{"id":"https://openalex.org/W7164686920","doi":"https://doi.org/10.1145/3803291.3803294","title":"Ebbinghaus Forgetting Curve and Large Language Model Memory Management: A Cognitive Science-Driven Long-Context Enhancement Framework Design and Prospects","display_name":"Ebbinghaus Forgetting Curve and Large Language Model Memory Management: A Cognitive Science-Driven Long-Context Enhancement Framework Design and Prospects","publication_year":2026,"publication_date":"2026-03-11","ids":{"openalex":"https://openalex.org/W7164686920","doi":"https://doi.org/10.1145/3803291.3803294"},"language":null,"primary_location":{"id":"doi:10.1145/3803291.3803294","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3803291.3803294","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 9th International Conference on Information and Computer Technologies","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3803291.3803294","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138567738","display_name":"Linxuan Jiang","orcid":"https://orcid.org/0009-0008-2276-5297"},"institutions":[{"id":"https://openalex.org/I90259746","display_name":"Capital University of Economics and Business","ror":"https://ror.org/01r5sf951","country_code":"CN","type":"education","lineage":["https://openalex.org/I90259746"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linxuan Jiang","raw_affiliation_strings":["School of Statistics, Capital University of Economics and Business, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0008-2276-5297","affiliations":[{"raw_affiliation_string":"School of Statistics, Capital University of Economics and Business, Beijing, China","institution_ids":["https://openalex.org/I90259746"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5138580257","display_name":"Yuyang Cheng","orcid":"https://orcid.org/0009-0000-1487-4436"},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuyang Cheng","raw_affiliation_strings":["School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, Guangxi, China"],"raw_orcid":"https://orcid.org/0009-0000-1487-4436","affiliations":[{"raw_affiliation_string":"School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, Guangxi, China","institution_ids":["https://openalex.org/I5343935"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":"73","last_page":"81"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.08730000257492065,"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":0.08730000257492065,"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/T13629","display_name":"Text Readability and Simplification","score":0.07680000364780426,"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/T10465","display_name":"Neurobiology of Language and Bilingualism","score":0.0754999965429306,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.8431000113487244},{"id":"https://openalex.org/keywords/cognitive-architecture","display_name":"Cognitive architecture","score":0.48890000581741333},{"id":"https://openalex.org/keywords/memory-model","display_name":"Memory model","score":0.482699990272522},{"id":"https://openalex.org/keywords/cognition","display_name":"Cognition","score":0.4408000111579895},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.43309998512268066},{"id":"https://openalex.org/keywords/dynamic-random-access-memory","display_name":"Dynamic random-access memory","score":0.3806999921798706},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.34950000047683716}],"concepts":[{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.8431000113487244},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6704000234603882},{"id":"https://openalex.org/C20854674","wikidata":"https://www.wikidata.org/wiki/Q4386060","display_name":"Cognitive architecture","level":3,"score":0.48890000581741333},{"id":"https://openalex.org/C12186640","wikidata":"https://www.wikidata.org/wiki/Q6815743","display_name":"Memory model","level":3,"score":0.482699990272522},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4551999866962433},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.4408000111579895},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.43309998512268066},{"id":"https://openalex.org/C118702147","wikidata":"https://www.wikidata.org/wiki/Q189396","display_name":"Dynamic random-access memory","level":3,"score":0.3806999921798706},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.34950000047683716},{"id":"https://openalex.org/C21963081","wikidata":"https://www.wikidata.org/wiki/Q11337567","display_name":"Working memory","level":3,"score":0.34150001406669617},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.3359000086784363},{"id":"https://openalex.org/C171675096","wikidata":"https://www.wikidata.org/wiki/Q1143380","display_name":"Extended