{"id":"https://openalex.org/W4415163323","doi":"https://doi.org/10.1109/iccv51701.2025.00115","title":"FA: Forced Prompt Learning of Vision-Language Models for Out-of-Distribution Detection","display_name":"FA: Forced Prompt Learning of Vision-Language Models for Out-of-Distribution Detection","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4415163323","doi":"https://doi.org/10.1109/iccv51701.2025.00115"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51701.2025.00115","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.00115","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/2507.04511","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061726247","display_name":"Xinhua Lu","orcid":"https://orcid.org/0000-0002-2338-7020"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinhua Lu","raw_affiliation_strings":["Sun Yat-sen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Runhe Lai","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Runhe Lai","raw_affiliation_strings":["Sun Yat-sen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111041997","display_name":"Yanqi Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanqi Wu","raw_affiliation_strings":["Sun Yat-sen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091238714","display_name":"Kanghao Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kanghao Chen","raw_affiliation_strings":["Hong Kong University of Science and Technology (Guangzhou)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hong Kong University of Science and Technology (Guangzhou)","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108050904","display_name":"Wei\u2010Shi Zheng","orcid":"https://orcid.org/0000-0001-8327-0003"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei-Shi Zheng","raw_affiliation_strings":["Sun Yat-sen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100707149","display_name":"Ruixuan Wang","orcid":"https://orcid.org/0000-0002-8714-0369"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruixuan Wang","raw_affiliation_strings":["Sun Yat-sen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"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":0.13483262,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1152","last_page":"1161"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9909999966621399,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9909999966621399,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9388999938964844,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9175999760627747,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.6342999935150146},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6158999800682068},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5899999737739563},{"id":"https://openalex.org/keywords/forcing","display_name":"Forcing (mathematics)","score":0.5892000198364258},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5629000067710876},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5429999828338623},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.48730000853538513}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6850000023841858},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.6342999935150146},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6158999800682068},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5899999737739563},{"id":"https://openalex.org/C197115733","wikidata":"https://www.wikidata.org/wiki/Q1003136","display_name":"Forcing (mathematics)","level":2,"score":0.5892000198364258},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5629000067710876},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5501999855041504},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5429999828338623},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.48730000853538513},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.42559999227523804},{"id":"https://openalex.org/C2780211513","wikidata":"https://www.wikidata.org/wiki/Q1132167","display_name":"Discernment","level":2,"score":0.42089998722076416},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4147999882698059},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.3086000084877014},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2953000068664551},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2930999994277954},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.2757999897003174},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.2574000060558319}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv51701.2025.00115","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.00115","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:2507.04511","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.04511","pdf_url":"https://arxiv.org/pdf/2507.04511","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.2507.04511","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2507.04511","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2507.04511","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.04511","pdf_url":"https://arxiv.org/pdf/2507.04511","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":[{"id":"https://openalex.org/G761644807","display_name":"\u9762\u5411\u75be\u75c5\u667a\u80fd\u8bca\u65ad\u7684\u53ef\u89e3\u91ca\u6a21\u578b\u8f85\u52a9\u4e0b\u6df1\u5ea6\u6301\u7eed\u5b66\u4e60\u65b9\u6cd5\u7814\u7a76","funder_award_id":"62071502","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Pre-trained":[0],"vision-language":[1],"models":[2],"(VLMs)":[3],"have":[4],"advanced":[5],"out-of-distribution":[6],"(OOD)":[7],"detection":[8],"recently.":[9],"However,":[10],"existing":[11],"CLIP-based":[12,49],"methods":[13],"often":[14],"focus":[15],"on":[16,29,52],"learning":[17],"OOD-related":[18,43],"knowledge":[19,66],"to":[20,58,79,136],"improve":[21],"OOD":[22,73,158],"detection,":[23,159],"showing":[24],"limited":[25],"generalization":[26],"or":[27],"reliance":[28],"external":[30,165],"large-scale":[31],"auxiliary":[32,166],"datasets.":[33],"In":[34,147],"this":[35,148],"study,":[36],"instead":[37],"of":[38,62,72,93,101,143,153,173],"delving":[39],"into":[40],"the":[41,63,70,94,98,122,133,144],"intricate":[42],"knowledge,":[44],"we":[45,127],"propose":[46],"an":[47,170],"innovative":[48],"framework":[50],"based":[51],"Forced":[53],"prompt":[54,82,135],"leArning":[55],"(FA),":[56],"designed":[57],"make":[59],"full":[60],"use":[61],"In-Distribution":[64],"(ID)":[65],"and":[67,90,121,140],"ultimately":[68],"boost":[69],"effectiveness":[71],"detection.":[74],"Our":[75],"key":[76],"insight":[77],"is":[78,151,190],"learn":[80,137],"a":[81,129],"(i.e.,":[83],"forced":[84,124,130,134],"prompt)":[85],"that":[86],"contains":[87],"more":[88,114,138],"diversified":[89],"richer":[91],"descriptions":[92,142],"ID":[95,110,119,145],"classes":[96],"beyond":[97],"textual":[99],"semantics":[100],"class":[102],"labels.":[103],"Specifically,":[104],"it":[105],"promotes":[106],"better":[107],"discernment":[108],"for":[109],"images,":[111],"by":[112],"forcing":[113],"notable":[115,155],"semantic":[116],"similarity":[117],"between":[118],"images":[120],"learnable":[123],"prompt.":[125],"Moreover,":[126],"introduce":[128],"coefficient,":[131],"encouraging":[132],"comprehensive":[139],"nuanced":[141],"classes.":[146],"way,":[149],"FA":[150],"capable":[152],"achieving":[154],"improvements":[156],"in":[157],"even":[160],"when":[161],"trained":[162],"without":[163],"any":[164],"datasets,":[167],"while":[168],"maintaining":[169],"identical":[171],"number":[172],"trainable":[174],"parameters":[175],"as":[176],"CoOp.":[177],"Extensive":[178],"empirical":[179],"evaluations":[180],"confirm":[181],"our":[182],"method":[183],"consistently":[184],"outperforms":[185],"current":[186],"state-of-the-art":[187],"methods.":[188],"Code":[189],"available":[191],"at":[192],"https://github.com/0xFAFA/FA.":[193]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-14T00:00:00"}