{"id":"https://openalex.org/W7166021829","doi":"https://doi.org/10.48550/arxiv.2606.27330","title":"Empowering GUI Agents via Autonomous Experience Exploration and Hindsight Experience Utilization for Task Planning","display_name":"Empowering GUI Agents via Autonomous Experience Exploration and Hindsight Experience Utilization for Task Planning","publication_year":2026,"publication_date":"2026-06-25","ids":{"openalex":"https://openalex.org/W7166021829","doi":"https://doi.org/10.48550/arxiv.2606.27330"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.27330","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27330","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.2606.27330","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013651593","display_name":"Tianyi Men","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Men, Tianyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139426278","display_name":"Zhuoran Jin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin, Zhuoran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139435135","display_name":"Pengfei Cao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cao, Pengfei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139434017","display_name":"Yubo Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yubo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139450661","display_name":"Kang Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Kang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139442546","display_name":"Jun Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Jun","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":0.17149999737739563,"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":0.17149999737739563,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.09910000115633011,"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":0.09830000251531601,"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/hindsight-bias","display_name":"Hindsight bias","score":0.9319999814033508},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7462999820709229},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5874999761581421},{"id":"https://openalex.org/keywords/executable","display_name":"Executable","score":0.5358999967575073},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.44670000672340393},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.4311999976634979}],"concepts":[{"id":"https://openalex.org/C10347200","wikidata":"https://www.wikidata.org/wiki/Q1960297","display_name":"Hindsight bias","level":2,"score":0.9319999814033508},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7462999820709229},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6341000199317932},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5874999761581421},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.5774999856948853},{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.5358999967575073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4745999872684479},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.44670000672340393},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.4311999976634979},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3968999981880188},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.3898000121116638},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.32179999351501465},{"id":"https://openalex.org/C84653758","wikidata":"https://www.wikidata.org/wiki/Q5575175","display_name":"Goal orientation","level":2,"score":0.2964000105857849},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.2937000095844269},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.2831999957561493},{"id":"https://openalex.org/C201025465","wikidata":"https://www.wikidata.org/wiki/Q11248500","display_name":"User experience design","level":2,"score":0.2567000091075897},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2526000142097473}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.27330","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27330","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.2606.27330","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27330","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multimodal":[0],"web":[1],"agents":[2],"can":[3],"assist":[4],"humans":[5],"in":[6],"operating":[7],"repetitive":[8],"GUI":[9],"tasks,":[10],"where":[11],"effective":[12],"task":[13,95,108,134],"planning":[14,44,57,129,175],"is":[15,171],"essential":[16],"for":[17,173],"decomposing":[18],"complex":[19],"tasks":[20,167],"into":[21],"executable":[22],"actions.":[23],"While":[24],"small":[25,178],"open":[26],"source":[27],"MLLMs":[28],"are":[29],"cost":[30],"efficient":[31],"and":[32,45,60,71,112,168],"privacy":[33],"preserving":[34],"compared":[35],"with":[36],"commercial":[37],"large":[38],"models,":[39],"they":[40],"suffer":[41],"from":[42],"weak":[43],"limited":[46],"cross":[47],"website":[48],"generalization.":[49,139],"To":[50,83],"address":[51],"these":[52],"limitations,":[53],"we":[54,92],"introduce":[55],"the":[56,86,94,156],"experience":[58,74],"exploration":[59],"utilization":[61],"(PEEU)":[62],"method,":[63],"which":[64],"autonomously":[65],"explores":[66],"environments":[67],"to":[68,75,101],"discover":[69],"experiences":[70,170],"utilizes":[72],"hindsight":[73,164],"synthesize":[76],"strictly":[77],"aligned,":[78],"high":[79,113,127,132,165],"level":[80,121,128,133,166],"training":[81,135],"data.":[82],"quantitatively":[84],"analyze":[85],"generalization":[87,105],"behaviors":[88],"driving":[89],"this":[90],"performance,":[91],"propose":[93],"decomposition":[96],"hierarchical":[97],"analysis":[98,116],"framework":[99],"(TDHAF)":[100],"systematically":[102],"study":[103],"compositional":[104],"across":[106],"three":[107],"granularities:":[109],"low,":[110],"middle":[111],"levels.":[114],"Our":[115],"reveals":[117],"that":[118],"mastering":[119],"low":[120],"atomic":[122],"skills":[123],"does":[124],"not":[125],"guarantee":[126],"competence,":[130],"while":[131],"yields":[136],"stronger":[137],"OOD":[138,174],"Experiments":[140],"on":[141],"real":[142],"world":[143],"benchmarks":[144],"demonstrate":[145,162],"PEEU's":[146],"superior":[147],"effectiveness:":[148],"our":[149],"7B":[150],"model":[151],"achieves":[152],"30.6%":[153],"accuracy,":[154],"outperforming":[155],"much":[157],"larger":[158],"Qwen2.5-VL-32B":[159],"model.":[160],"These":[161],"constructing":[163],"leveraging":[169],"crucial":[172],"abilities":[176],"of":[177],"MLLMs.":[179]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-27T00:00:00"}