{"id":"https://openalex.org/W7155407565","doi":"https://doi.org/10.48550/arxiv.2604.20714","title":"Learning to Evolve: A Self-Improving Framework for Multi-Agent Systems via Textual Parameter Graph Optimization","display_name":"Learning to Evolve: A Self-Improving Framework for Multi-Agent Systems via Textual Parameter Graph Optimization","publication_year":2026,"publication_date":"2026-04-22","ids":{"openalex":"https://openalex.org/W7155407565","doi":"https://doi.org/10.48550/arxiv.2604.20714"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.20714","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.20714","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.2604.20714","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134372384","display_name":"Shan He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Shan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134414066","display_name":"Runze Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Runze","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008832682","display_name":"Zhuoyun Du","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Du, Zhuoyun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134458318","display_name":"Huiyu Bai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bai, Huiyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134459387","display_name":"Zouying Cao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cao, Zouying","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134435763","display_name":"Yu Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134426128","display_name":"Bo Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Bo","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/T11273","display_name":"Advanced Graph Neural Networks","score":0.313400000333786,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.313400000333786,"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/T14347","display_name":"Big Data and Digital Economy","score":0.16979999840259552,"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"}},{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.09480000287294388,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/workflow","display_name":"Workflow","score":0.7612000107765198},{"id":"https://openalex.org/keywords/debugging","display_name":"Debugging","score":0.7527999877929688},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5598000288009644},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4862000048160553},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.4253999888896942},{"id":"https://openalex.org/keywords/optimization-algorithm","display_name":"Optimization algorithm","score":0.36800000071525574}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.786899983882904},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.7612000107765198},{"id":"https://openalex.org/C168065819","wikidata":"https://www.wikidata.org/wiki/Q845566","display_name":"Debugging","level":2,"score":0.7527999877929688},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5598000288009644},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4862000048160553},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4503999948501587},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.4253999888896942},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.382999986410141},{"id":"https://openalex.org/C2987595161","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Optimization algorithm","level":2,"score":0.36800000071525574},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.35899999737739563},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.31779998540878296},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3154999911785126},{"id":"https://openalex.org/C47822265","wikidata":"https://www.wikidata.org/wiki/Q854457","display_name":"Complex system","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C164752517","wikidata":"https://www.wikidata.org/wiki/Q5570875","display_name":"Global optimization","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2572999894618988}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.20714","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.20714","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.2604.20714","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.20714","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":[{"score":0.713657021522522,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Designing":[0],"and":[1,91,114,143,169],"optimizing":[2],"multi-agent":[3,71],"systems":[4],"(MAS)":[5],"is":[6,123],"a":[7,66,70,83,129],"complex,":[8],"labor-intensive":[9],"process":[10],"of":[11,33,120,178],"\"Agent":[12],"Engineering.\"":[13],"Existing":[14],"automatic":[15],"optimization":[16,53,137],"methods,":[17],"primarily":[18],"focused":[19],"on":[20,164],"flat":[21],"prompt":[22],"tuning,":[23],"lack":[24],"the":[25,30,80,154,176],"structural":[26],"awareness":[27],"to":[28,49,73,75,111,156,159],"debug":[29],"intricate":[31],"web":[32],"interactions":[34],"in":[35],"MAS.":[36],"More":[37],"critically,":[38],"these":[39,57],"optimizers":[40],"are":[41,93],"static;":[42],"they":[43],"do":[44],"not":[45],"learn":[46,74,157],"from":[47,108,135],"experience":[48],"improve":[50],"their":[51],"own":[52],"strategies.":[54],"To":[55,97],"address":[56],"gaps,":[58],"we":[59,100],"introduce":[60],"Textual":[61,84],"Parameter":[62,85],"Graph":[63,86],"Optimization":[64,127],"(TPGO),":[65],"framework":[67,122],"that":[68,133,172],"enables":[69],"system":[72,155],"evolve.":[76],"TPGO":[77,173],"first":[78],"models":[79],"MAS":[81],"as":[82],"(TPG),":[87],"where":[88],"agents,":[89],"tools,":[90],"workflows":[92],"modular,":[94],"optimizable":[95],"nodes.":[96],"guide":[98],"evolution,":[99],"derive":[101],"\"textual":[102],"gradients,\"":[103],"structured":[104],"natural":[105],"language":[106],"feedback":[107],"execution":[109],"traces,":[110],"pinpoint":[112],"failures":[113],"suggest":[115],"granular":[116],"modifications.":[117],"The":[118],"core":[119],"our":[121],"Group":[124],"Relative":[125],"Agent":[126],"(GRAO),":[128],"novel":[130],"meta-learning":[131],"strategy":[132],"learns":[134],"historical":[136],"experiences.":[138],"By":[139],"analyzing":[140],"past":[141],"successes":[142],"failures,":[144],"GRAO":[145],"becomes":[146],"progressively":[147],"better":[148],"at":[149],"proposing":[150],"effective":[151],"updates,":[152],"allowing":[153],"how":[158],"optimize":[160],"itself.":[161],"Extensive":[162],"experiments":[163],"complex":[165],"benchmarks":[166],"like":[167],"GAIA":[168],"MCP-Universe":[170],"show":[171],"significantly":[174],"enhances":[175],"performance":[177],"state-of-the-art":[179],"agent":[180],"frameworks,":[181],"achieving":[182],"higher":[183],"success":[184],"rates":[185],"through":[186],"automated,":[187],"self-improving":[188],"optimization.":[189]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-24T00:00:00"}
