{"id":"https://openalex.org/W7147411308","doi":"https://doi.org/10.48550/arxiv.2603.29194","title":"Multi-Layered Memory Architectures for LLM Agents: An Experimental Evaluation of Long-Term Context Retention","display_name":"Multi-Layered Memory Architectures for LLM Agents: An Experimental Evaluation of Long-Term Context Retention","publication_year":2026,"publication_date":"2026-03-31","ids":{"openalex":"https://openalex.org/W7147411308","doi":"https://doi.org/10.48550/arxiv.2603.29194"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.29194","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.29194","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.29194","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5132668248","display_name":"Sunil Tiwari","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Tiwari, Sunil","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5132594655","display_name":"Payal Fofadiya","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fofadiya, Payal","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5132668248"],"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":0.5231000185012817,"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":0.5231000185012817,"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/T12031","display_name":"Speech and dialogue systems","score":0.2718999981880188,"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":0.048900000751018524,"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/context","display_name":"Context (archaeology)","score":0.6765999794006348},{"id":"https://openalex.org/keywords/context-dependent-memory","display_name":"Context-dependent memory","score":0.5196999907493591},{"id":"https://openalex.org/keywords/data-retention","display_name":"Data retention","score":0.48260000348091125},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.4821999967098236},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.36010000109672546},{"id":"https://openalex.org/keywords/semantic-memory","display_name":"Semantic memory","score":0.35659998655319214},{"id":"https://openalex.org/keywords/context-switch","display_name":"Context switch","score":0.3499000072479248},{"id":"https://openalex.org/keywords/knowledge-retention","display_name":"Knowledge retention","score":0.34700000286102295},{"id":"https://openalex.org/keywords/context-model","display_name":"Context model","score":0.3467000126838684}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7573000192642212},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6765999794006348},{"id":"https://openalex.org/C76679254","wikidata":"https://www.wikidata.org/wiki/Q5165163","display_name":"Context-dependent memory","level":4,"score":0.5196999907493591},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5042999982833862},{"id":"https://openalex.org/C2780866740","wikidata":"https://www.wikidata.org/wiki/Q5227345","display_name":"Data retention","level":2,"score":0.48260000348091125},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4821999967098236},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.36010000109672546},{"id":"https://openalex.org/C197914299","wikidata":"https://www.wikidata.org/wiki/Q18650","display_name":"Semantic memory","level":3,"score":0.35659998655319214},{"id":"https://openalex.org/C53833338","wikidata":"https://www.wikidata.org/wiki/Q1061424","display_name":"Context switch","level":2,"score":0.3499000072479248},{"id":"https://openalex.org/C2985756769","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge retention","level":2,"score":0.34700000286102295},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.3467000126838684},{"id":"https://openalex.org/C176649486","wikidata":"https://www.wikidata.org/wiki/Q2308807","display_name":"Memory management","level":3,"score":0.3418999910354614},{"id":"https://openalex.org/C30390489","wikidata":"https://www.wikidata.org/wiki/Q4680748","display_name":"Adaptive memory","level":3,"score":0.3416000008583069},{"id":"https://openalex.org/C2779602883","wikidata":"https://www.wikidata.org/wiki/Q15544750","display_name":"Memory architecture","level":2,"score":0.33390000462532043},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.3276999890804291},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3221000134944916},{"id":"https://openalex.org/C119907115","wikidata":"https://www.wikidata.org/wiki/Q6815725","display_name":"Memory errors","level":3,"score":0.30640000104904175},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3059000074863434},{"id":"https://openalex.org/C118702147","wikidata":"https://www.wikidata.org/wiki/Q189396","display_name":"Dynamic random-access memory","level":3,"score":0.30169999599456787},{"id":"https://openalex.org/C2779086471","wikidata":"https://www.wikidata.org/wiki/Q2051704","display_name":"False memory","level":3,"score":0.29750001430511475},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2897000014781952},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.26579999923706055},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.2635999917984009},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.25679999589920044},{"id":"https://openalex.org/C2909211665","wikidata":"https://www.wikidata.org/wiki/Q492","display_name":"Memory retention","level":2,"score":0.25429999828338623}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.29194","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.29194","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.29194","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.29194","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":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Long-horizon":[0],"dialogue":[1,22],"systems":[2],"suffer":[3],"from":[4],"semanticdrift":[5],"and":[6,27,34,47,54,70,81,91],"unstable":[7],"memory":[8,77],"retention":[9,35,73,90],"across":[10],"extended":[11],"sessions.":[12],"This":[13],"paper":[14],"presents":[15],"a":[16],"Multi-Layer":[17],"Memory":[18],"Framework":[19],"that":[20],"decomposes":[21],"history":[23],"into":[24],"working,":[25],"episodic,":[26],"semantic":[28],"layers":[29],"with":[30,66],"adaptive":[31],"retrieval":[32],"gating":[33],"regularization.":[36],"The":[37],"architecture":[38],"controls":[39],"cross-session":[40],"drift":[41],"while":[42,74],"maintaining":[43],"bounded":[44],"context":[45,82,96],"growth":[46],"computational":[48],"efficiency.":[49],"Experiments":[50],"on":[51],"LOCOMO,":[52],"LOCCO,":[53],"LoCoMo":[55],"show":[56],"improved":[57],"performance,":[58],"achieving":[59],"46.85":[60],"Success":[61],"Rate,":[62],"0.618":[63],"overall":[64],"F1":[65],"0.594":[67],"multi-hop":[68],"F1,":[69],"56.90%":[71],"six-period":[72],"reducing":[75],"false":[76],"rate":[78],"to":[79,84],"5.1%":[80],"usage":[83],"58.40%.":[85],"Results":[86],"confirm":[87],"enhanced":[88],"long-term":[89],"reasoning":[92],"stability":[93],"under":[94],"constrained":[95],"budgets.":[97]},"counts_by_year":[],"updated_date":"2026-04-02T13:53:19.096889","created_date":"2026-04-02T00:00:00"}