{"id":"https://openalex.org/W4387968188","doi":"https://doi.org/10.1145/3581783.3611835","title":"VPA: Fully Test-Time Visual Prompt Adaptation","display_name":"VPA: Fully Test-Time Visual Prompt Adaptation","publication_year":2023,"publication_date":"2023-10-26","ids":{"openalex":"https://openalex.org/W4387968188","doi":"https://doi.org/10.1145/3581783.3611835"},"language":"en","primary_location":{"id":"doi:10.1145/3581783.3611835","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3611835","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015291768","display_name":"Jiachen Sun","orcid":"https://orcid.org/0000-0003-1170-4735"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jiachen Sun","raw_affiliation_strings":["University of Michigan, Ann Arbor, MI, USA"],"raw_orcid":"https://orcid.org/0000-0003-1170-4735","affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030917007","display_name":"Mark Ibrahim","orcid":"https://orcid.org/0009-0005-2135-7476"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mark Ibrahim","raw_affiliation_strings":["Meta AI, New York, NY, USA"],"raw_orcid":"https://orcid.org/0009-0005-2135-7476","affiliations":[{"raw_affiliation_string":"Meta AI, New York, NY, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102935600","display_name":"Melissa Hall","orcid":"https://orcid.org/0009-0009-0509-1654"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Melissa Hall","raw_affiliation_strings":["Meta AI, New York, NY, USA"],"raw_orcid":"https://orcid.org/0009-0009-0509-1654","affiliations":[{"raw_affiliation_string":"Meta AI, New York, NY, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021932110","display_name":"Ivan Evtimov","orcid":"https://orcid.org/0009-0003-7763-4263"},"institutions":[{"id":"https://openalex.org/I2799847335","display_name":"Art Institute of Portland","ror":"https://ror.org/01cb0jg64","country_code":"US","type":"education","lineage":["https://openalex.org/I2799847335","https://openalex.org/I2799969541"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ivan Evtimov","raw_affiliation_strings":["Meta AI, Seattle, WA, USA"],"raw_orcid":"https://orcid.org/0009-0003-7763-4263","affiliations":[{"raw_affiliation_string":"Meta AI, Seattle, WA, USA","institution_ids":["https://openalex.org/I2799847335"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003217329","display_name":"Z. Morley Mao","orcid":"https://orcid.org/0000-0002-9844-2055"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Z. Morley Mao","raw_affiliation_strings":["University of Michigan, Ann Arbor, MI, USA"],"raw_orcid":"https://orcid.org/0000-0002-9844-2055","affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079611849","display_name":"Cristian Canton Ferrer","orcid":"https://orcid.org/0000-0002-3189-5498"},"institutions":[{"id":"https://openalex.org/I2799847335","display_name":"Art Institute of Portland","ror":"https://ror.org/01cb0jg64","country_code":"US","type":"education","lineage":["https://openalex.org/I2799847335","https://openalex.org/I2799969541"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cristian Canton Ferrer","raw_affiliation_strings":["Meta AI, Seattle, WA, USA"],"raw_orcid":"https://orcid.org/0000-0002-3189-5498","affiliations":[{"raw_affiliation_string":"Meta AI, Seattle, WA, USA","institution_ids":["https://openalex.org/I2799847335"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084499027","display_name":"Caner Haz\u0131rba\u015f","orcid":"https://orcid.org/0000-0003-1980-5768"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Caner Hazirbas","raw_affiliation_strings":["Meta AI, New York, NY, USA"],"raw_orcid":"https://orcid.org/0000-0003-1980-5768","affiliations":[{"raw_affiliation_string":"Meta AI, New York, NY, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5015291768"],"corresponding_institution_ids":["https://openalex.org/I27837315"],"apc_list":null,"apc_paid":null,"fwci":1.0225,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.81559512,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"5796","last_page":"5806"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998999834060669,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998999834060669,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9998999834060669,"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":0.9973999857902527,"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/robustness","display_name":"Robustness (evolution)","score":0.8608173131942749},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7998001575469971},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.7029327154159546},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.6559350490570068},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5468487739562988},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5431486964225769},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4384566843509674},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.06624594330787659}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8608173131942749},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7998001575469971},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.7029327154159546},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.6559350490570068},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5468487739562988},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5431486964225769},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4384566843509674},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.06624594330787659},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3581783.3611835","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3611835","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8100000023841858,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G1963474923","display_name":null,"funder_award_id":"CNS-1930041, CMMI-2038215","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5829395208","display_name":null,"funder_award_id":"2038215","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G598984900","display_name":null,"funder_award_id":"1930041","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7916748770","display_name":null,"funder_award_id":"CMMI-2038215","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7982038569","display_name":null,"funder_award_id":"CNS-1930041","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8377316191","display_name":null,"funder_award_id":"2112562","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337391","display_name":"Division of Civil, Mechanical and Manufacturing Innovation","ror":"https://ror.org/028yd4c30"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2962793481","https://openalex.org/W2963857521","https://openalex.org/W2981720610","https://openalex.org/W2999905431","https://openalex.org/W3034218934","https://openalex.org/W3035682985","https://openalex.org/W3040572086","https://openalex.org/W3171007011","https://openalex.org/W3173324345","https://openalex.org/W3177096435","https://openalex.org/W3198377975","https://openalex.org/W3198430326","https://openalex.org/W3198675127","https://openalex.org/W3212055905","https://openalex.org/W3214575451","https://openalex.org/W4221156702","https://openalex.org/W4312310776","https://openalex.org/W4312354055","https://openalex.org/W4312365002","https://openalex.org/W4313156423","https://openalex.org/W4382239347","https://openalex.org/W6600210674","https://openalex.org/W6600617465"],"related_works":["https://openalex.org/W3162204513","https://openalex.org/W2371138613","https://openalex.org/W2048963458","https://openalex.org/W2997567050","https://openalex.org/W43109613","https://openalex.org/W2359952343","https://openalex.org/W2239445980","https://openalex.org/W2080152487","https://openalex.org/W3083152911","https://openalex.org/W4394775207"],"abstract_inverted_index":{"Textual":[0],"prompt":[1,42],"tuning":[2],"has":[3],"demonstrated":[4],"significant":[5],"performance":[6,152],"improvements":[7],"in":[8,162],"adapting":[9],"natural":[10],"language":[11],"processing":[12],"models":[13],"to":[14,140],"a":[15,65],"variety":[16],"of":[17,31,40,68,166],"downstream":[18],"tasks":[19],"by":[20,28,120,137,153],"treating":[21],"hand-engineered":[22],"prompts":[23],"as":[24],"trainable":[25],"parameters.":[26],"Inspired":[27],"the":[29,38,53,164],"success":[30],"textual":[32],"prompting,":[33],"several":[34],"studies":[35],"have":[36],"investigated":[37],"efficacy":[39],"visual":[41,58],"tuning.":[43],"In":[44],"this":[45],"work,":[46],"we":[47,130,144],"present":[48],"Visual":[49],"Prompt":[50],"Adaptation":[51],"(VPA),":[52],"first":[54],"framework":[55],"that":[56,114,132,146],"generalizes":[57],"prompting":[59],"with":[60],"test-time":[61,73,127],"adaptation.":[62,95,110],"VPA":[63,84,98,115,133,147,157],"introduces":[64],"small":[66],"number":[67],"learnable":[69],"tokens,":[70],"enabling":[71],"fully":[72],"and":[74,93,108],"storage-efficient":[75],"adaptation":[76,88,151],"without":[77],"necessitating":[78],"source-domain":[79],"information.":[80],"We":[81,96],"examine":[82],"our":[83],"design":[85],"under":[86],"diverse":[87],"settings,":[89],"encompassing":[90],"single-image,":[91],"batched-image,":[92],"pseudo-label":[94],"evaluate":[97],"on":[99],"multiple":[100],"tasks,":[101],"including":[102],"out-of-distribution":[103],"(OOD)":[104],"generalization,":[105],"corruption":[106,135],"robustness,":[107],"domain":[109,150],"Experimental":[111],"results":[112],"reveal":[113],"effectively":[116],"enhances":[117],"OOD":[118],"generalization":[119],"3.3%":[121],"across":[122],"various":[123],"models,":[124],"surpassing":[125],"previous":[126],"approaches.":[128],"Furthermore,":[129],"show":[131],"improves":[134],"robustness":[136,165],"6.5%":[138],"compared":[139],"strong":[141],"baselines.":[142],"Finally,":[143],"demonstrate":[145],"also":[148,158],"boosts":[149],"relatively":[154],"5.2%.":[155],"Our":[156],"exhibits":[159],"marked":[160],"effectiveness":[161],"improving":[163],"zero-shot":[167],"recognition":[168],"for":[169],"vision-language":[170],"models.":[171]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}