{"id":"https://openalex.org/W4416551551","doi":"https://doi.org/10.1109/iccv51701.2025.01476","title":"Steering Guidance for Personalized Text-to-Image Diffusion Models","display_name":"Steering Guidance for Personalized Text-to-Image Diffusion Models","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4416551551","doi":"https://doi.org/10.1109/iccv51701.2025.01476"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51701.2025.01476","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.01476","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":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2508.00319","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051216184","display_name":"Sunghyun Park","orcid":"https://orcid.org/0009-0003-8497-2367"},"institutions":[{"id":"https://openalex.org/I19268510","display_name":"Qualcomm (United Kingdom)","ror":"https://ror.org/04d3djg48","country_code":"GB","type":"company","lineage":["https://openalex.org/I19268510","https://openalex.org/I4210087596"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Sunghyun Park","raw_affiliation_strings":["Qualcomm AI Research is an initiative of Qualcomm Technologies, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Qualcomm AI Research is an initiative of Qualcomm Technologies, Inc","institution_ids":["https://openalex.org/I19268510"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025534005","display_name":"Seokeon Choi","orcid":"https://orcid.org/0000-0002-1695-5894"},"institutions":[{"id":"https://openalex.org/I19268510","display_name":"Qualcomm (United Kingdom)","ror":"https://ror.org/04d3djg48","country_code":"GB","type":"company","lineage":["https://openalex.org/I19268510","https://openalex.org/I4210087596"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Seokeon Choi","raw_affiliation_strings":["Qualcomm AI Research is an initiative of Qualcomm Technologies, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Qualcomm AI Research is an initiative of Qualcomm Technologies, Inc","institution_ids":["https://openalex.org/I19268510"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069883233","display_name":"Hyung Woo Park","orcid":"https://orcid.org/0000-0002-5341-9249"},"institutions":[{"id":"https://openalex.org/I19268510","display_name":"Qualcomm (United Kingdom)","ror":"https://ror.org/04d3djg48","country_code":"GB","type":"company","lineage":["https://openalex.org/I19268510","https://openalex.org/I4210087596"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Hyoungwoo Park","raw_affiliation_strings":["Qualcomm AI Research is an initiative of Qualcomm Technologies, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Qualcomm AI Research is an initiative of Qualcomm Technologies, Inc","institution_ids":["https://openalex.org/I19268510"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091430620","display_name":"Sungrack Yun","orcid":"https://orcid.org/0000-0003-2462-3854"},"institutions":[{"id":"https://openalex.org/I19268510","display_name":"Qualcomm (United Kingdom)","ror":"https://ror.org/04d3djg48","country_code":"GB","type":"company","lineage":["https://openalex.org/I19268510","https://openalex.org/I4210087596"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Sungrack Yun","raw_affiliation_strings":["Qualcomm AI Research is an initiative of Qualcomm Technologies, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Qualcomm AI Research is an initiative of Qualcomm Technologies, Inc","institution_ids":["https://openalex.org/I19268510"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"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":0.31666815,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"15907","last_page":"15916"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.770799994468689,"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"}},"topics":[{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.770799994468689,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.021299999207258224,"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/T11448","display_name":"Face recognition and analysis","score":0.020999999716877937,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/personalization","display_name":"Personalization","score":0.5667999982833862},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.54339998960495},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.46399998664855957},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.4586000144481659},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.43959999084472656},{"id":"https://openalex.org/keywords/guidance-system","display_name":"Guidance system","score":0.35920000076293945}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7534000277519226},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.5667999982833862},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.54339998960495},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4648999869823456},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.46399998664855957},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.4586000144481659},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.43959999084472656},{"id":"https://openalex.org/C201004817","wikidata":"https://www.wikidata.org/wiki/Q1707071","display_name":"Guidance system","level":2,"score":0.35920000076293945},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.33329999446868896},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33329999446868896},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.3005000054836273},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.29429998993873596},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.2797999978065491},{"id":"https://openalex.org/C2777855551","wikidata":"https://www.wikidata.org/wiki/Q12310021","display_name":"Subject (documents)","level":2,"score":0.27889999747276306},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26260000467300415},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.2538999915122986},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.25360000133514404}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv51701.2025.01476","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.01476","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:2508.00319","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2508.00319","pdf_url":"https://arxiv.org/pdf/2508.00319","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2508.00319","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2508.00319","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2508.00319","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2508.00319","pdf_url":"https://arxiv.org/pdf/2508.00319","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Personalizing":[0],"text-to-image":[1],"diffusion":[2],"models":[3,10,127],"is":[4],"crucial":[5],"for":[6],"adapting":[7],"the":[8,31,39,43,65,72,75,112,144],"pre-trained":[9,124],"to":[11,62,74],"specific":[12],"target":[13,32,76,167],"concepts,":[14],"enabling":[15],"diverse":[16],"image":[17],"generation.":[18],"However,":[19],"fine-tuning":[20,174],"with":[21,30,172],"few":[22],"images":[23],"introduces":[24],"an":[25,97],"inherent":[26],"trade-off":[27],"between":[28,123],"aligning":[29],"distribution":[33,168],"(e.g.,":[34,46],"subject":[35],"fidelity)":[36],"and":[37,58,125,166],"preserving":[38],"broad":[40],"knowledge":[41],"of":[42,114],"original":[44],"model":[45,100,119],"text":[47,81,105,164],"editability).":[48],"Existing":[49],"sampling":[50],"guidance":[51,56,132,138,161],"methods,":[52,133],"such":[53],"as":[54],"classifier-free":[55],"(CFG)":[57],"autoguidance":[59],"(AG),":[60],"fail":[61],"effectively":[63],"guide":[64],"output":[66],"toward":[67,146],"well-balanced":[68],"space:":[69],"CFG":[70],"restricts":[71],"adaptation":[73],"distribution,":[77],"while":[78],"AG":[79],"compromises":[80],"alignment.":[82],"To":[83],"address":[84],"these":[85],"limitations,":[86],"we":[87],"propose":[88],"personalization":[89],"guidance,":[90],"a":[91,103,117,147],"simple":[92],"yet":[93],"effective":[94],"method":[95,109,141],"leveraging":[96],"unlearned":[98],"weak":[99,118],"conditioned":[101],"on":[102,137],"null":[104],"prompt.":[106],"Moreover,":[107],"our":[108,140,159],"dynamically":[110],"controls":[111],"extent":[113],"unlearning":[115],"in":[116],"through":[120],"weight":[121],"interpolation":[122],"fine-tuned":[126],"during":[128],"inference.":[129],"Unlike":[130],"existing":[131],"which":[134],"depend":[135],"solely":[136],"scales,":[139],"explicitly":[142],"steers":[143],"outputs":[145],"balanced":[148],"latent":[149],"space":[150],"without":[151],"additional":[152],"computational":[153],"overhead.":[154],"Experimental":[155],"results":[156],"demonstrate":[157],"that":[158],"proposed":[160],"can":[162],"improve":[163],"alignment":[165],"fidelity,":[169],"integrating":[170],"seamlessly":[171],"various":[173],"strategies.":[175]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