memory","level":4,"score":0.31150001287460327},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.310699999332428},{"id":"https://openalex.org/C161407221","wikidata":"https://www.wikidata.org/wiki/Q4382939","display_name":"Cognitive model","level":3,"score":0.30550000071525574},{"id":"https://openalex.org/C119907115","wikidata":"https://www.wikidata.org/wiki/Q6815725","display_name":"Memory errors","level":3,"score":0.28780001401901245},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.272599995136261},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C83056255","wikidata":"https://www.wikidata.org/wiki/Q2910843","display_name":"Information processing theory","level":3,"score":0.2596000134944916},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2587999999523163}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3803291.3803294","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3803291.3803294","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 9th International Conference on Information and Computer Technologies","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3803291.3803294","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3803291.3803294","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 9th International Conference on Information and Computer Technologies","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.650039553642273,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2049428464","https://openalex.org/W2063392212","https://openalex.org/W2090951600","https://openalex.org/W2130736456","https://openalex.org/W2163569782","https://openalex.org/W2889787757","https://openalex.org/W2963963993","https://openalex.org/W3099215402","https://openalex.org/W4393147158"],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"generally":[4],"face":[5],"the":[6,11,26,33,36,47,56,73,80,91,98,132,156,165,188,191,200,210,215,230,245],"challenge":[7],"of":[8,29,35,49,60,85,135,190,202,212,232,247],"\"lost":[9,213],"in":[10,25,32,52,214,227,253],"middle\"":[12],"when":[13],"dealing":[14],"with":[15,164,255],"long":[16,86,205,224],"contexts,":[17],"which":[18,130],"is":[19,195],"marked":[20],"by":[21,89],"a":[22,105,123,149,179,220,236,240],"substantial":[23],"decrease":[24],"utilization":[27],"efficiency":[28],"key":[30],"information":[31,88],"middle":[34],"document.":[37],"In":[38],"order":[39],"to":[40,55,118,169,186,197],"solve":[41],"this":[42,44,119,161],"problem,":[43],"paper":[45],"introduces":[46],"principle":[48],"human":[50,92,256],"memory":[51,57,68,94,110,126,136,167,172,248],"cognitive":[53,67,162,233,257],"science":[54],"management":[58],"mechanism":[59,163],"LLM.":[61],"We":[62],"have":[63],"proposed":[64],"an":[65],"intelligent":[66],"enhancement":[69,111],"framework":[70,78,194],"based":[71,138],"on":[72,139,204],"Ebbinghaus":[74],"Forgetting":[75],"Curve.":[76],"The":[77],"optimizes":[79],"storage,":[81],"retrieval":[82],"and":[83,96,108,144,174,176,208,239],"forgetting":[84,100,157],"text":[87,206,225],"simulating":[90],"hierarchical":[93],"system":[95],"combining":[97],"dynamic":[99,150,171],"curve":[101],"mechanism,":[102],"thus":[103],"building":[104],"quantifiable,":[106],"predictable":[107],"manageable":[109],"system.":[112],"There":[113],"are":[114,251],"four":[115],"main":[116],"contributions":[117],"work:":[120],"1)":[121],"Introduce":[122],"new":[124,221],"multi-dimensional":[125],"intensity":[127],"quantification":[128],"model,":[129],"evaluates":[131],"intrinsic":[133],"value":[134],"fragments":[137],"their":[140],"emotional":[141],"intensity,":[142],"novelty":[143],"repetition":[145],"frequency;":[146],"2)":[147],"Design":[148],"retention":[151],"rate":[152],"prediction":[153],"algorithm":[154],"using":[155,183],"curve;":[158],"3)":[159],"Combine":[160],"three-layer":[166],"architecture":[168],"achieve":[170],"migration":[173],"update;":[175],"4)":[177],"formulate":[178],"thorough":[180],"experimental":[181],"scheme":[182],"LongBench-E":[184],"benchmarking":[185],"verify":[187],"effectiveness":[189],"framework.":[192],"Our":[193],"expected":[196],"significantly":[198],"improve":[199],"performance":[201],"LLM":[203,228],"tasks":[207],"alleviate":[209],"phenomenon":[211],"middle\".":[216],"This":[217],"study":[218],"establishes":[219],"paradigm":[222],"for":[223,244],"processing":[226],"from":[229],"perspective":[231],"science,":[234],"providing":[235],"theoretical":[237],"basis":[238],"clear":[241],"empirical":[242],"path":[243],"development":[246],"systems":[249],"that":[250],"more":[252],"line":[254],"mechanisms.":[258]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-06-14T00:00:00"}
