{"id":"https://openalex.org/W7161593180","doi":"https://doi.org/10.48550/arxiv.2605.16045","title":"RecMem: Recurrence-based Memory Consolidation for Efficient and Effective Long-Running LLM Agents","display_name":"RecMem: Recurrence-based Memory Consolidation for Efficient and Effective Long-Running LLM Agents","publication_year":2026,"publication_date":"2026-05-15","ids":{"openalex":"https://openalex.org/W7161593180","doi":"https://doi.org/10.48550/arxiv.2605.16045"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.16045","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.16045","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.2605.16045","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136448216","display_name":"Zijie Dai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dai, Zijie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136414070","display_name":"Shiyuan Deng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deng, Shiyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136436752","display_name":"Sheng Guan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guan, Sheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136437667","display_name":"Yizhou Tian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tian, Yizhou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136392044","display_name":"Xin Yao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao, Xin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136377678","display_name":"Xiao Yan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan, Xiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136431717","display_name":"James Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, James","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":0.19359999895095825,"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":0.19359999895095825,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.06159999966621399,"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":0.05299999937415123,"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/memory-consolidation","display_name":"Memory consolidation","score":0.604200005531311},{"id":"https://openalex.org/keywords/subconscious","display_name":"Subconscious","score":0.5687000155448914},{"id":"https://openalex.org/keywords/semantic-memory","display_name":"Semantic memory","score":0.5302000045776367},{"id":"https://openalex.org/keywords/extended-memory","display_name":"Extended memory","score":0.5091000199317932},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.49239999055862427},{"id":"https://openalex.org/keywords/episodic-memory","display_name":"Episodic memory","score":0.45989999175071716},{"id":"https://openalex.org/keywords/flat-memory-model","display_name":"Flat memory model","score":0.44530001282691956},{"id":"https://openalex.org/keywords/memory-management","display_name":"Memory management","score":0.4401000142097473},{"id":"https://openalex.org/keywords/memory-model","display_name":"Memory model","score":0.41339999437332153},{"id":"https://openalex.org/keywords/interleaved-memory","display_name":"Interleaved memory","score":0.3813999891281128}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.722000002861023},{"id":"https://openalex.org/C48455012","wikidata":"https://www.wikidata.org/wiki/Q2892593","display_name":"Memory consolidation","level":3,"score":0.604200005531311},{"id":"https://openalex.org/C96851999","wikidata":"https://www.wikidata.org/wiki/Q848369","display_name":"Subconscious","level":3,"score":0.5687000155448914},{"id":"https://openalex.org/C197914299","wikidata":"https://www.wikidata.org/wiki/Q18650","display_name":"Semantic memory","level":3,"score":0.5302000045776367},{"id":"https://openalex.org/C171675096","wikidata":"https://www.wikidata.org/wiki/Q1143380","display_name":"Extended memory","level":4,"score":0.5091000199317932},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.49239999055862427},{"id":"https://openalex.org/C88576662","wikidata":"https://www.wikidata.org/wiki/Q18646","display_name":"Episodic memory","level":3,"score":0.45989999175071716},{"id":"https://openalex.org/C57863822","wikidata":"https://www.wikidata.org/wiki/Q905488","display_name":"Flat memory model","level":4,"score":0.44530001282691956},{"id":"https://openalex.org/C176649486","wikidata":"https://www.wikidata.org/wiki/Q2308807","display_name":"Memory management","level":3,"score":0.4401000142097473},{"id":"https://openalex.org/C12186640","wikidata":"https://www.wikidata.org/wiki/Q6815743","display_name":"Memory model","level":3,"score":0.41339999437332153},{"id":"https://openalex.org/C63511323","wikidata":"https://www.wikidata.org/wiki/Q908936","display_name":"Interleaved