{"id":"https://openalex.org/W7201843239","doi":"https://doi.org/10.1371/journal.pone.0354157","title":"Efficient fine-tuning of large-scale vision-language models for visual marketing analysis: From brand logo detection to aesthetic preference prediction","display_name":"Efficient fine-tuning of large-scale vision-language models for visual marketing analysis: From brand logo detection to aesthetic preference prediction","publication_year":2026,"publication_date":"2026-08-07","ids":{"openalex":"https://openalex.org/W7201843239","doi":"https://doi.org/10.1371/journal.pone.0354157","pmid":"https://pubmed.ncbi.nlm.nih.gov/42566445","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/13450759"},"language":"en","primary_location":{"id":"doi:10.1371/journal.pone.0354157","doi":"https://doi.org/10.1371/journal.pone.0354157","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pone.0354157","pdf_url":"https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0354157&type=printable","source":{"id":"https://openalex.org/S202381698","display_name":"PLoS ONE","issn_l":"1932-6203","issn":["1932-6203"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","erih-plus","jufo-1","ki-jl-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS One","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0354157&type=printable","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5145971208","display_name":"Suxiang Qin","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210118063","display_name":"Guangxi Normal University for Nationalities","ror":"https://ror.org/02cejc171","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210118063"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Suxiang Qin","raw_affiliation_strings":["Guangxi Normal University for Nationalities, Jiangzhou, Chongzuo, Guangxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangxi Normal University for Nationalities, Jiangzhou, Chongzuo, Guangxi, China","institution_ids":["https://openalex.org/I4210118063"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113299879","display_name":"Songwen Wei","orcid":"https://orcid.org/0009-0001-1643-9152","observed_orcids":["https://orcid.org/0009-0001-1643-9152"]},"institutions":[{"id":"https://openalex.org/I4210118063","display_name":"Guangxi Normal University for Nationalities","ror":"https://ror.org/02cejc171","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210118063"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Songwen Wei","raw_affiliation_strings":["Guangxi Normal University for Nationalities, Jiangzhou, Chongzuo, Guangxi, China"],"raw_orcid":"https://orcid.org/0009-0001-1643-9152","affiliations":[{"raw_affiliation_string":"Guangxi Normal University for Nationalities, Jiangzhou, Chongzuo, Guangxi, China","institution_ids":["https://openalex.org/I4210118063"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5113299879"],"corresponding_institution_ids":["https://openalex.org/I4210118063"],"apc_list":{"value":2382,"currency":"USD","value_usd":2382},"apc_paid":{"value":2382,"currency":"USD","value_usd":2382},"fwci":1.4934,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.77989917,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"21","issue":"8","first_page":"e0354157","last_page":"e0354157"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.7538999915122986,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.7538999915122986,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.22550000250339508,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.004100000020116568,"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/vision-language-models","display_name":"vision-language models","score":0.8270000219345093},{"id":"https://openalex.org/keywords/efficient-fine-tuning","display_name":"efficient fine-tuning","score":0.8560000061988831},{"id":"https://openalex.org/keywords/vision-language-alignment","display_name":"vision-language alignment","score":0.8230000138282776},{"id":"https://openalex.org/keywords/logo-detection","display_name":"logo detection","score":0.4230000078678131},{"id":"https://openalex.org/keywords/consumer-behavior-modeling","display_name":"customer behavior modeling","score":0.5070000290870667}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7402999997138977},{"id":"https://openalex.org/C2778720087","wikidata":"https://www.wikidata.org/wiki/Q201436","display_name":"Logo (programming language)","level":2,"score":0.6796000003814697},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.628000020980835},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5597000122070312},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.477400004863739},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.4708999991416931},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44040000438690186},{"id":"https://openalex.org/C48891531","wikidata":"https://www.wikidata.org/wiki/Q1141436","display_name":"Marketing research","level":2,"score":0.4043000042438507},{"id":"https://openalex.org/C150506046","wikidata":"https://www.wikidata.org/wiki/Q6667822","display_name":"Logos Bible Software","level":2,"score":0.3589000105857849},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3538999855518341},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.34450000524520874},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3431999981403351},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.32429999113082886},{"id":"https://openalex.org/C23213687","wikidata":"https://www.wikidata.org/wiki/Q301468","display_name":"Consumer behaviour","level":2,"score":0.3222000002861023},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.31690001487731934},{"id":"https://openalex.org/C98495876","wikidata":"https://www.wikidata.org/wiki/Q1323528","display_name":"Digital marketing","level":2,"score":0.30169999599456787},{"id":"https://openalex.org/C3017588708","wikidata":"https://www.wikidata.org/wiki/Q758901","display_name":"Audio visual","level":2,"score":0.2883000075817108},{"id":"https://openalex.org/C2781286702","wikidata":"https://www.wikidata.org/wiki/Q2604680","display_name":"Target audience","level":2,"score":0.28540000319480896},{"id":"https://openalex.org/C2780878386","wikidata":"https://www.wikidata.org/wiki/Q1659648","display_name":"Visual language","level":2,"score":0.28189998865127563},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2815999984741211},{"id":"https://openalex.org/C512338625","wikidata":"https://www.wikidata.org/wiki/Q624902","display_name":"Online advertising","level":3,"score":0.27869999408721924},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2671999931335449},{"id":"https://openalex.org/C181204326","wikidata":"https://www.wikidata.org/wiki/Q7239820","display_name":"Preference learning","level":3,"score":0.2669000029563904},{"id":"https://openalex.org/C35639132","wikidata":"https://www.wikidata.org/wiki/Q7452468","display_name":"Sequence labeling","level":3,"score":0.2635999917984009}],"mesh":[{"descriptor_ui":"D003258","descriptor_name":"Consumer Behavior","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004954","descriptor_name":"Esthetics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D040541","descriptor_name":"Marketing","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":3,"locations":[{"id":"doi:10.1371/journal.pone.0354157","doi":"https://doi.org/10.1371/journal.pone.0354157","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pone.0354157","pdf_url":"https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0354157&type=printable","source":{"id":"https://openalex.org/S202381698","display_name":"PLoS ONE","issn_l":"1932-6203","issn":["1932-6203"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","erih-plus","jufo-1","ki-jl-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS One","raw_type":"journal-article"},{"id":"pmh:oai:pubmedcentral.nih.gov:13450759","doi":null,"is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13450759/","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13450759/pdf/pone.0354157.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLoS One","raw_type":"Text"},{"id":"pmid:42566445","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42566445","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,"listed_in":[],"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":"PloS one","raw_type":"Journal Article"}],"best_oa_location":{"id":"doi:10.1371/journal.pone.0354157","doi":"https://doi.org/10.1371/journal.pone.0354157","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pone.0354157","pdf_url":"https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0354157&type=printable","source":{"id":"https://openalex.org/S202381698","display_name":"PLoS ONE","issn_l":"1932-6203","issn":["1932-6203"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","erih-plus","jufo-1","ki-jl-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS One","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320325559","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7201843239.pdf","grobid_xml":"https://content.openalex.org/works/W7201843239.