{"id":"https://openalex.org/W4415428416","doi":"https://doi.org/10.3233/faia251115","title":"Learning After Model Deployment","display_name":"Learning After Model Deployment","publication_year":2025,"publication_date":"2025-10-21","ids":{"openalex":"https://openalex.org/W4415428416","doi":"https://doi.org/10.3233/faia251115"},"language":null,"primary_location":{"id":"doi:10.3233/faia251115","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia251115","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.3233/faia251115","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120092226","display_name":"Derda Kaymak","orcid":null},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Derda Kaymak","raw_affiliation_strings":["University of Illinois Chicago, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois Chicago, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017100245","display_name":"Gyuhak Kim","orcid":"https://orcid.org/0000-0002-3110-4561"},"institutions":[{"id":"https://openalex.org/I4210099672","display_name":"Accenture (United States)","ror":"https://ror.org/013g16z83","country_code":"US","type":"company","lineage":["https://openalex.org/I4210093804","https://openalex.org/I4210099672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gyuhak Kim","raw_affiliation_strings":["Accenture, USA"],"affiliations":[{"raw_affiliation_string":"Accenture, USA","institution_ids":["https://openalex.org/I4210099672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120092227","display_name":"Tomoya Kaichi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164495","display_name":"KDDI Research (Japan)","ror":"https://ror.org/05qsqt662","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210164495"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomoya Kaichi","raw_affiliation_strings":["KDDI Research, Japan"],"affiliations":[{"raw_affiliation_string":"KDDI Research, Japan","institution_ids":["https://openalex.org/I4210164495"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038450961","display_name":"Tatsuya Konishi","orcid":"https://orcid.org/0000-0002-2255-0156"},"institutions":[{"id":"https://openalex.org/I4210164495","display_name":"KDDI Research (Japan)","ror":"https://ror.org/05qsqt662","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210164495"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tatsuya Konishi","raw_affiliation_strings":["KDDI Research, Japan"],"affiliations":[{"raw_affiliation_string":"KDDI Research, Japan","institution_ids":["https://openalex.org/I4210164495"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100339927","display_name":"Bing Liu","orcid":"https://orcid.org/0000-0002-4096-6980"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bing Liu","raw_affiliation_strings":["University of Illinois Chicago, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois Chicago, USA","institution_ids":["https://openalex.org/I39422238"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5120092226"],"corresponding_institution_ids":["https://openalex.org/I39422238"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.64002933,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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/T13405","display_name":"Educational Assessment and Improvement","score":0.1860000044107437,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13405","display_name":"Educational Assessment and Improvement","score":0.1860000044107437,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.6782000064849854},{"id":"https://openalex.org/keywords/incremental-learning","display_name":"Incremental learning","score":0.6035000085830688},{"id":"https://openalex.org/keywords/ask-price","display_name":"Ask price","score":0.5684999823570251},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5428000092506409},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4505999982357025},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.41040000319480896},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.4027000069618225},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.3982999920845032}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7242000102996826},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.6782000064849854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6748999953269958},{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.6035000085830688},{"id":"https://openalex.org/C90329073","wikidata":"https://www.wikidata.org/wiki/Q914232","display_name":"Ask price","level":2,"score":0.5684999823570251},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5428000092506409},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5220999717712402},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4505999982357025},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.41040000319480896},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.4027000069618225},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.3982999920845032},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.32899999618530273},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3066999912261963},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3012999892234802},{"id":"https://openalex.org/C2779542340","wikidata":"https://www.wikidata.org/wiki/Q1062461","display_name":"Learning