{"id":"https://openalex.org/W7163381953","doi":"https://doi.org/10.48550/arxiv.2606.03143","title":"FederatedSkill: Federated Learning for Agentic Skill Evolution","display_name":"FederatedSkill: Federated Learning for Agentic Skill Evolution","publication_year":2026,"publication_date":"2026-06-02","ids":{"openalex":"https://openalex.org/W7163381953","doi":"https://doi.org/10.48550/arxiv.2606.03143"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.03143","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03143","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2606.03143","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101176820","display_name":"Jingbo Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Jingbo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130617664","display_name":"Guanyu Yao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao, Guanyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137770463","display_name":"Yang Zhang","orcid":"https://orcid.org/0009-0005-8024-1940"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071146373","display_name":"Ramana Rao Kompella","orcid":"https://orcid.org/0000-0002-7559-8997"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kompella, Ramana Rao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137758273","display_name":"Gaowen Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Gaowen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5112248869","display_name":"Shiyu Chang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chang, Shiyu","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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.3882000148296356,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.3882000148296356,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.2475000023841858,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.026599999517202377,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/task","display_name":"Task (project management)","score":0.6976000070571899},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.40560001134872437},{"id":"https://openalex.org/keywords/compromise","display_name":"Compromise","score":0.40139999985694885},{"id":"https://openalex.org/keywords/diversity","display_name":"Diversity (politics)","score":0.39239999651908875},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.38749998807907104},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.3619000017642975},{"id":"https://openalex.org/keywords/collaborative-learning","display_name":"Collaborative learning","score":0.35030001401901245},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.3264000117778778}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.724399983882904},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6976000070571899},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.42800000309944153},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.40560001134872437},{"id":"https://openalex.org/C46355384","wikidata":"https://www.wikidata.org/wiki/Q726686","display_name":"Compromise","level":2,"score":0.40139999985694885},{"id":"https://openalex.org/C2781316041","wikidata":"https://www.wikidata.org/wiki/Q1230584","display_name":"Diversity (politics)","level":2,"score":0.39239999651908875},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.38749998807907104},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.3619000017642975},{"id":"https://openalex.org/C138020889","wikidata":"https://www.wikidata.org/wiki/Q2349659","display_name":"Collaborative learning","level":2,"score":0.35030001401901245},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.3422999978065491},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3400999903678894},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.3264000117778778},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.29249998927116394},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.29109999537467957},{"id":"https://openalex.org/C199776023","wikidata":"https://www.wikidata.org/wiki/Q202875","display_name":"Negotiation","level":2,"score":0.2770000100135803},{"id":"https://openalex.org/C2779436431","wikidata":"https://www.wikidata.org/wiki/Q30672407","display_name":"Policy learning","level":2,"score":0.27549999952316284},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2750999927520752},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2605000138282776},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2590999901294708},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.25440001487731934}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.03143","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03143","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2606.03143","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03143","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":[{"score":0.7451285719871521,"id":"https://metadata.un.org/sdg/4","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":{"Modern":[0],"LLM":[1],"agents":[2],"increasingly":[3],"rely":[4],"on":[5],"skill":[6,13,77,109],"libraries":[7],"to":[8,29,55,100,133],"handle":[9],"complex":[10],"tasks,":[11],"making":[12],"evolution":[14,95,110],"a":[15,49,62,113,134,141],"primary":[16],"driver":[17],"of":[18,88],"self-improvement.":[19],"However,":[20],"isolated":[21],"single-user":[22],"task":[23,122],"streams":[24],"lack":[25],"the":[26,85,91],"diversity":[27],"required":[28],"build":[30],"comprehensive":[31],"skills.":[32],"While":[33],"cross-user":[34],"collaboration":[35],"can":[36],"overcome":[37],"this":[38],"data":[39],"bottleneck,":[40],"current":[41],"trajectory-sharing":[42],"approaches":[43],"compromise":[44],"user":[45],"privacy":[46],"and":[47,140],"impose":[48],"uniform":[50],"global":[51,115],"library":[52],"that":[53],"fails":[54],"accommodate":[56],"client":[57],"heterogeneity.":[58],"We":[59],"introduce":[60],"FederatedSkill,":[61],"privacy-preserving":[63],"framework":[64],"for":[65],"collaborative":[66],"agent":[67,96,121],"evolution.":[68],"Moving":[69],"beyond":[70],"raw":[71],"trajectory":[72],"sharing,":[73],"FederatedSkill":[74,124],"utilizes":[75],"semantic":[76],"diffs,":[78],"structured":[79],"patches":[80,99],"over":[81,128],"local":[82],"libraries,":[83],"as":[84],"fundamental":[86],"unit":[87],"communication.":[89],"On":[90],"server":[92],"side,":[93],"an":[94],"aggregates":[97],"these":[98],"dynamically":[101],"model":[102],"client-specific":[103],"capability":[104],"boundaries,":[105],"facilitating":[106],"strictly":[107],"personalized":[108],"rather":[111],"than":[112],"suboptimal":[114],"average.":[116],"Evaluated":[117],"across":[118],"20":[119],"distinct":[120],"families,":[123],"demonstrates":[125],"substantial":[126],"gains":[127],"self-evolving":[129],"baselines,":[130],"achieving":[131],"up":[132],"44.4%":[135],"increase":[136],"in":[137,144],"success":[138],"rate":[139],"37.5%":[142],"reduction":[143],"computational":[145],"cost.":[146]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-04T00:00:00"}