memory","level":4,"score":0.3813999891281128},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.36410000920295715},{"id":"https://openalex.org/C2776014549","wikidata":"https://www.wikidata.org/wiki/Q3050847","display_name":"Consolidation (business)","level":2,"score":0.3560999929904938},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.35120001435279846},{"id":"https://openalex.org/C18131444","wikidata":"https://www.wikidata.org/wiki/Q163585","display_name":"Memory protection","level":5,"score":0.3499999940395355},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3400999903678894},{"id":"https://openalex.org/C74426580","wikidata":"https://www.wikidata.org/wiki/Q719484","display_name":"Memory map","level":3,"score":0.3278999924659729},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.3215000033378601},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.321399986743927},{"id":"https://openalex.org/C24590219","wikidata":"https://www.wikidata.org/wiki/Q18601","display_name":"Long-term memory","level":3,"score":0.30480000376701355},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3043999969959259},{"id":"https://openalex.org/C3720319","wikidata":"https://www.wikidata.org/wiki/Q5015937","display_name":"Cache-only memory architecture","level":5,"score":0.3005000054836273},{"id":"https://openalex.org/C39528615","wikidata":"https://www.wikidata.org/wiki/Q1229610","display_name":"Distributed shared memory","level":5,"score":0.29919999837875366},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29750001430511475},{"id":"https://openalex.org/C136085584","wikidata":"https://www.wikidata.org/wiki/Q910289","display_name":"Overlay","level":2,"score":0.296099990606308},{"id":"https://openalex.org/C92855701","wikidata":"https://www.wikidata.org/wiki/Q5830907","display_name":"Computer memory","level":3,"score":0.2946000099182129},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.28850001096725464},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C87608573","wikidata":"https://www.wikidata.org/wiki/Q7317078","display_name":"Retrospective memory","level":5,"score":0.26820001006126404},{"id":"https://openalex.org/C2779602883","wikidata":"https://www.wikidata.org/wiki/Q15544750","display_name":"Memory architecture","level":2,"score":0.25949999690055847},{"id":"https://openalex.org/C30390489","wikidata":"https://www.wikidata.org/wiki/Q4680748","display_name":"Adaptive memory","level":3,"score":0.258899986743927},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.16045","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.16045","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.2605.16045","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.16045","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":{"Memory":[0],"systems":[1,27,157],"often":[2],"organize":[3],"user-agent":[4],"interactions":[5,68,108],"as":[6],"retrievable":[7],"external":[8],"memory":[9,26,36,42,60,72,92,141,149,156],"and":[10,38,74,90,117,122],"are":[11,84,96,119],"crucial":[12],"for":[13,35,81,98],"long-running":[14],"agents":[15],"by":[16,57,140,158],"overcoming":[17],"the":[18,136,148],"limited":[19],"context":[20],"windows":[21],"of":[22,153],"LLMs.":[23],"However,":[24],"existing":[25],"invoke":[28],"LLMs":[29,83],"to":[30,46,87,110,160],"process":[31],"every":[32],"incoming":[33,67],"interaction":[34],"extraction,":[37],"such":[39],"an":[40],"eager":[41],"consolidation":[43,61,104],"scheme":[44],"leads":[45],"substantial":[47],"token":[48,151],"consumption.":[49],"To":[50,124],"tackle":[51],"this":[52],"problem,":[53],"we":[54],"propose":[55],"RecMem":[56,65,127,146],"rethinking":[58],"when":[59,93],"should":[62],"be":[63],"conducted.":[64],"stores":[66],"in":[69],"a":[70,111,130],"subconscious":[71],"layer":[73],"encode":[75],"them":[76],"using":[77],"lightweight":[78],"embedding":[79],"models":[80],"retrieval.":[82],"only":[85],"invoked":[86],"extract":[88],"episodic":[89],"semantic":[91,112,131],"sustained":[94],"recurrence":[95],"observed":[97],"semantically":[99],"similar":[100],"interactions.":[101],"Such":[102],"recurrence-based":[103],"works":[105],"because":[106],"these":[107],"correspond":[109],"cluster":[113],"with":[114],"rich":[115],"information":[116],"thus":[118],"worth":[120],"extraction":[121],"summarization.":[123],"improve":[125],"accuracy,":[126],"also":[128],"incorporates":[129],"refinement":[132],"mechanism":[133],"that":[134,145],"recovers":[135],"fine-grained":[137],"facts":[138],"omitted":[139],"extraction.":[142],"Experiments":[143],"show":[144],"reduces":[147],"construction":[150],"cost":[152],"three":[154],"SOTA":[155],"up":[159],"87%":[161],"while":[162],"exceeding":[163],"their":[164],"accuracy.":[165]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-19T00:00:00"}