{"id":"https://openalex.org/W4224545477","doi":"https://doi.org/10.48550/arxiv.2204.03649","title":"Unsupervised Prompt Learning for Vision-Language Models","display_name":"Unsupervised Prompt Learning for Vision-Language Models","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4224545477","doi":"https://doi.org/10.48550/arxiv.2204.03649"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2204.03649","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":["Cornell University"],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/abs/2204.03649","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074624048","display_name":"Tony Jun Huang","orcid":"https://orcid.org/0000-0003-1205-3313"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Tony","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114042713","display_name":"Jack O. Chu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chu, Jack","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5090973869","display_name":"Fangyun Wei","orcid":"https://orcid.org/0000-0001-8784-4916"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Fangyun","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":41,"citation_normalized_percentile":{"value":0.999842,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9997,"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":0.9997,"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":0.999,"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/T10028","display_name":"Topic Modeling","score":0.9872,"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/adapter","display_name":"Adapter (computing)","score":0.67388827},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.53362674},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.41953206}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.86154914},{"id":"https://openalex.org/C177284502","wikidata":"https://www.wikidata.org/wiki/Q1005390","display_name":"Adapter (computing)","level":2,"score":0.67388827},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6298784},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.60269845},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5743085},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.53362674},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.5330972},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48934597},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.426382},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.41953206},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0925633},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.066494524},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2204.03649","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":["Cornell University"],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://api.datacite.org/dois/10.48550/arxiv.2204.03649","pdf_url":null,"source":{"id":"https://openalex.org/S4393179698","display_name":"DataCite API","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210145204","host_organization_name":"DataCite","host_organization_lineage":["https://openalex.org/I4210145204"],"host_organization_lineage_names":["DataCite"],"type":"metadata"},"license":null,"license_id":null,"version":null}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2204.03649","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":["Cornell University"],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4385571108","https://openalex.org/W4306381730","https://openalex.org/W4229060448","https://openalex.org/W3184035966","https://openalex.org/W3044188621","https://openalex.org/W2981692913","https://openalex.org/W2726367589","https://openalex.org/W2485605994","https://openalex.org/W2160602540","https://openalex.org/W2133028525"],"abstract_inverted_index":{"Contrastive":[0],"vision-language":[1,53,121],"models":[2,54,178],"like":[3],"CLIP":[4,145],"have":[5],"shown":[6],"great":[7],"progress":[8],"in":[9,91],"transfer":[10,117],"learning.":[11,139],"In":[12,35,83],"the":[13,16,32,76,81,93,96,130,166,170],"inference":[14],"stage,":[15],"proper":[17],"text":[18],"description,":[19],"also":[20],"known":[21],"as":[22,45,125,151,153],"prompt,":[23],"needs":[24],"to":[25,29,37,51,110,133],"be":[26],"carefully":[27],"designed":[28],"correctly":[30],"classify":[31],"given":[33],"images.":[34],"order":[36],"avoid":[38,111],"laborious":[39],"prompt":[40,106,112,138,147],"engineering,":[41],"recent":[42],"works":[43],"such":[44],"CoOp,":[46],"CLIP-Adapter":[47],"and":[48,101,169,177],"Tip-Adapter":[49],"propose":[50],"adapt":[52],"for":[55],"downstream":[56],"image":[57],"recognition":[58],"tasks":[59],"on":[60,149,173],"a":[61,88],"small":[62],"set":[63],"of":[64,95,119,160],"labeled":[65,73],"data.":[66],"Though":[67],"promising":[68],"improvements":[69],"are":[70,99,179],"achieved,":[71],"requiring":[72],"data":[74],"from":[75],"target":[77,97],"datasets":[78,98],"may":[79],"restrict":[80],"scalability.":[82],"this":[84],"paper,":[85],"we":[86,102,126],"explore":[87],"different":[89],"scenario,":[90],"which":[92],"labels":[94],"unprovided,":[100],"present":[103],"an":[104],"unsupervised":[105,135],"learning":[107,136],"(UPL)":[108],"approach":[109],"engineering":[113,148],"while":[114],"simultaneously":[115],"improving":[116],"performance":[118],"CLIP-like":[120],"models.":[122],"As":[123],"far":[124],"know,":[127],"UPL":[128,142,161],"is":[129,162],"first":[131],"work":[132],"introduce":[134],"into":[137],"Experimentally,":[140],"our":[141],"outperforms":[143],"original":[144],"with":[146,165],"ImageNet":[150],"well":[152],"other":[154],"10":[155],"datasets.":[156,175],"An":[157],"enhanced":[158],"version":[159],"even":[163],"competitive":[164],"8-shot":[167,171],"CoOp":[168],"TIP-Adapter":[172],"most":[174],"Code":[176],"available":[180],"at":[181],"https://github.com/tonyhuang2022/UPL.":[182]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4224545477","counts_by_year":[{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":30},{"year":2022,"cited_by_count":1}],"updated_date":"2025-01-05T03:01:06.896092","created_date":"2022-04-27"}