{"id":"https://openalex.org/W4414972122","doi":"https://doi.org/10.1109/iccv51701.2025.01712","title":"ConceptSplit: Decoupled Multi-Concept Personalization of Diffusion Models via Token-Wise Adaptation and Attention Disentanglement","display_name":"ConceptSplit: Decoupled Multi-Concept Personalization of Diffusion Models via Token-Wise Adaptation and Attention Disentanglement","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4414972122","doi":"https://doi.org/10.1109/iccv51701.2025.01712"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51701.2025.01712","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.01712","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2510.04668","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Habin Lim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Habin Lim","raw_affiliation_strings":["Korea University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea University","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yeongseob Won","orcid":null},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yeongseob Won","raw_affiliation_strings":["Kyung Hee University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kyung Hee University","institution_ids":["https://openalex.org/I35928602"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Juwon Seo","orcid":null},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Juwon Seo","raw_affiliation_strings":["Kyung Hee University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kyung Hee University","institution_ids":["https://openalex.org/I35928602"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Juwon Seo","orcid":null},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Juwon Seo","raw_affiliation_strings":["Kyung Hee University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kyung Hee University","institution_ids":["https://openalex.org/I35928602"]}]},{"author_position":"last","author":{"id":null,"display_name":"Park Park","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Park Park","raw_affiliation_strings":["Korea University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea University","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22875977,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"18421","last_page":"18430"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9298999905586243,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9298999905586243,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9061999917030334,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9007999897003174,"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/personalization","display_name":"Personalization","score":0.6521999835968018},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.6116999983787537},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6050999760627747},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5544999837875366},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5393999814987183},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.48260000348091125},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.447299987077713},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.39489999413490295}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7795000076293945},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.6521999835968018},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.6116999983787537},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6050999760627747},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5544999837875366},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5393999814987183},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.48260000348091125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45509999990463257},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.447299987077713},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40389999747276306},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.39489999413490295},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3734000027179718},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.3626999855041504},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.34049999713897705},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.33160001039505005},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2928999960422516},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.27730000019073486},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.2709999978542328},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26570001244544983},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25519999861717224}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv51701.2025.01712","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.01712","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2510.04668","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.04668","pdf_url":"https://arxiv.org/pdf/2510.04668","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,"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.2510.04668","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2510.04668","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,"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":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2510.04668","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.04668","pdf_url":"https://arxiv.org/pdf/2510.04668","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,"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":[],"awards":[{"id":"https://openalex.org/G19451764","display_name":null,"funder_award_id":"RS-2024-00457882","funder_id":"https://openalex.org/F4320321373","funder_display_name":"Korea University"}],"funders":[{"id":"https://openalex.org/F4320321373","display_name":"Korea University","ror":"https://ror.org/047dqcg40"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"multi-concept":[3,152],"personalization":[4],"for":[5,125],"text-to-image":[6],"(T2I)":[7],"diffusion":[8],"models":[9],"to":[10,56,117],"represent":[11],"several":[12],"subjects":[13],"in":[14,39,47,90,107],"an":[15],"image":[16],"has":[17],"gained":[18],"much":[19],"more":[20],"attention.":[21],"The":[22],"main":[23],"challenge":[24],"of":[25],"this":[26,45,48],"task":[27],"is":[28,159],"\"concept":[29],"mixing\",":[30],"where":[31],"multiple":[32],"learned":[33],"concepts":[34,60],"interfere":[35],"or":[36],"blend":[37],"undesirably":[38],"the":[40,58,87,101,112,137],"output":[41],"image.":[42],"To":[43],"address":[44],"issue,":[46],"paper,":[49],"we":[50,72,97,121,146],"present":[51],"ConceptSplit,":[52],"a":[53,78,104],"novel":[54],"framework":[55,66],"split":[57],"individual":[59],"through":[61],"training":[62,80],"and":[63,115,143],"inference.":[64],"Our":[65],"comprises":[67],"two":[68],"key":[69,102],"components.":[70],"First,":[71],"introduce":[73],"Token-wise":[74],"Value":[75],"Adaptation":[76],"(ToVA),":[77],"merging-free":[79],"method":[81],"that":[82,99,148],"focuses":[83],"exclusively":[84],"on":[85,93],"adapting":[86],"value":[88],"projection":[89],"cross-attention.":[91],"Based":[92],"our":[94],"empirical":[95],"analysis,":[96],"found":[98],"modifying":[100],"projection,":[103],"common":[105],"approach":[106],"existing":[108],"methods,":[109],"can":[110],"disrupt":[111],"attention":[113,131],"mechanism":[114],"lead":[116],"concept":[118,156],"mixing.":[119],"Second,":[120],"propose":[122],"Latent":[123],"Optimization":[124],"Disentangled":[126],"Attention":[127],"(LODA),":[128],"which":[129],"alleviates":[130],"entanglement":[132],"during":[133],"inference":[134],"by":[135],"optimizing":[136],"input":[138],"latent.":[139],"Through":[140],"extensive":[141],"qualitative":[142],"quantitative":[144],"experiments,":[145],"demonstrate":[147],"ConceptSplit":[149],"achieves":[150],"robust":[151],"personalization,":[153],"mitigating":[154],"unintended":[155],"interference.":[157],"Code":[158],"available":[160],"at":[161],"https://github.com/KU-VGI/ConceptSplit":[162]},"counts_by_year":[],"updated_date":"2026-08-18T07:49:30.821534","created_date":"2025-10-09T00:00:00"}
