{"id":"https://openalex.org/W7133487740","doi":"https://doi.org/10.1145/3774904.3792677","title":"VL-KGE: Vision-Language Models Meet Knowledge Graph Embeddings","display_name":"VL-KGE: Vision-Language Models Meet Knowledge Graph Embeddings","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7133487740","doi":"https://doi.org/10.1145/3774904.3792677"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2603.02435","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2603.02435","pdf_url":"https://arxiv.org/pdf/2603.02435","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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"},"type":"article","indexed_in":["arxiv"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2603.02435","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059204263","display_name":"Athanasios Efthymiou","orcid":"https://orcid.org/0000-0001-7163-1115"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Efthymiou, Athanasios","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075331928","display_name":"Stevan Rudinac","orcid":"https://orcid.org/0000-0003-1904-8736"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rudinac, Stevan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081752388","display_name":"Monika Kackovic","orcid":"https://orcid.org/0000-0002-7423-3902"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kackovic, Monika","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018810337","display_name":"Nachoem M. Wijnberg","orcid":"https://orcid.org/0000-0001-8070-8719"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wijnberg, Nachoem","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5070684680","display_name":"Marcel Worring","orcid":"https://orcid.org/0000-0003-4097-4136"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Worring, Marcel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":17.0132,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.98147376,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":97},"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":0.9818000197410583,"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":0.9818000197410583,"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":0.004800000227987766,"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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.00419999985024333,"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/embedding","display_name":"Embedding","score":0.7754999995231628},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.6237000226974487},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.5566999912261963},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4700999855995178},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.4348999857902527},{"id":"https://openalex.org/keywords/statistical-relational-learning","display_name":"Statistical relational learning","score":0.3788999915122986}],"concepts":[{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7754999995231628},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.703000009059906},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.6237000226974487},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.5566999912261963},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4903999865055084},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4700999855995178},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.4348999857902527},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3970000147819519},{"id":"https://openalex.org/C177877439","wikidata":"https://www.wikidata.org/wiki/Q7604413","display_name":"Statistical relational learning","level":3,"score":0.3788999915122986},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.3377000093460083},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3262999951839447},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3237999975681305},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.31769999861717224},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2709999978542328},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.2581999897956848}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2603.02435","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2603.02435","pdf_url":"https://arxiv.org/pdf/2603.02435","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"pmh:oai:dare.uva.nl:publications/6a7b8103-4182-4423-9934-fb4552c83441","is_oa":true,"landing_page_url":"https://handle.uba.uva.nl/personal/pure/en/publications/vlkge-visionlanguage-models-meet-knowledge-graph-embeddings(6a7b8103-4182-4423-9934-fb4552c83441).html","pdf_url":"https://pure.uva.nl/ws/files/328473529/3774904.3792677.pdf","source":{"id":"https://openalex.org/S4306400088","display_name":"UvA-DARE (University of Amsterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887064364","host_organization_name":"University of Amsterdam","host_organization_lineage":["https://openalex.org/I887064364"],"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":"Efthymiou, A, Rudinac, S, Kackovic, M, Wijnberg, N & Worring, M 2026, VL-KGE: Vision-Language Models Meet Knowledge Graph Embeddings. in WWW '26 : Proceedings of the ACM Web Conference 2026 : April 13-17, 2026, Dubai, United Arab Emirates. Association for Computing Machinery, New York, NY, pp. 7552-7563, 35th ACM Web Conference, WWW 2026, Dubai, United Arab Emirates, 29/06/26. https://doi.org/10.1145/3774904.3792677","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2603.02435","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2603.02435","pdf_url":"https://arxiv.org/pdf/2603.02435","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Real-world":[0],"multimodal":[1,44,109,135,150],"knowledge":[2,17,112,161],"graphs":[3],"(MKGs)":[4],"are":[5,11,33],"inherently":[6],"heterogeneous,":[7],"modeling":[8,105],"entities":[9,28],"that":[10,96,127],"associated":[12],"with":[13,102],"diverse":[14,80],"modalities.":[15],"Traditional":[16],"graph":[18],"embedding":[19,85],"(KGE)":[20],"methods":[21,137],"excel":[22],"at":[23],"learning":[24],"continuous":[25],"representations":[26,110],"of":[27,111,147],"and":[29,59,117,124,134,155],"relations,":[30],"yet":[31],"they":[32],"typically":[34],"designed":[35],"for":[36,149],"unimodal":[37,133],"settings.":[38],"Recent":[39],"approaches":[40],"extend":[41],"KGE":[42,136],"to":[43,78,106],"settings":[45],"but":[46],"remain":[47],"constrained,":[48],"often":[49],"processing":[50],"modalities":[51,81],"in":[52,55,138],"isolation,":[53],"resulting":[54],"weak":[56],"cross-modal":[57,98],"alignment,":[58],"relying":[60],"on":[61,115],"simplistic":[62],"assumptions":[63],"such":[64],"as":[65],"uniform":[66],"modality":[67],"availability":[68],"across":[69],"entities.":[70],"Vision-Language":[71,89],"Models":[72],"(VLMs)":[73],"offer":[74],"a":[75,83,94],"powerful":[76],"way":[77],"align":[79],"within":[82],"shared":[84],"space.":[86],"We":[87],"propose":[88],"Knowledge":[90],"Graph":[91],"Embeddings":[92],"(VL-KGE),":[93],"framework":[95],"integrates":[97],"alignment":[99],"from":[100],"VLMs":[101,148],"structured":[103,156],"relational":[104],"learn":[107],"unified":[108],"graphs.":[113,162],"Experiments":[114],"WN9-IMG":[116],"two":[118],"novel":[119],"fine":[120],"art":[121],"MKGs,":[122],"WikiArt-MKG-v1":[123],"WikiArt-MKG-v2,":[125],"demonstrate":[126],"VL-KGE":[128],"consistently":[129],"improves":[130],"over":[131,158],"traditional":[132],"link":[139],"prediction":[140],"tasks.":[141],"Our":[142],"results":[143],"highlight":[144],"the":[145],"value":[146],"KGE,":[151],"enabling":[152],"more":[153],"robust":[154],"reasoning":[157],"large-scale":[159],"heterogeneous":[160]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-28T08:01:55.173337","created_date":"2026-03-05T00:00:00"}
