{"id":"https://openalex.org/W7163285976","doi":"https://doi.org/10.48550/arxiv.2606.00610","title":"MemGraphRAG: Memory-based Multi-Agent System for Graph Retrieval-Augmented Generation","display_name":"MemGraphRAG: Memory-based Multi-Agent System for Graph Retrieval-Augmented Generation","publication_year":2026,"publication_date":"2026-05-30","ids":{"openalex":"https://openalex.org/W7163285976","doi":"https://doi.org/10.48550/arxiv.2606.00610"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.00610","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.00610","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.2606.00610","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137680016","display_name":"Chuanjie Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Chuanjie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100667249","display_name":"Zhiyi Xiang","orcid":"https://orcid.org/0009-0009-2034-4904"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiang, Zhishang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137632270","display_name":"Yunbo Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Yunbo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137626623","display_name":"Zerui Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Zerui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137620663","display_name":"Qinggang Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Qinggang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137655111","display_name":"Jinsong Su","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Su, Jinsong","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/T10028","display_name":"Topic Modeling","score":0.46459999680519104,"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/T10028","display_name":"Topic Modeling","score":0.46459999680519104,"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":0.17630000412464142,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.08219999819993973,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.5162000060081482},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.48750001192092896},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4198000133037567},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.3970000147819519},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.36090001463890076},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.3578999936580658},{"id":"https://openalex.org/keywords/directed-graph","display_name":"Directed graph","score":0.3271999955177307},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.32589998841285706}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.805400013923645},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.5162000060081482},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5112000107765198},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.48750001192092896},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4198000133037567},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3970000147819519},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.36090001463890076},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3578999936580658},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34610000252723694},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.3271999955177307},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.32589998841285706},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.32499998807907104},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3181000053882599},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.3167000114917755},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.29440000653266907},{"id":"https://openalex.org/C33762810","wikidata":"https://www.wikidata.org/wiki/Q461671","display_name":"Data integrity","level":2,"score":0.2833000123500824},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.26269999146461487},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.26089999079704285},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.25920000672340393},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2563000023365021},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2549000084400177}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.00610","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.00610","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.2606.00610","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.00610","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":{"Retrieval-Augmented":[0],"Generation":[1],"(RAG)":[2],"has":[3],"become":[4],"an":[5],"essential":[6],"method":[7],"for":[8,22,51,63,161],"mitigating":[9],"hallucinations":[10],"in":[11],"Large":[12],"Language":[13],"Models":[14],"(LLMs)":[15],"by":[16,123],"leveraging":[17],"external":[18],"knowledge.":[19],"Although":[20],"effective":[21],"simple":[23],"queries,":[24],"traditional":[25],"RAG":[26,38],"struggles":[27],"with":[28,178],"large-scale,":[29],"unstructured":[30],"corpora":[31],"where":[32],"information":[33],"is":[34,183],"highly":[35],"fragmented.":[36],"Graph-based":[37],"(GraphRAG)":[39],"incorporates":[40],"knowledge":[41],"graphs":[42,89],"to":[43,81,109,140],"capture":[44],"structural":[45,147],"relationships,":[46],"enabling":[47],"more":[48],"comprehensive":[49],"retrieval":[50,92,158],"complex":[52],"reasoning.":[53],"However,":[54],"existing":[55],"GraphRAG":[56],"methods":[57,78],"rely":[58],"on":[59,70,167],"isolated,":[60],"fragment-level":[61],"extraction":[62,134],"graph":[64,112],"construction,":[65],"lacking":[66],"a":[67,75,100,105,117,128,155],"global":[68,130],"perspective":[69],"the":[71,133,150,162,174],"whole":[72],"corpus.":[73,151],"As":[74],"result,":[76],"these":[77],"frequently":[79],"lead":[80],"thematically":[82],"inconsistent,":[83],"logically":[84],"conflicting,":[85],"and":[86,145],"structurally":[87],"fragmented":[88],"that":[90,103,171],"degrade":[91],"performance.":[93],"In":[94],"this":[95],"paper,":[96],"we":[97,153],"propose":[98,154],"MemGraphRAG,":[99],"novel":[101],"framework":[102],"introduces":[104],"memory-based":[106],"multi-agent":[107],"system":[108],"ensure":[110],"high-quality":[111],"construction.":[113],"Specifically,":[114],"MemGraphRAG":[115,172],"employs":[116],"collaborative":[118],"society":[119],"of":[120],"agents":[121,139],"supported":[122],"shared":[124],"memory,":[125],"which":[126],"provides":[127],"unified":[129],"context":[131],"throughout":[132,149],"process.":[135],"This":[136],"mechanism":[137],"allows":[138],"dynamically":[141],"resolve":[142],"logical":[143],"conflicts":[144],"maintain":[146],"connectivity":[148],"Furthermore,":[152],"memory-aware":[156],"hierarchical":[157],"algorithm":[159],"tailored":[160],"constructed":[163],"graph.":[164],"Extensive":[165],"experiments":[166],"multiple":[168],"benchmarks":[169],"demonstrate":[170],"outperforms":[173],"state-of-the-art":[175],"baseline":[176],"models":[177],"comparable":[179],"efficiency.":[180],"Our":[181],"code":[182],"available":[184],"at":[185],"https://github.com/XMUDeepLIT/MemGraphRAG.":[186]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-03T00:00:00"}
