{"id":"https://openalex.org/W7207549765","doi":"https://doi.org/10.48550/arxiv.2609.02519","title":"Spectral Initialization and Scheduled Graph Smoothness for Uncertain Knowledge Graph Completion","display_name":"Spectral Initialization and Scheduled Graph Smoothness for Uncertain Knowledge Graph Completion","publication_year":2026,"publication_date":"2026-09-02","ids":{"openalex":"https://openalex.org/W7207549765","doi":"https://doi.org/10.48550/arxiv.2609.02519"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2609.02519","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.02519","pdf_url":"https://arxiv.org/pdf/2609.02519","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2609.02519","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065477478","display_name":"Md Abrar Jahin","orcid":"https://orcid.org/0000-0002-1623-3859","observed_orcids":["https://orcid.org/0000-0002-1623-3859"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jahin, Md Abrar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124939865","display_name":"Taufikur Rahman Fuad","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I59805279","display_name":"Islamic University of Technology","ror":"https://ror.org/057gnqw22","country_code":"BD","type":"education","lineage":["https://openalex.org/I59805279"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Fuad, Taufikur Rahman","raw_affiliation_strings":["Islamic University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Islamic University of Technology","institution_ids":["https://openalex.org/I59805279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127371743","display_name":"Jay Pujara","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pujara, Jay","raw_affiliation_strings":["University of Southern California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Southern California","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089542402","display_name":"Craig A. Knoblock","orcid":"https://orcid.org/0000-0002-6371-4807","observed_orcids":["https://orcid.org/0000-0002-6371-4807"]},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Knoblock, Craig A.","raw_affiliation_strings":["University of Southern California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Southern California","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9994999766349792,"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":0.9994999766349792,"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/T10028","display_name":"Topic Modeling","score":0.00039999998989515007,"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/T10215","display_name":"Semantic Web and Ontologies","score":9.999999747378752e-05,"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/knowledge-graph-completion","display_name":"knowledge graph completion","score":0.9810000061988831},{"id":"https://openalex.org/keywords/confidence-estimation","display_name":"confidence estimation","score":0.753000020980835},{"id":"https://openalex.org/keywords/spectral-initialization","display_name":"spectral initialization","score":0.6320000290870667},{"id":"https://openalex.org/keywords/link-prediction","display_name":"link prediction","score":0.6759999990463257},{"id":"https://openalex.org/keywords/quest","display_name":"quest","score":0.5659999847412109}],"concepts":[{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.6207000017166138},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.6207000017166138},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5979999899864197},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.5321999788284302},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.45669999718666077},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39250001311302185},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.375},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3723999857902527},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.36880001425743103},{"id":"https://openalex.org/C169214877","wikidata":"https://www.wikidata.org/wiki/Q981016","display_name":"Dirichlet distribution","level":3,"score":0.3601999878883362},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.3598000109195709},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34279999136924744},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3001999855041504},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2791999876499176},{"id":"https://openalex.org/C2781020372","wikidata":"https://www.wikidata.org/wiki/Q533093","display_name":"On the fly","level":2,"score":0.2542000114917755},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.25}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2609.02519","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.02519","pdf_url":"https://arxiv.org/pdf/2609.02519","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2609.02519","doi":"https://doi.org/10.48550/arxiv.2609.02519","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2609.02519","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2609.02519","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.02519","pdf_url":"https://arxiv.org/pdf/2609.02519","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7207549765.pdf","grobid_xml":"https://content.openalex.org/works/W7207549765.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4415897909","https://openalex.org/W3149813942","https://openalex.org/W7160826194","https://openalex.org/W4402358749","https://openalex.org/W7162655989","https://openalex.org/W3115640131","https://openalex.org/W4401357435","https://openalex.org/W3014490432","https://openalex.org/W3155038476","https://openalex.org/W4402784462"],"abstract_inverted_index":{"Uncertain":[0],"knowledge":[1,5],"graphs":[2,6],"(UKGs)":[3],"extend":[4],"by":[7],"assigning":[8],"each":[9],"triple":[10],"a":[11,145],"continuous":[12],"confidence":[13,104],"score.":[14],"Since":[15],"most":[16],"possible":[17],"triples":[18],"lack":[19],"observed":[20,132],"confidences,":[21],"recent":[22],"methods":[23,32,117],"rely":[24],"on":[25,109,123,133],"semi-supervised":[26],"learning":[27,60],"to":[28,56,93],"generate":[29],"pseudo-labels.":[30],"These":[31,136],"initialize":[33],"entity":[34,65],"embeddings":[35,66],"without":[36],"using":[37,67],"the":[38,57,68,73,120,124,129],"confidence-weighted":[39,74],"graph,":[40],"discarding":[41],"its":[42],"global":[43],"community":[44,78],"and":[45,79,106,118,154],"hub":[46,80],"structure.":[47],"We":[48],"introduce":[49],"QUEST,":[50],"which":[51],"adds":[52],"no":[53],"trainable":[54],"parameters":[55],"standard":[58],"confidence-distribution":[59],"pipeline.":[61],"First,":[62],"QUEST":[63,85,102],"initializes":[64],"smallest":[69],"non-trivial":[70],"eigenvectors":[71],"of":[72,111],"graph":[75,146],"Laplacian,":[76],"incorporating":[77],"structure":[81],"before":[82],"training.":[83],"Second,":[84],"applies":[86],"an":[87],"unbiased":[88],"mini-batch":[89],"Dirichlet":[90,147],"energy":[91,148],"regularizer":[92,149],"enforce":[94],"early-stage":[95],"structural":[96,141],"consistency.":[97],"On":[98],"two":[99],"UKG":[100,158],"datasets,":[101],"improves":[103],"prediction":[105,108],"link":[107],"six":[110],"eight":[112],"metric-dataset":[113],"pairs":[114],"over":[115],"prior":[116],"matches":[119],"previous":[121],"best":[122],"remaining":[125],"two,":[126],"while":[127],"removing":[128],"instability":[130],"spike":[131],"dense":[134],"graphs.":[135],"results":[137],"indicate":[138],"that":[139],"spectral":[140],"priors":[142],"combined":[143],"with":[144],"improve":[150],"accuracy,":[151],"training":[152],"stability,":[153],"checkpoint":[155],"reliability":[156],"in":[157],"completion.":[159]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-09-04T00:00:00"}