{"id":"https://openalex.org/W7134817799","doi":"https://doi.org/10.48550/arxiv.2603.07432","title":"Generalization in Online Reinforcement Learning for Mobile Agents","display_name":"Generalization in Online Reinforcement Learning for Mobile Agents","publication_year":2026,"publication_date":"2026-03-08","ids":{"openalex":"https://openalex.org/W7134817799","doi":"https://doi.org/10.48550/arxiv.2603.07432"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.07432","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":null,"license_id":null,"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/A5128688286","display_name":"Li Gu","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Gu, Li","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016421623","display_name":"Zihuan Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Zihuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064393186","display_name":"Zhixiang Chi","orcid":"https://orcid.org/0000-0003-4560-4986"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chi, Zhixiang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128641834","display_name":"Huan Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Huan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100400476","display_name":"Ziqiang Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Ziqiang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012517550","display_name":"Yuanhao Yu","orcid":"https://orcid.org/0000-0001-8176-9716"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Yuanhao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128679035","display_name":"Glen Berseth","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Berseth, Glen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128674547","display_name":"Yang Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yang","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5128688286"],"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.6940000057220459,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.6940000057220459,"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":0.11500000208616257,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.020999999716877937,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8222000002861023},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6570000052452087},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6093999743461609},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.5644999742507935},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5527999997138977},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5006999969482422},{"id":"https://openalex.org/keywords/asynchronous-communication","display_name":"Asynchronous communication","score":0.48510000109672546},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.46070000529289246},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4334000051021576}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8222000002861023},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8044000267982483},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6570000052452087},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6093999743461609},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.5644999742507935},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5527999997138977},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5472000241279602},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5144000053405762},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5006999969482422},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.48510000109672546},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.46070000529289246},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4334000051021576},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.42250001430511475},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.39070001244544983},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.3869999945163727},{"id":"https://openalex.org/C17098449","wikidata":"https://www.wikidata.org/wiki/Q176814","display_name":"Partially observable Markov decision process","level":4,"score":0.38179999589920044},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.38100001215934753},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.35850000381469727},{"id":"https://openalex.org/C37789001","wikidata":"https://www.wikidata.org/wiki/Q782543","display_name":"Graphical user interface","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C144543869","wikidata":"https://www.wikidata.org/wiki/Q2738570","display_name":"Mobile computing","level":2,"score":0.2815000116825104},{"id":"https://openalex.org/C2988145974","wikidata":"https://www.wikidata.org/wiki/Q620615","display_name":"Mobile apps","level":2,"score":0.2809999883174896},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.2721000015735626},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.26840001344680786},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.2563000023365021}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.07432","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.07432","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.07432","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.2603.07432","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.6737329363822937}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Graphical":[0],"user":[1],"interface":[2],"(GUI)-based":[3],"mobile":[4,10],"agents":[5,31],"automate":[6],"digital":[7],"tasks":[8],"on":[9,39,129,148,155,180],"devices":[11],"by":[12],"interpreting":[13],"natural-language":[14],"instructions":[15],"and":[16,51,69,88,114,119,125,159,192,210],"interacting":[17],"with":[18,35,74,104],"the":[19,46,60,163,197,203,211],"screen.":[20],"While":[21],"recent":[22],"methods":[23],"apply":[24],"reinforcement":[25],"learning":[26],"(RL)":[27],"to":[28,45,83,122,139],"train":[29],"vision-language-model(VLM)":[30],"in":[32,186],"interactive":[33],"environments":[34],"a":[36,63,72,105,135,145,168],"primary":[37],"focus":[38],"performance,":[40],"generalization":[41,82],"remains":[42],"underexplored":[43],"due":[44],"lack":[47],"of":[48,111,165],"standardized":[49],"benchmarks":[50],"open-source":[52,196],"RL":[53,94,133,199],"systems.":[54],"In":[55],"this":[56,187],"work,":[57],"we":[58,171,195],"formalize":[59],"problem":[61],"as":[62],"Contextual":[64],"Markov":[65],"Decision":[66],"Process":[67],"(CMDP)":[68],"introduce":[70],"\\textbf{AndroidWorld-Generalization},":[71],"benchmark":[73],"three":[75],"increasingly":[76],"challenging":[77],"regimes":[78],"for":[79],"evaluating":[80],"zero-shot":[81],"unseen":[84,149,156,181],"task":[85,205],"instances,":[86],"templates,":[87],"applications.":[89],"We":[90],"further":[91],"propose":[92],"an":[93],"training":[95,200],"system":[96],"that":[97,132,173],"integrates":[98],"Group":[99],"Relative":[100],"Policy":[101],"Optimization":[102],"(GRPO)":[103],"scalable":[106],"rollout":[107],"collection":[108],"system,":[109,201],"consisting":[110],"containerized":[112],"infrastructure":[113,213],"asynchronous":[115],"execution":[116],"%":[117],",":[118],"error":[120],"recovery":[121],"support":[123,190],"reliable":[124],"efficient":[126],"training.":[127],"Experiments":[128],"AndroidWorld-Generalization":[130],"show":[131],"enables":[134],"7B-parameter":[136],"VLM":[137],"agent":[138],"surpass":[140],"supervised":[141],"fine-tuning":[142],"baselines,":[143],"yielding":[144],"26.1\\%":[146],"improvement":[147],"instances":[150],"but":[151],"only":[152],"limited":[153],"gains":[154],"templates":[157],"(15.7\\%)":[158],"apps":[160],"(8.3\\%),":[161],"underscoring":[162],"challenges":[164],"generalization.":[166],"As":[167],"preliminary":[169],"step,":[170],"demonstrate":[172],"few-shot":[174],"adaptation":[175],"at":[176],"test-time":[177],"improves":[178],"performance":[179],"apps,":[182],"motivating":[183],"future":[184],"research":[185],"direction.":[188],"To":[189],"reproducibility":[191],"fair":[193],"comparison,":[194],"full":[198],"including":[202],"environment,":[204],"suite,":[206],"models,":[207],"prompt":[208],"configurations,":[209],"underlying":[212],"\\footnote{https://github.com/zihuanjiang/AndroidWorld-Generalization}.":[214]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-03-11T00:00:00"}
