{"id":"https://openalex.org/W7160830074","doi":"https://doi.org/10.48550/arxiv.2605.07505","title":"LiteGUI: Distilling Compact GUI Agents with Reinforcement Learning","display_name":"LiteGUI: Distilling Compact GUI Agents with Reinforcement Learning","publication_year":2026,"publication_date":"2026-05-08","ids":{"openalex":"https://openalex.org/W7160830074","doi":"https://doi.org/10.48550/arxiv.2605.07505"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.07505","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.07505","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2605.07505","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135899115","display_name":"Yubin Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Yubin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102497980","display_name":"Zicheng Cai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cai, Zicheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135846230","display_name":"Liping Ning","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ning, Liping","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135860573","display_name":"Hua Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Hua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135875831","display_name":"Zhi Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Zhi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135832825","display_name":"Yaohua Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Yaohua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135850879","display_name":"Hao Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Hao","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":0.7293000221252441,"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":0.7293000221252441,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.07259999960660934,"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/T11574","display_name":"Artificial Intelligence in Games","score":0.026000000536441803,"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/pipeline","display_name":"Pipeline (software)","score":0.5582000017166138},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5482000112533569},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4422999918460846},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.43299999833106995},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.3776000142097473},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.375},{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.3379000127315521},{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.33719998598098755}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7875000238418579},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5582000017166138},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5482000112533569},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5123000144958496},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4422999918460846},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.43299999833106995},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4081000089645386},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3776000142097473},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.375},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.3379000127315521},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.33719998598098755},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.3368000090122223},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.32679998874664307},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.3199000060558319},{"id":"https://openalex.org/C2779038628","wikidata":"https://www.wikidata.org/wiki/Q7248497","display_name":"Programming by demonstration","level":3,"score":0.31439998745918274},{"id":"https://openalex.org/C37789001","wikidata":"https://www.wikidata.org/wiki/Q782543","display_name":"Graphical user interface","level":2,"score":0.295199990272522},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2906999886035919},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.28459998965263367},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.2791999876499176},{"id":"https://openalex.org/C2776505523","wikidata":"https://www.wikidata.org/wiki/Q4785468","display_name":"Plan (archaeology)","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.26739999651908875},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.266400009393692}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.07505","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.07505","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.07505","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.07505","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"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":{"Developing":[0],"lightweight,":[1],"on-device":[2,15],"vision-language":[3],"GUI":[4,85,115,144,158],"agents":[5,16],"is":[6],"essential":[7],"for":[8,34],"efficient":[9],"cross-platform":[10],"automated":[11,152],"interaction.":[12],"However,":[13],"current":[14],"are":[17],"constrained":[18],"by":[19],"limited":[20],"model":[21],"capacity,":[22],"and":[23,43,46,107,195],"further":[24,122,189],"performance":[25,68,173,210],"improvements":[26],"remain":[27],"urgently":[28],"needed.":[29],"Traditional":[30],"Supervised":[31],"Fine-Tuning":[32],"(SFT)":[33],"small-scale":[35,70],"models":[36,176,183],"often":[37],"leads":[38],"to":[39,49,156],"overfitting,":[40],"catastrophic":[41],"forgetting":[42],"policy":[44],"rigidity,":[45],"thus":[47],"fails":[48],"fully":[50,200],"address":[51],"these":[52],"challenges.":[53],"In":[54,147],"this":[55,119],"work,":[56],"we":[57,121,149],"propose":[58],"a":[59,99,124],"novel":[60],"SFT-free":[61],"training":[62],"paradigm":[63],"that":[64,129,168,191],"significantly":[65],"enhances":[66],"the":[67,75,84,109,202,209],"of":[69,79,204,212],"models.":[71],"We":[72],"first":[73],"present":[74],"initial":[76],"systematic":[77],"integration":[78],"generalized":[80],"knowledge":[81],"distillation":[82,194],"into":[83],"agent":[86,145],"domain":[87],"via":[88],"Guided":[89],"On-policy":[90],"Distillation.":[91],"By":[92],"incorporating":[93],"oracle":[94],"reference":[95],"trajectories":[96,160],"together":[97],"with":[98,135,161,180],"dynamic":[100],"retrieval":[101],"mechanism,":[102],"our":[103,169],"method":[104,170],"reduces":[105],"hallucinations":[106],"mitigates":[108],"cognitive":[110],"misalignment":[111],"inherent":[112],"in":[113,142],"multi-solution":[114,163,196],"tasks.":[116],"Building":[117],"on":[118],"foundation,":[120],"introduce":[123],"Multi-solution":[125],"Dual-level":[126],"GRPO":[127],"framework":[128],"jointly":[130],"aligns":[131],"macro-level":[132],"subtask":[133],"planning":[134],"micro-level":[136],"execution":[137],"matching,":[138],"thereby":[139],"improving":[140],"exploration":[141,198],"long-horizon":[143],"scenarios.":[146],"addition,":[148],"construct":[150],"an":[151],"data":[153],"generation":[154],"pipeline":[155],"synthesize":[157],"task":[159],"rich":[162],"annotations.":[164],"Extensive":[165],"experiments":[166],"show":[167],"achieves":[171],"state-of-the-art":[172],"among":[174],"lightweight":[175],"while":[177],"remaining":[178],"competitive":[179],"substantially":[181],"larger-scale":[182],"across":[184],"all":[185],"benchmarks.":[186],"Ablation":[187],"studies":[188],"demonstrate":[190],"structured":[192],"on-policy":[193],"dual-level":[197],"can":[199],"unlock":[201],"capabilities":[203],"2B/3B":[205],"scale":[206],"agents,":[207],"surpassing":[208],"limits":[211],"conventional":[213],"imitation":[214],"learning.":[215]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-12T00:00:00"}