiments":[234,252],"over":[235],"scenarios":[241],"demonstrate":[243],"superiority":[245],"model.":[250],"Empirical":[251],"indicate":[253],"weight":[259],"sharing":[260],"play":[264],"roles":[266],"affecting":[268],"performances.":[271]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":6}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}