{"id":"https://openalex.org/W7138936500","doi":"https://doi.org/10.48550/arxiv.2603.16856","title":"Online Experiential Learning for Language Models","display_name":"Online Experiential Learning for Language Models","publication_year":2026,"publication_date":"2026-03-17","ids":{"openalex":"https://openalex.org/W7138936500","doi":"https://doi.org/10.48550/arxiv.2603.16856"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.16856","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.16856","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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.16856","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130153420","display_name":"Tianzhu Ye","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ye, Tianzhu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130129377","display_name":"Li Dong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong, Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130130306","display_name":"Qingxiu Dong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong, Qingxiu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130019005","display_name":"Xun Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Xun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130142853","display_name":"Shaohan Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Shaohan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130064902","display_name":"Furu Wei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Furu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"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":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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.24889999628067017,"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":0.24889999628067017,"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/T10028","display_name":"Topic Modeling","score":0.15940000116825104,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.06650000065565109,"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/experiential-learning","display_name":"Experiential learning","score":0.8029999732971191},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5665000081062317},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.4973999857902527},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.43630000948905945},{"id":"https://openalex.org/keywords/experiential-knowledge","display_name":"Experiential knowledge","score":0.4000999927520752},{"id":"https://openalex.org/keywords/context-model","display_name":"Context model","score":0.39489999413490295},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.3855000138282776}],"concepts":[{"id":"https://openalex.org/C37228920","wikidata":"https://www.wikidata.org/wiki/Q1307600","display_name":"Experiential learning","level":2,"score":0.8029999732971191},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6589000225067139},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5665000081062317},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.49900001287460327},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.4973999857902527},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.43630000948905945},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4341999888420105},{"id":"https://openalex.org/C123353603","wikidata":"https://www.wikidata.org/wiki/Q5421070","display_name":"Experiential knowledge","level":2,"score":0.4000999927520752},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.39489999413490295},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3855000138282776},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3804999887943268},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3653999865055084},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3257000148296356},{"id":"https://openalex.org/C207609745","wikidata":"https://www.wikidata.org/wiki/Q4944086","display_name":"Bootstrapping (finance)","level":2,"score":0.3212999999523163},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.3181000053882599},{"id":"https://openalex.org/C16443162","wikidata":"https://www.wikidata.org/wiki/Q1068473","display_name":"Educational technology","level":2,"score":0.28940001130104065},{"id":"https://openalex.org/C154775046","wikidata":"https://www.wikidata.org/wiki/Q188","display_name":"German","level":2,"score":0.2883000075817108},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.26820001006126404},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.25949999690055847},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.16856","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.16856","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.16856","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.16856","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6143468022346497,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,88],"prevailing":[1],"paradigm":[2],"for":[3,111,178],"improving":[4],"large":[5],"language":[6,38],"models":[7,39],"relies":[8],"on":[9,65,117],"offline":[10],"training":[11],"with":[12],"human":[13],"annotations":[14],"or":[15],"simulated":[16],"environments,":[17],"leaving":[18],"the":[19,66,85,100,169,173],"rich":[20],"experience":[21],"accumulated":[22,60],"during":[23],"real-world":[24],"deployment":[25,46],"entirely":[26],"unexploited.":[27],"We":[28,114],"propose":[29],"Online":[30],"Experiential":[31],"Learning":[32],"(OEL),":[33],"a":[34],"framework":[35],"that":[36,106,153,165],"enables":[37],"to":[40,84,93],"continuously":[41],"improve":[42],"from":[43,61],"their":[44],"own":[45],"experience.":[47],"OEL":[48,116,131],"operates":[49],"in":[50],"two":[51,89],"stages:":[52],"first,":[53],"transferable":[54],"experiential":[55,109,155],"knowledge":[56,71,110,156,170],"is":[57,72,157,176],"extracted":[58,154],"and":[59,125,128,142,164,172],"interaction":[62],"trajectories":[63,105],"collected":[64],"user":[67],"side;":[68],"second,":[69],"this":[70],"consolidated":[73],"into":[74],"model":[75,102,123,175],"parameters":[76],"via":[77],"on-policy":[78,166],"context":[79],"distillation,":[80],"requiring":[81],"no":[82],"access":[83],"user-side":[86],"environment.":[87],"stages":[90],"are":[91],"iterated":[92],"form":[94],"an":[95],"online":[96],"learning":[97],"loop,":[98],"where":[99],"improved":[101],"collects":[103],"higher-quality":[104],"yield":[107],"richer":[108],"subsequent":[112],"rounds.":[113],"evaluate":[115],"text-based":[118],"game":[119],"environments":[120],"across":[121],"multiple":[122],"scales":[124],"both":[126,139],"thinking":[127],"non-thinking":[129],"variants.":[130],"achieves":[132],"consistent":[133],"improvements":[134],"over":[135],"successive":[136],"iterations,":[137],"enhancing":[138],"task":[140],"accuracy":[141],"token":[143],"efficiency":[144],"while":[145],"preserving":[146],"out-of-distribution":[147],"performance.":[148],"Our":[149],"analysis":[150],"further":[151],"shows":[152],"significantly":[158],"more":[159],"effective":[160,179],"than":[161],"raw":[162],"trajectories,":[163],"consistency":[167],"between":[168],"source":[171],"policy":[174],"critical":[177],"learning.":[180]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-20T00:00:00"}
