{"id":"https://openalex.org/W7156041176","doi":"https://doi.org/10.1145/3774904.3792497","title":"TGSBM: Transformer-Guided Stochastic Block Model for Link Prediction","display_name":"TGSBM: Transformer-Guided Stochastic Block Model for Link Prediction","publication_year":2026,"publication_date":"2026-04-12","ids":{"openalex":"https://openalex.org/W7156041176","doi":"https://doi.org/10.1145/3774904.3792497"},"language":null,"primary_location":{"id":"doi:10.1145/3774904.3792497","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792497","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2026","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3774904.3792497","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036135101","display_name":"Zhejian Yang","orcid":"https://orcid.org/0000-0002-6980-8062"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhejian Yang","raw_affiliation_strings":["Jilin University, Changchun, Jilin, China"],"raw_orcid":"https://orcid.org/0000-0002-6980-8062","affiliations":[{"raw_affiliation_string":"Jilin University, Changchun, Jilin, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025935227","display_name":"Songwei Zhao","orcid":"https://orcid.org/0000-0001-6149-3214"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Songwei Zhao","raw_affiliation_strings":["Jilin University, Changchun, Jilin, China"],"raw_orcid":"https://orcid.org/0000-0001-6149-3214","affiliations":[{"raw_affiliation_string":"Jilin University, Changchun, Jilin, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048936923","display_name":"Zilin Zhao","orcid":"https://orcid.org/0000-0002-7002-9306"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zilin Zhao","raw_affiliation_strings":["Jilin University, Changchun, Jilin, China"],"raw_orcid":"https://orcid.org/0009-0003-2190-958X","affiliations":[{"raw_affiliation_string":"Jilin University, Changchun, Jilin, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108294333","display_name":"Hechang Chen","orcid":"https://orcid.org/0000-0001-7835-9556"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hechang Chen","raw_affiliation_strings":["Jilin University, Changchun, Jilin, China"],"raw_orcid":"https://orcid.org/0000-0001-7835-9556","affiliations":[{"raw_affiliation_string":"Jilin University, Changchun, Jilin, China","institution_ids":["https://openalex.org/I194450716"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I194450716"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4746","last_page":"4757"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9768999814987183,"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":0.9768999814987183,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.007400000002235174,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.005100000184029341,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/scalability","display_name":"Scalability","score":0.572700023651123},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4925000071525574},{"id":"https://openalex.org/keywords/stochastic-block-model","display_name":"Stochastic block model","score":0.4837000072002411},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.41589999198913574},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.3871999979019165},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3815000057220459},{"id":"https://openalex.org/keywords/quadratic-equation","display_name":"Quadratic equation","score":0.3582000136375427},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.34610000252723694}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7128000259399414},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.572700023651123},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5562999844551086},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4925000071525574},{"id":"https://openalex.org/C2779982251","wikidata":"https://www.wikidata.org/wiki/Q25053762","display_name":"Stochastic block model","level":3,"score":0.4837000072002411},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.41589999198913574},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4108999967575073},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39010000228881836},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3871999979019165},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3815000057220459},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.3582000136375427},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.34610000252723694},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.3400999903678894},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.31619998812675476},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3100000023841858},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29339998960494995},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.2870999872684479},{"id":"https://openalex.org/C2779172887","wikidata":"https://www.wikidata.org/wiki/Q184316","display_name":"PageRank","level":2,"score":0.2757999897003174},{"id":"https://openalex.org/C133079900","wikidata":"https://www.wikidata.org/wiki/Q5155065","display_name":"Community