{"id":"https://openalex.org/W7134806975","doi":"https://doi.org/10.48550/arxiv.2603.07163","title":"PromptGate Client Adaptive Vision Language Gating for Open Set Federated Active Learning","display_name":"PromptGate Client Adaptive Vision Language Gating for Open Set Federated Active Learning","publication_year":2026,"publication_date":"2026-03-07","ids":{"openalex":"https://openalex.org/W7134806975","doi":"https://doi.org/10.48550/arxiv.2603.07163"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.07163","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128688437","display_name":"Adea Nesturi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nesturi, Adea","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128653835","display_name":"David Due\u00f1as Gaviria","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gaviria, David Due\u00f1as","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128654162","display_name":"Jiajun Zeng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zeng, Jiajun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128679160","display_name":"Shadi Albarqouni","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Albarqouni, Shadi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.46070000529289246,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.46070000529289246,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.16840000450611115,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.16539999842643738,"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/context","display_name":"Context (archaeology)","score":0.6626999974250793},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.6193000078201294},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.5913000106811523},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.553600013256073},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5278000235557556},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.48420000076293945},{"id":"https://openalex.org/keywords/mistake","display_name":"Mistake","score":0.42719998955726624},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.41429999470710754},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.36890000104904175}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7879999876022339},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6626999974250793},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.6193000078201294},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.5913000106811523},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.553600013256073},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5278000235557556},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.48420000076293945},{"id":"https://openalex.org/C2777179996","wikidata":"https://www.wikidata.org/wiki/Q911222","display_name":"Mistake","level":2,"score":0.42719998955726624},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41909998655319214},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.41429999470710754},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.36890000104904175},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.36640000343322754},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.33730000257492065},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.33559998869895935},{"id":"https://openalex.org/C194544171","wikidata":"https://www.wikidata.org/wiki/Q21105679","display_name":"Gating","level":2,"score":0.33169999718666077},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.32899999618530273},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.3273000121116638},{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.3165000081062317},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31150001287460327},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.29350000619888306},{"id":"https://openalex.org/C42357961","wikidata":"https://www.wikidata.org/wiki/Q213363","display_name":"Open set","level":2,"score":0.27900001406669617},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.27630001306533813},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.2754000127315521},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C2779764123","wikidata":"https://www.wikidata.org/wiki/Q7972881","display_name":"Wasting","level":2,"score":0.2671000063419342},{"id":"https://openalex.org/C138020889","wikidata":"https://www.wikidata.org/wiki/Q2349659","display_name":"Collaborative learning","level":2,"score":0.26579999923706055},{"id":"https://openalex.org/C108383078","wikidata":"https://www.wikidata.org/wiki/Q7096399","display_name":"Open platform","level":3,"score":0.2599000036716461},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2590999901294708}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.07163","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.07163","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.07163","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:doi:10.48550/arxiv.2603.07163","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Deploying":[0],"medical":[1,19],"AI":[2,20],"across":[3],"resource-constrained":[4],"institutions":[5],"demands":[6],"data-efficient":[7],"learning":[8],"pipelines":[9],"that":[10,69,86,123,144],"respect":[11],"patient":[12,104],"privacy.":[13],"Federated":[14,67],"Learning":[15,44],"(FL)":[16],"enables":[17],"collaborative":[18],"without":[21,102],"centralising":[22],"data,":[23],"yet":[24],"real-world":[25],"clinical":[26,94],"pools":[27,72],"are":[28],"inherently":[29],"open-set,":[30],"containing":[31],"out-of-distribution":[32],"(OOD)":[33],"noise":[34,50],"such":[35],"as":[36],"imaging":[37,141],"artifacts":[38],"and":[39,96,139],"wrong":[40],"modalities.":[41],"Standard":[42],"Active":[43],"(AL)":[45],"query":[46],"strategies":[47],"mistake":[48],"this":[49],"for":[51,65],"informative":[52],"samples,":[53],"wasting":[54],"scarce":[55],"annotation":[56],"budgets.":[57],"We":[58],"propose":[59],"PromptGate,":[60],"a":[61,77,88,120,126],"dynamic":[62,121],"VLM-gated":[63],"framework":[64],"Open-Set":[66],"AL":[68,133],"purifies":[70],"unlabeled":[71],"before":[73],"querying.":[74],"PromptGate":[75,154],"introduces":[76],"federated":[78],"Class-Specific":[79],"Context":[80],"Optimization:":[81],"lightweight,":[82],"learnable":[83],"prompt":[84],"vectors":[85],"adapt":[87],"frozen":[89],"BiomedCLIP":[90],"backbone":[91],"to":[92,150],"local":[93],"domains":[95],"aggregate":[97],"globally":[98],"via":[99],"FedAvg":[100],"--":[101],"sharing":[103],"data.":[105],"As":[106],"new":[107],"annotations":[108],"arrive,":[109],"prompts":[110],"progressively":[111],"sharpen":[112],"the":[113,117],"ID/OOD":[114],"boundary,":[115],"turning":[116],"VLM":[118,147],"into":[119],"gatekeeper":[122],"is":[124],"strategy-agnostic:":[125],"plug-and-play":[127],"pre-selection":[128],"module":[129],"enhancing":[130],"any":[131],"downstream":[132],"strategy.":[134],"Experiments":[135],"on":[136],"distributed":[137],"dermatology":[138],"breast":[140],"benchmarks":[142],"show":[143],"while":[145],"static":[146],"prompting":[148],"degrades":[149],"50%":[151],"ID":[152],"purity,":[153],"maintains":[155],"$&gt;$95%":[156],"purity":[157],"with":[158],"98%":[159],"OOD":[160],"recall.":[161]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-11T00:00:00"}
