{"id":"https://openalex.org/W7160940100","doi":"https://doi.org/10.48550/arxiv.2605.10064","title":"MAGE: Multi-Agent Self-Evolution with Co-Evolutionary Knowledge Graphs","display_name":"MAGE: Multi-Agent Self-Evolution with Co-Evolutionary Knowledge Graphs","publication_year":2026,"publication_date":"2026-05-11","ids":{"openalex":"https://openalex.org/W7160940100","doi":"https://doi.org/10.48550/arxiv.2605.10064"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.10064","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.10064","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":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.2605.10064","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135999771","display_name":"Ruiyi Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Ruiyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135992271","display_name":"Zechen Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Zechen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135993649","display_name":"Hao Xue","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xue, Hao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135979728","display_name":"Imran Razzak","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Razzak, Imran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135978045","display_name":"Flora D. Salim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Salim, Flora D.","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":0.3292999863624573,"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":0.3292999863624573,"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/T10028","display_name":"Topic Modeling","score":0.2282000035047531,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.09070000052452087,"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/inference","display_name":"Inference","score":0.5644000172615051},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.4361000061035156},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.3666999936103821},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.33899998664855957},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.3167000114917755},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.3140000104904175}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6589999794960022},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5644000172615051},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.4361000061035156},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.40799999237060547},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.3666999936103821},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.33899998664855957},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32109999656677246},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3167000114917755},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.3140000104904175},{"id":"https://openalex.org/C32946077","wikidata":"https://www.wikidata.org/wiki/Q618079","display_name":"Network analysis","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.27559998631477356},{"id":"https://openalex.org/C162838799","wikidata":"https://www.wikidata.org/wiki/Q596077","display_name":"Counterexample","level":2,"score":0.2603999972343445},{"id":"https://openalex.org/C2777220311","wikidata":"https://www.wikidata.org/wiki/Q6423340","display_name":"Knowledge acquisition","level":2,"score":0.258899986743927},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25360000133514404},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.10064","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.10064","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":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.2605.10064","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.10064","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.8198869824409485,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Self-evolving":[0],"language-model":[1],"agents":[2],"must":[3],"decide":[4],"what":[5,13],"to":[6,11],"learn":[7],"next":[8],"and":[9,74,101,132,153,168,185,198,204],"how":[10,125],"preserve":[12],"they":[14],"have":[15],"learned":[16],"across":[17],"iterations.":[18],"Existing":[19],"systems":[20],"typically":[21],"carry":[22],"this":[23],"cross-iteration":[24],"knowledge":[25,64],"as":[26,85],"natural-language":[27],"feedback,":[28],"flat":[29],"episodic":[30],"memory,":[31],"or":[32],"implicit":[33],"reinforcement":[34],"signals,":[35],"none":[36],"of":[37,139],"which":[38,82],"cleanly":[39],"supports":[40],"a":[41,55,61,89,97,102],"frozen":[42,90],"weak":[43],"backbone":[44,116],"at":[45],"inference":[46],"time.":[47],"This":[48],"paper":[49],"introduces":[50],"MAGE":[51,171],"(Multi-Agent":[52],"Graph-guided":[53],"Evolution),":[54],"framework":[56],"that":[57,181],"externalizes":[58],"self-knowledge":[59],"into":[60],"four-subgraph":[62],"co-evolutionary":[63],"graph.":[65],"Its":[66],"experience":[67],"subgraph":[68],"stores":[69],"both":[70],"teacher-written":[71,186],"failure":[72],"corrections":[73,187],"the":[75,95,109,114,140],"learner's":[76,115],"own":[77],"past":[78],"correct":[79],"reasoning":[80],"traces,":[81],"are":[83,106,188],"retrieved":[84],"task-conditioned":[86],"guidance":[87],"for":[88,143],"execution":[91],"model.":[92],"During":[93],"evolution,":[94],"graph,":[96],"task-level":[98],"search":[99],"bandit,":[100],"skill-level":[103],"routing":[104],"bandit":[105],"updated":[107],"from":[108],"same":[110],"reward":[111],"stream,":[112],"while":[113],"remains":[117],"unchanged.":[118],"We":[119],"further":[120],"provide":[121],"structural":[122],"analysis":[123],"showing":[124],"append-only":[126],"memory":[127],"growth,":[128],"bounded":[129],"curriculum":[130],"coverage,":[131],"task-filtered":[133],"retrieval":[134,141],"together":[135],"support":[136],"stable":[137],"improvement":[138],"substrate":[142],"frozen-learner":[144],"evolution.":[145],"Across":[146],"nine":[147],"benchmarks":[148],"spanning":[149],"mathematical":[150],"reasoning,":[151,161],"multi-hop":[152],"open-domain":[154],"question":[155],"answering,":[156],"spatio-temporal":[157],"analysis,":[158],"financial":[159],"numerical":[160],"medical":[162],"multiple-choice,":[163],"an":[164],"open-world":[165],"survival":[166],"game,":[167],"web":[169],"navigation,":[170],"achieves":[172],"strong":[173],"performance":[174],"against":[175],"prompt-based":[176],"frozen-backbone":[177],"baselines.":[178],"Ablations":[179],"show":[180],"self-harvested":[182],"success":[183,191],"traces":[184],"complementary,":[189],"with":[190],"memories":[192,200],"contributing":[193],"most":[194],"on":[195],"reasoning-template-heavy":[196],"tasks":[197],"corrective":[199],"supporting":[201],"harder":[202],"composition":[203],"interaction":[205],"settings.":[206]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-13T00:00:00"}