structure","level":2,"score":0.2727999985218048},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C558772884","wikidata":"https://www.wikidata.org/wiki/Q1508564","display_name":"Graph rewriting","level":3,"score":0.26829999685287476},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25859999656677246},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.25519999861717224},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.25519999861717224}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3774904.3792497","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792497","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2026","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3774904.3792497","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792497","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.44781890511512756,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1883408324","https://openalex.org/W1967184357","https://openalex.org/W1993418693","https://openalex.org/W2007444087","https://openalex.org/W2026417691","https://openalex.org/W2029289148","https://openalex.org/W2051638434","https://openalex.org/W2963224548","https://openalex.org/W2963732630","https://openalex.org/W2968890898","https://openalex.org/W3082429057","https://openalex.org/W4214888512","https://openalex.org/W4308488195","https://openalex.org/W4312056373","https://openalex.org/W4388513805","https://openalex.org/W4401863661","https://openalex.org/W4408145169","https://openalex.org/W4409365184","https://openalex.org/W4412605501","https://openalex.org/W4415658227","https://openalex.org/W7133241215"],"related_works":[],"abstract_inverted_index":{"Link":[0],"prediction":[1],"is":[2],"a":[3,85,124,139,181,186],"cornerstone":[4],"of":[5,31,33,93,102],"the":[6,89,99],"Web":[7],"ecosystem,":[8],"powering":[9],"applications":[10],"from":[11],"recommendation":[12],"and":[13,19,35,39,73,119,135,137,172,191],"search":[14],"to":[15,57,168],"knowledge":[16],"graph":[17,53,64],"completion":[18],"collaboration":[20],"forecasting.":[21],"However,":[22],"large-scale":[23,194],"networks":[24,55],"present":[25],"unique":[26],"challenges:":[27],"they":[28],"contain":[29],"hundreds":[30],"thousands":[32],"nodes":[34],"edges":[36],"with":[37,98],"heterogeneous":[38],"overlapping":[40],"community":[41,133,174],"structures":[42],"that":[43,87,115,128,143,184],"evolve":[44],"over":[45,132],"time.":[46],"Existing":[47],"approaches":[48],"face":[49],"notable":[50],"limitations:":[51],"traditional":[52],"neural":[54,125,140],"struggle":[56],"capture":[58],"global":[59,121],"structural":[60],"dependencies,":[61],"while":[62],"recent":[63],"transformers":[65],"achieve":[66],"strong":[67],"performance":[68,158],"but":[69],"incur":[70],"quadratic":[71],"complexity":[72,118],"lack":[74],"interpretable":[75,173],"latent":[76],"structure.":[77],"We":[78],"propose":[79],"TGSBM":[80,106,179],"(Transformer-Guided":[81],"Stochastic":[82,95],"Block":[83,96],"Model),":[84],"framework":[86],"integrates":[88],"principled":[90],"generative":[91,148],"structure":[92],"Overlapping":[94],"Models":[97],"representational":[100],"power":[101],"sparse":[103,113],"Graph":[104],"Transformers.":[105],"comprises":[107],"three":[108],"main":[109],"components:":[110],"(i)":[111],"expander-augmented":[112],"attention":[114],"enables":[116],"near-linear":[117],"efficient":[120],"mixing,":[122],"(ii)":[123],"variational":[126],"encoder":[127],"infers":[129],"structured":[130],"posteriors":[131],"memberships":[134],"strengths,":[136],"(iii)":[138],"edge":[141],"decoder":[142],"reconstructs":[144],"links":[145],"via":[146],"OSBM's":[147],"process,":[149],"preserving":[150],"interpretability.":[151],"Experiments":[152],"across":[153],"diverse":[154],"benchmarks":[155],"demonstrate":[156],"competitive":[157],"(mean":[159],"rank":[160],"1.6":[161],"under":[162],"HeaRT":[163],"protocol),":[164],"superior":[165],"scalability":[166],"(up":[167],"6\u00d7":[169],"faster":[170],"training),":[171],"structures.":[175],"These":[176],"results":[177],"position":[178],"as":[180],"practical":[182],"approach":[183],"strikes":[185],"balance":[187],"between":[188],"accuracy,":[189],"efficiency,":[190],"transparency":[192],"for":[193],"link":[195],"prediction.":[196]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-04-28T00:00:00"}