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1980972548","https://openalex.org/W2078807908","https://openalex.org/W2103577800","https://openalex.org/W2516195739","https://openalex.org/W2754213847","https://openalex.org/W3213113582","https://openalex.org/W4225582302","https://openalex.org/W4225683910","https://openalex.org/W4281638504","https://openalex.org/W4296629858","https://openalex.org/W4312983485","https://openalex.org/W4322620997","https://openalex.org/W4379520637","https://openalex.org/W4385343171","https://openalex.org/W4385570414","https://openalex.org/W4389861256","https://openalex.org/W4392254174","https://openalex.org/W4393857491","https://openalex.org/W4399376234","https://openalex.org/W4400233153","https://openalex.org/W4402671897","https://openalex.org/W4402743672","https://openalex.org/W4403395879","https://openalex.org/W4407276872","https://openalex.org/W4407667497","https://openalex.org/W4408733250","https://openalex.org/W4409495439","https://openalex.org/W4410493021","https://openalex.org/W4414095994","https://openalex.org/W4416011390","https://openalex.org/W7121478740","https://openalex.org/W7125799258","https://openalex.org/W7130412677","https://openalex.org/W7133193597"],"related_works":["https://openalex.org/W7121478740","https://openalex.org/W1953758350","https://openalex.org/W7203558639","https://openalex.org/W4410712222","https://openalex.org/W7084027932","https://openalex.org/W7130701575","https://openalex.org/W3004033597","https://openalex.org/W4212915707","https://openalex.org/W3096073754","https://openalex.org/W3034797636"],"abstract_inverted_index":{"Visual":[0],"marketing":[1,72,166,184],"analysis":[2,185],"has":[3],"emerged":[4],"as":[5],"a":[6,48,81],"critical":[7],"research":[8],"domain":[9],"at":[10],"the":[11,32,45,64,111,130,135,158,172,175],"intersection":[12],"of":[13,37,47,66,174],"computer":[14],"vision,":[15],"natural":[16],"language":[17],"processing,":[18],"and":[19,34,56,63,89,96,100,121,126,152,178],"consumer":[20],"behavior":[21],"modeling.":[22],"This":[23],"study":[24],"addresses":[25],"three":[26],"fundamental":[27],"challenges":[28],"in":[29,40,154,165,181],"this":[30],"field:":[31],"accurate":[33],"robust":[35],"detection":[36,117],"brand":[38],"logos":[39],"complex":[41],"commercial":[42],"visual":[43,54,183],"scenes,":[44],"construction":[46],"unified":[49],"model":[50],"for":[51,70],"understanding":[52],"both":[53],"content":[55],"accompanying":[57],"text":[58],"through":[59],"fine-grained":[60],"vision-language":[61],"alignment,":[62],"quantification":[65],"audience":[67],"aesthetic":[68,141],"preferences":[69],"data-driven":[71],"effectiveness":[73,167,173],"prediction.":[74],"We":[75],"propose":[76],"Brand-Aesthetic":[77],"Vision-Language":[78,94],"Assistant":[79],"(BAVLA),":[80],"novel":[82],"framework":[83,138],"comprising":[84],"Multi-granularity":[85],"Context-aware":[86],"Brand":[87],"Detection":[88],"Fusion":[90],"Module":[91,98],"(MCBF),":[92],"Aesthetic-aware":[93],"Alignment":[95],"Reasoning":[97],"(AVLR),":[99],"Task-aware":[101],"Progressive":[102],"Efficient":[103],"Tuning":[104],"strategy":[105,180],"(TaPET).":[106],"Compared":[107],"to":[108],"existing":[109],"methods,":[110],"proposed":[112,176],"MCBF":[113],"module":[114],"improves":[115],"logo":[116],"mAP":[118],"by":[119,150],"6.2%":[120],"2.5%":[122],"over":[123],"Faster":[124],"R-CNN":[125],"YOLOv8,":[127],"respectively,":[128,156],"on":[129,157],"Flickr":[131],"Logo-27":[132],"dataset.":[133],"Furthermore,":[134],"complete":[136],"BAVLA":[137],"achieves":[139],"superior":[140],"prediction":[142],"performance,":[143],"surpassing":[144],"previous":[145],"best":[146],"methods":[147],"(NIMA,":[148],"AestheticCNN)":[149],"0.084":[151],"0.055":[153],"PLCC,":[155],"AVA":[159],"dataset,":[160],"while":[161],"attaining":[162],"82.4%":[163],"accuracy":[164],"classification.":[168],"These":[169],"findings":[170],"validate":[171],"modules":[177],"training":[179],"advancing":[182],"capabilities.":[186]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2026-08-08T00:00:00"}