object","level":2,"score":0.2896000146865845},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.28839999437332153},{"id":"https://openalex.org/C24138899","wikidata":"https://www.wikidata.org/wiki/Q17141258","display_name":"Instance-based learning","level":3,"score":0.28049999475479126},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.273499995470047},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.25529998540878296},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.25450000166893005}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3233/faia251115","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia251115","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},{"id":"pmh:oai:arXiv.org:2510.17160","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.17160","pdf_url":"https://arxiv.org/pdf/2510.17160","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.3233/faia251115","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia251115","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3973128626","display_name":null,"funder_award_id":"2225427","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5390123671","display_name":null,"funder_award_id":"10424","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5603462533","display_name":null,"funder_award_id":"CNS-2225427","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6062656956","display_name":null,"funder_award_id":"IIS-2229876","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6360409883","display_name":null,"funder_award_id":"2229876","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8239307590","display_name":"III: Small: A Holistic Approach to Sentiment Analysis","funder_award_id":"1910424","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","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/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0,42,119],"classic":[1,165],"supervised":[2,166],"learning,":[3],"once":[4],"a":[5,241],"model":[6,47,186],"is":[7,13,26,79,90,100,126,154,161,181],"deployed":[8],"in":[9,87,135,156,169,232],"an":[10,44,109],"application,":[11,150],"it":[12,21],"fixed.":[14],"No":[15],"updates":[16],"will":[17,261],"be":[18,49,209],"made":[19],"to":[20,51,102,183],"during":[22,149],"the":[23,46,121,137,173,185,191,195,199,220,257,263],"application.":[24],"This":[25],"inappropriate":[27],"for":[28,116],"many":[29],"dynamic":[30,127,247],"and":[31,59,81,112,128,178,198,211,250],"open":[32],"environments,":[33],"where":[34],"unexpected":[35],"samples":[36,55,125,201],"from":[37,56,130,164,187,194,202,214],"unseen":[38,57],"classes":[39,58,142,146,153,176,197,228,255],"may":[40],"appear.":[41],"such":[43],"environment,":[45],"should":[48],"able":[50],"detect":[52],"these":[53,215,237],"novel":[54,124,200,242],"learn":[60,172],"them":[61],"after":[62,72],"they":[63,107],"are":[64,147],"labeled.":[65],"We":[66],"call":[67],"this":[68,88,207],"paradigm":[69],"Autonomous":[70],"Learning":[71,160],"Model":[73],"Deployment":[74],"(ALMD).":[75],"The":[76],"learning":[77,167,252],"here":[78],"continuous":[80],"involves":[82],"no":[83],"human":[84,93],"engineers.":[85],"Labeling":[86],"scenario":[89],"performed":[91],"by":[92],"co-workers":[94],"or":[95],"other":[96],"knowledgeable":[97],"agents,":[98],"which":[99,245],"similar":[101],"what":[103],"humans":[104],"do":[105],"when":[106],"encounter":[108],"unfamiliar":[110],"object":[111],"ask":[113],"another":[114],"person":[115],"its":[117],"name.":[118],"ALMD,":[120,170],"detection":[122,134,249],"of":[123,139,226,253,265],"differs":[129],"traditional":[131,157],"out-of-distribution":[132],"(OOD)":[133],"that":[136],"set":[138],"in-distribution":[140],"(ID)":[141],"expands":[143],"as":[144,206],"new":[145,175,227,254],"learned":[148],"whereas":[151],"ID":[152,196],"fixed":[155],"OOD":[158,248],"detection.":[159],"also":[162],"different":[163],"because":[168,224],"we":[171,239],"encountered":[174],"immediately":[177],"incrementally.":[179],"It":[180],"difficult":[182],"retrain":[184],"scratch":[188],"using":[189],"all":[190],"past":[192],"data":[193,221],"newly":[203],"discovered":[204],"classes,":[205],"would":[208],"resource-":[210],"time-consuming.":[212],"Apart":[213],"two":[216],"challenges,":[217],"ALMD":[218],"faces":[219],"scarcity":[222],"issue":[223],"instances":[225],"often":[229],"appear":[230],"sporadically":[231],"real-life":[233],"applications.":[234],"To":[235],"address":[236],"issues,":[238],"propose":[240],"method,":[243],"PLDA,":[244],"performs":[246],"incremental":[251],"on":[256],"fly.":[258],"Empirical":[259],"evaluations":[260],"demonstrate":[262],"effectiveness":[264],"PLDA.":[266]},"counts_by_year":[],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2025-10-22T00:00:00"}