{"id":"https://openalex.org/W7165771535","doi":"https://doi.org/10.48550/arxiv.2606.24752","title":"Can Scale Save Us From Plasticity Loss in Large Language Models?","display_name":"Can Scale Save Us From Plasticity Loss in Large Language Models?","publication_year":2026,"publication_date":"2026-06-23","ids":{"openalex":"https://openalex.org/W7165771535","doi":"https://doi.org/10.48550/arxiv.2606.24752"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.24752","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.24752","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"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.2606.24752","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076176197","display_name":"J. Fernando Hernandez-Garcia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hernandez-Garcia, J. Fernando","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125253329","display_name":"Tomas Figliolia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Figliolia, Tom\u00e1s","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5048239223","display_name":"Beren Millidge","orcid":"https://orcid.org/0000-0003-1872-5635"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Millidge, Beren","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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.7896999716758728,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.7896999716758728,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.07010000199079514,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T13629","display_name":"Text Readability and Simplification","score":0.011599999852478504,"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/plasticity","display_name":"Plasticity","score":0.8206999897956848},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.48080000281333923},{"id":"https://openalex.org/keywords/neuroplasticity","display_name":"Neuroplasticity","score":0.4683000147342682},{"id":"https://openalex.org/keywords/phenomenon","display_name":"Phenomenon","score":0.44510000944137573},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.42969998717308044},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42669999599456787},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.40939998626708984}],"concepts":[{"id":"https://openalex.org/C79186407","wikidata":"https://www.wikidata.org/wiki/Q472074","display_name":"Plasticity","level":2,"score":0.8206999897956848},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6001999974250793},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.48080000281333923},{"id":"https://openalex.org/C47611674","wikidata":"https://www.wikidata.org/wiki/Q849491","display_name":"Neuroplasticity","level":2,"score":0.4683000147342682},{"id":"https://openalex.org/C50335755","wikidata":"https://www.wikidata.org/wiki/Q483247","display_name":"Phenomenon","level":2,"score":0.44510000944137573},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.42969998717308044},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42669999599456787},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4131999909877777},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.40939998626708984},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.3743000030517578},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.35740000009536743},{"id":"https://openalex.org/C5687787","wikidata":"https://www.wikidata.org/wiki/Q5889850","display_name":"Homeostatic plasticity","level":5,"score":0.3285999894142151},{"id":"https://openalex.org/C2988416141","wikidata":"https://www.wikidata.org/wiki/Q6031139","display_name":"Information loss","level":2,"score":0.325300008058548},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.31630000472068787},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.29820001125335693},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2515000104904175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.24752","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.24752","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.24752","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.24752","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7753356099128723}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"loss":[1,60,75,96,124,170],"of":[2,7,31,61,94,122,146,168],"plasticity":[3,62,74,95,123,147,169],"-":[4,20],"the":[5,67,120,143,176,179,206],"ability":[6,207],"a":[8,22,64,82,111,126],"network":[9],"to":[10,102,157,160,183,208,211],"learn":[11],"new":[12,212],"information":[13,19],"after":[14,214],"having":[15],"already":[16],"learned":[17],"older":[18],"is":[21,155,181],"fundamental":[23],"challenge":[24],"in":[25,47,54,66,76,218],"creating":[26],"artificial":[27],"neural":[28],"networks":[29],"capable":[30],"continual":[32,84,184,220],"learning.":[33],"Although":[34],"this":[35],"phenomenon":[36,180],"has":[37,43],"been":[38,45],"known":[39],"for":[40],"decades,":[41],"it":[42],"mostly":[44],"studied":[46],"older,":[48],"relatively":[49],"small":[50],"architectures":[51],"and":[52,221],"rarely":[53],"natural-language":[55,202],"domains.":[56],"To":[57],"determine":[58],"whether":[59],"remains":[63],"problem":[65],"modern":[68],"transformer-based":[69],"LLM":[70],"paradigm,":[71],"we":[72,91],"study":[73],"GPT-style":[77],"Transformer":[78,197],"models":[79,98,140,199],"trained":[80,200],"on":[81,110,201],"multilingual":[83,173],"learning":[85,185],"problem.":[86],"Consistent":[87],"with":[88,132,186],"prior":[89],"work,":[90],"find":[92,118,166],"evidence":[93,167],"across":[97],"ranging":[99],"from":[100],"5M":[101],"314M":[103],"non-embedding":[104],"parameters,":[105],"as":[106],"measured":[107],"by":[108],"deterioration":[109],"held-out":[112],"Vietnamese":[113],"probing":[114],"task.":[115],"We":[116,164],"further":[117],"that":[119,138,150,178,194],"onset":[121],"follows":[125],"predictable":[127],"scaling":[128],"law,":[129],"growing":[130],"sublinearly":[131],"model":[133],"size.":[134],"These":[135],"results":[136,192],"suggest":[137,193],"larger":[139],"may":[141],"delay":[142],"measurable":[144],"effects":[145],"loss,":[148],"but":[149],"increasing":[151],"parameter":[152],"count":[153],"alone":[154],"likely":[156],"be":[158],"insufficient":[159],"completely":[161],"prevent":[162],"it.":[163],"also":[165],"under":[171],"stationary":[172,222],"training,":[174,217],"challenging":[175],"view":[177],"exclusive":[182],"abrupt":[187],"task":[188],"changes.":[189],"Overall,":[190],"our":[191],"even":[195],"large":[196],"language":[198],"will":[203],"eventually":[204],"lose":[205],"efficiently":[209],"adapt":[210],"data":[213],"sufficiently":[215],"long":[216],"both":[219],"settings.":[223]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-25T00:00:00"}