{"id":"https://openalex.org/W4406892011","doi":"https://doi.org/10.1109/tnnls.2025.3528885","title":"Concept-Aware Graph Convolutional Network for Compositional Zero-Shot Learning","display_name":"Concept-Aware Graph Convolutional Network for Compositional Zero-Shot Learning","publication_year":2025,"publication_date":"2025-01-28","ids":{"openalex":"https://openalex.org/W4406892011","doi":"https://doi.org/10.1109/tnnls.2025.3528885","pmid":"https://pubmed.ncbi.nlm.nih.gov/40031299"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2025.3528885","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3528885","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100355653","display_name":"Yang Liu","orcid":"https://orcid.org/0000-0001-5917-8653"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yang Liu","raw_affiliation_strings":["School of Telecommunications Engineering, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Telecommunications Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056851669","display_name":"Xinshuo Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinshuo Wang","raw_affiliation_strings":["School of Telecommunications Engineering, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Telecommunications Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101785348","display_name":"Xinbo Gao","orcid":"https://orcid.org/0000-0003-1443-0776"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinbo Gao","raw_affiliation_strings":["Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046605531","display_name":"Jungong Han","orcid":"https://orcid.org/0000-0003-4361-956X"},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jungong Han","raw_affiliation_strings":["Department of Computer Science, The University of Sheffield, Yorkshire, U.K"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Sheffield, Yorkshire, U.K","institution_ids":["https://openalex.org/I91136226"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082634513","display_name":"Ling Shao","orcid":"https://orcid.org/0000-0002-8264-6117"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling Shao","raw_affiliation_strings":["UCAS-Terminus AI Laboratory, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"UCAS-Terminus AI Laboratory, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100355653"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":9.4273,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.97175946,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"36","issue":"6","first_page":"10394","last_page":"10406"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.993399977684021,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.993399977684021,"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/T12676","display_name":"Machine Learning and ELM","score":0.9675999879837036,"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":0.6702550649642944},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5760140419006348},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4180352985858917},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2945328950881958}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6702550649642944},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5760140419006348},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4180352985858917},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2945328950881958}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2025.3528885","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3528885","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:40031299","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40031299","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3453920714","display_name":null,"funder_award_id":"62221005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4297946667","display_name":null,"funder_award_id":"U22A2096","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4854076541","display_name":null,"funder_award_id":"62376207","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G913836228","display_name":null,"funder_award_id":"62036007","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/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1948251820","https://openalex.org/W2117539524","https://openalex.org/W2328725012","https://openalex.org/W2400717490","https://openalex.org/W2736809457","https://openalex.org/W2889167066","https://openalex.org/W2940256401","https://openalex.org/W2947983671","https://openalex.org/W2963499153","https://openalex.org/W2964015378","https://openalex.org/W2964051675","https://openalex.org/W2986385672","https://openalex.org/W2990045899","https://openalex.org/W3007364240","https://openalex.org/W3035084814","https://openalex.org/W3042609801","https://openalex.org/W3158711590","https://openalex.org/W3159481202","https://openalex.org/W3162332195","https://openalex.org/W3164354101","https://openalex.org/W3168997536","https://openalex.org/W3176474016","https://openalex.org/W3189076762","https://openalex.org/W3196690531","https://openalex.org/W3211858897","https://openalex.org/W4280590775","https://openalex.org/W4281722009","https://openalex.org/W4312310776","https://openalex.org/W4312358791","https://openalex.org/W4312400874","https://openalex.org/W4312539810","https://openalex.org/W4312578829","https://openalex.org/W4312847199","https://openalex.org/W4313183962","https://openalex.org/W4385245566","https://openalex.org/W4386065859","https://openalex.org/W4386076688","https://openalex.org/W4387449204","https://openalex.org/W4393149562","https://openalex.org/W4393159686","https://openalex.org/W4400077048","https://openalex.org/W4400314496","https://openalex.org/W4401387710","https://openalex.org/W6736057607","https://openalex.org/W6760001035","https://openalex.org/W6771932116","https://openalex.org/W6780184713","https://openalex.org/W6783399553","https://openalex.org/W6791353385","https://openalex.org/W6796967493","https://openalex.org/W6800217721","https://openalex.org/W6845600268","https://openalex.org/W6849007661"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Compositional":[0],"zero-shot":[1],"learning":[2,122],"(CZSL)":[3],"aims":[4],"to":[5,20,59,63,84,116],"identify":[6],"unobservable":[7],"compositional":[8],"concepts":[9],"with":[10],"prior":[11,145],"knowledge":[12],"of":[13,121],"known":[14],"primitives":[15,37],"(attributes":[16],"and":[17,25,38,65,81,137,150],"objects).":[18],"Due":[19],"distribution":[21],"differences":[22],"between":[23,36,78],"seen":[24],"unseen":[26,91],"components,":[27],"existing":[28],"methods":[29],"for":[30,89],"CZSL":[31,152],"often":[32],"ignore":[33],"intrinsic":[34],"variations":[35],"suffer":[39],"from":[40,67],"domain":[41],"bias":[42],"problems.":[43],"To":[44],"address":[45],"this":[46],"challenge,":[47],"we":[48],"proposed":[49,72,108,142],"a":[50,99],"concept-aware":[51],"graph":[52,103],"convolutional":[53],"network":[54],"(GCN)":[55],"that":[56,140],"utilizes":[57,74],"cross-attentions":[58],"extract":[60],"features":[61,80],"unique":[62],"attributes":[64],"objects":[66],"paired":[68],"concept-sharing":[69],"inputs.":[70],"The":[71],"model":[73,109,143],"the":[75,86,102,107,111,119,141],"cosine":[76],"similarity":[77],"visual":[79],"synthetic":[82],"embeddings":[83],"estimate":[85],"feasibility":[87],"score":[88,94],"each":[90],"composition.":[92],"This":[93],"is":[95],"then":[96],"employed":[97],"as":[98],"weight":[100],"in":[101,124,147],"adjacency":[104],"matrix.":[105],"Additionally,":[106],"incorporates":[110],"Earth":[112],"mover's":[113],"distance":[114],"(EMD)":[115],"further":[117],"limit":[118],"concept":[120],"interest":[123],"disentanglers.":[125],"Experimental":[126],"results":[127],"on":[128],"three":[129],"challenging":[130],"dataset":[131],"benchmarks,":[132],"including":[133],"UT-Zappos":[134],"50K,":[135],"C-GQA,":[136],"MIT-States,":[138],"demonstrate":[139],"outperforms":[144],"work":[146],"both":[148],"closed-":[149],"open-world":[151],"(OW-CZSL).":[153]},"counts_by_year":[{"year":2025,"cited_by_count":4}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}