{"id":"https://openalex.org/W7119188126","doi":"https://doi.org/10.48550/arxiv.2601.00426","title":"RMAAT: Astrocyte-Inspired Memory Compression and Replay for Efficient Long-Context Transformers","display_name":"RMAAT: Astrocyte-Inspired Memory Compression and Replay for Efficient Long-Context Transformers","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7119188126","doi":"https://doi.org/10.48550/arxiv.2601.00426"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2601.00426","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.00426","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.2601.00426","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047546816","display_name":"Md Zesun Ahmed Mia","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Mia, Md Zesun Ahmed","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031018070","display_name":"Malyaban Bal","orcid":"https://orcid.org/0000-0003-0287-2139"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bal, Malyaban","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5032635465","display_name":"Abhronil Sengupta","orcid":"https://orcid.org/0000-0002-5545-4494"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sengupta, Abhronil","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5047546816"],"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.603600025177002,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.603600025177002,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.10920000076293945,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.07530000060796738,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5892999768257141},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5491999983787537},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4129999876022339},{"id":"https://openalex.org/keywords/long-short-term-memory","display_name":"Long short term memory","score":0.3635999858379364},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3215999901294708},{"id":"https://openalex.org/keywords/computational-model","display_name":"Computational model","score":0.30820000171661377},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.3057999908924103}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7705000042915344},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5892999768257141},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5491999983787537},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4129999876022339},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.3635999858379364},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3215999901294708},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.3057999908924103},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.28200000524520874},{"id":"https://openalex.org/C2779602883","wikidata":"https://www.wikidata.org/wiki/Q15544750","display_name":"Memory architecture","level":2,"score":0.2721000015735626},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2720000147819519},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.26739999651908875},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.2660999894142151},{"id":"https://openalex.org/C2781357197","wikidata":"https://www.wikidata.org/wiki/Q5757597","display_name":"High memory","level":2,"score":0.26460000872612},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2606000006198883},{"id":"https://openalex.org/C2776638159","wikidata":"https://www.wikidata.org/wiki/Q18343761","display_name":"Memory cell","level":4,"score":0.2547000050544739},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2601.00426","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.00426","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.2601.00426","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.00426","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":{"The":[0],"quadratic":[1],"complexity":[2],"of":[3,148],"self-attention":[4],"mechanism":[5,99],"presents":[6],"a":[7,33,60,78,115],"significant":[8],"impediment":[9],"to":[10,14,36],"applying":[11],"Transformer":[12,50],"models":[13],"long":[15],"sequences.":[16],"This":[17],"work":[18],"explores":[19],"computational":[20,141],"principles":[21],"derived":[22,82],"from":[23,83],"astrocytes-glial":[24],"cells":[25],"critical":[26],"for":[27,40,119],"biological":[28],"memory":[29,67,120,143],"and":[30,137,142],"synaptic":[31],"modulation-as":[32],"complementary":[34],"approach":[35],"conventional":[37],"architectural":[38],"modifications":[39],"efficient":[41],"self-attention.":[42],"We":[43],"introduce":[44],"the":[45,127,146],"Recurrent":[46],"Memory":[47,111],"Augmented":[48],"Astromorphic":[49],"(RMAAT),":[51],"an":[52,96],"architecture":[53],"integrating":[54],"abstracted":[55],"astrocyte":[56,85,102],"functionalities.":[57],"RMAAT":[58],"employs":[59],"recurrent,":[61],"segment-based":[62],"processing":[63],"strategy":[64],"where":[65],"persistent":[66],"tokens":[68],"propagate":[69],"contextual":[70],"information.":[71],"An":[72],"adaptive":[73],"compression":[74],"mechanism,":[75],"governed":[76],"by":[77,101],"novel":[79,116],"retention":[80],"factor":[81],"simulated":[84],"long-term":[86],"plasticity":[87,104],"(LTP),":[88],"modulates":[89],"these":[90],"tokens.":[91],"Attention":[92],"within":[93],"segments":[94],"utilizes":[95],"efficient,":[97],"linear-complexity":[98],"inspired":[100],"short-term":[103],"(STP).":[105],"Training":[106],"is":[107],"performed":[108],"using":[109],"Astrocytic":[110],"Replay":[112],"Backpropagation":[113],"(AMRB),":[114],"algorithm":[117],"designed":[118],"efficiency":[121],"in":[122,140],"recurrent":[123],"networks.":[124],"Evaluations":[125],"on":[126],"Long":[128],"Range":[129],"Arena":[130],"(LRA)":[131],"benchmark":[132],"demonstrate":[133],"RMAAT's":[134],"competitive":[135],"accuracy":[136],"substantial":[138],"improvements":[139],"efficiency,":[144],"indicating":[145],"potential":[147],"incorporating":[149],"astrocyte-inspired":[150],"dynamics":[151],"into":[152],"scalable":[153],"sequence":[154],"models.":[155]},"counts_by_year":[],"updated_date":"2026-01-08T20:10:11.968330","created_date":"2026-01-08T00:00:00"}
