{"id":"https://openalex.org/W7137929384","doi":"https://doi.org/10.1609/aaai.v40i29.39672","title":"Online Multi-LLM Selection via Contextual Bandits Under Unstructured Context Evolution","display_name":"Online Multi-LLM Selection via Contextual Bandits Under Unstructured Context Evolution","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7137929384","doi":"https://doi.org/10.1609/aaai.v40i29.39672"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v40i29.39672","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i29.39672","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39672/43633","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39672/43633","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129687804","display_name":"Manhin Poon","orcid":null},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Manhin Poon","raw_affiliation_strings":["City University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"City University of Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079056866","display_name":"Xiangxiang Dai","orcid":"https://orcid.org/0000-0003-0179-196X"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xiangxiang Dai","raw_affiliation_strings":["The Chinese University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129675598","display_name":"Xutong Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xutong Liu","raw_affiliation_strings":["University of Washington"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Washington","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129721357","display_name":"Fang Kong","orcid":null},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fang Kong","raw_affiliation_strings":["Southern University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southern University of Science and Technology","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129646130","display_name":"John C.S. Lui","orcid":null},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"John C.S. Lui","raw_affiliation_strings":["The Chinese University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129651995","display_name":"Jinhang Zuo","orcid":null},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Jinhang Zuo","raw_affiliation_strings":["City University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"City University of Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"29","first_page":"24855","last_page":"24863"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.1581999957561493,"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/T10028","display_name":"Topic Modeling","score":0.1581999957561493,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.14470000565052032,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.05310000106692314,"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/regret","display_name":"Regret","score":0.8101999759674072},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6360999941825867},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6194000244140625},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5752000212669373},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.3935999870300293},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.3849000036716461},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.38359999656677246}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8162999749183655},{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.8101999759674072},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6360999941825867},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6194000244140625},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5752000212669373},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4950000047683716},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44200000166893005},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3935999870300293},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.3849000036716461},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.38359999656677246},{"id":"https://openalex.org/C71611378","wikidata":"https://www.wikidata.org/wiki/Q5165191","display_name":"Contextual design","level":3,"score":0.34060001373291016},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.3386000096797943},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.32109999656677246},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.3206000030040741},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.3102000057697296},{"id":"https://openalex.org/C117160843","wikidata":"https://www.wikidata.org/wiki/Q338652","display_name":"Sublinear function","level":2,"score":0.2989000082015991},{"id":"https://openalex.org/C195818886","wikidata":"https://www.wikidata.org/wiki/Q5421724","display_name":"Expressive power","level":2,"score":0.2989000082015991},{"id":"https://openalex.org/C2777851325","wikidata":"https://www.wikidata.org/wiki/Q7094102","display_name":"Online model","level":2,"score":0.2757999897003174},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2678000032901764},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25459998846054077}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v40i29.39672","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i29.39672","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39672/43633","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:ojs.aaai.org:article/39672","is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/39672","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i29.39672","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i29.39672","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39672/43633","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7137929384.pdf","grobid_xml":"https://content.openalex.org/works/W7137929384.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"exhibit":[4],"diverse":[5,167],"response":[6,73],"behaviors,":[7],"costs,":[8],"and":[9,47,114,134,145,157,181],"strengths,":[10],"making":[11],"it":[12],"challenging":[13],"to":[14,54,74,140],"select":[15],"the":[16,27,38,68,94,184],"most":[17],"suitable":[18],"LLM":[19,101,175,192],"for":[20,99,148,189],"a":[21,79,109,116],"given":[22],"user":[23,146],"query.":[24],"We":[25,107,130],"study":[26],"problem":[28],"of":[29,111,186],"adaptive":[30,191],"multi-LLM":[31],"selection":[32,102],"in":[33,72,178],"an":[34],"online":[35],"setting,":[36],"where":[37],"learner":[39],"interacts":[40],"with":[41],"users":[42],"through":[43],"multi-step":[44],"query":[45,143],"refinement":[46],"must":[48],"choose":[49],"LLMs":[50],"sequentially":[51],"without":[52,124],"access":[53],"offline":[55,160],"datasets":[56],"or":[57,87,162],"model":[58,76],"internals.":[59],"A":[60],"key":[61],"challenge":[62],"arises":[63],"from":[64],"unstructured":[65,104],"context":[66,128],"evolution:":[67],"prompt":[69,105],"dynamically":[70],"changes":[71],"previous":[75],"outputs":[77],"via":[78],"black-box":[80],"process,":[81],"which":[82],"cannot":[83],"be":[84],"simulated,":[85],"modeled,":[86],"learned.":[88],"To":[89],"address":[90],"this,":[91],"we":[92],"propose":[93],"first":[95],"contextual":[96,187],"bandit":[97],"framework":[98],"sequential":[100],"under":[103],"dynamics.":[106],"formalize":[108],"notion":[110],"myopic":[112],"regret":[113,123],"develop":[115],"LinUCB-based":[117],"algorithm":[118],"that":[119,170],"provably":[120],"achieves":[121],"sublinear":[122],"relying":[125],"on":[126,166],"future":[127],"prediction.":[129],"further":[131],"introduce":[132],"budget-aware":[133],"positionally-aware":[135],"(favoring":[136],"early-stage":[137],"satisfaction)":[138],"extensions":[139],"accommodate":[141],"variable":[142],"costs":[144],"preferences":[147],"early":[149],"high-quality":[150],"responses.":[151],"Our":[152],"algorithms":[153],"are":[154],"theoretically":[155],"grounded":[156],"require":[158],"no":[159],"fine-tuning":[161],"dataset-specific":[163],"training.":[164],"Experiments":[165],"benchmarks":[168],"demonstrate":[169],"our":[171],"methods":[172],"outperform":[173],"existing":[174],"routing":[176],"strategies":[177],"both":[179],"accuracy":[180],"cost-efficiency,":[182],"validating":[183],"power":[185],"bandits":[188],"real-time,":[190],"selection.":[193]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-03-18T00:00:00"}
