{"id":"https://openalex.org/W7148819840","doi":"https://doi.org/10.48550/arxiv.2604.01404","title":"Friends and Grandmothers in Silico: Localizing Entity Cells in Language Models","display_name":"Friends and Grandmothers in Silico: Localizing Entity Cells in Language Models","publication_year":2026,"publication_date":"2026-04-01","ids":{"openalex":"https://openalex.org/W7148819840","doi":"https://doi.org/10.48550/arxiv.2604.01404"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.01404","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01404","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.2604.01404","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5093903005","display_name":"Itay Yona","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yona, Itay","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132877845","display_name":"Dan Barzilay","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Barzilay, Dan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014354323","display_name":"Michael Karasik","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Karasik, Michael","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5132895773","display_name":"Mor Geva","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Geva, Mor","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":0.7613999843597412,"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":0.7613999843597412,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.04039999842643738,"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/T12090","display_name":"Language and cultural evolution","score":0.024299999698996544,"subfield":{"id":"https://openalex.org/subfields/3316","display_name":"Cultural Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.6866000294685364},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6013000011444092},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5940999984741211},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.5454999804496765},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.508400022983551},{"id":"https://openalex.org/keywords/language-understanding","display_name":"Language understanding","score":0.3553999960422516}],"concepts":[{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.6866000294685364},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6510999798774719},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6013000011444092},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5940999984741211},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.5454999804496765},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5342000126838684},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.508400022983551},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.492000013589859},{"id":"https://openalex.org/C2983448237","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Language understanding","level":2,"score":0.3553999960422516},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.322299987077713},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.30570000410079956},{"id":"https://openalex.org/C46312422","wikidata":"https://www.wikidata.org/wiki/Q11024","display_name":"Communication","level":1,"score":0.28690001368522644},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.2824999988079071},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2587999999523163}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.01404","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01404","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.2604.01404","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01404","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":[{"id":"https://metadata.un.org/sdg/4","score":0.4126158058643341,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"How":[0],"do":[1],"language":[2,210],"models":[3,72],"retrieve":[4],"entity-specific":[5],"facts":[6],"from":[7,146],"their":[8],"parameters?":[9],"We":[10,48],"investigate":[11],"this":[12,68],"question":[13],"by":[14,27,53,94],"searching":[15],"for":[16,57,117,136,202],"sparse,":[17],"entity-selective":[18],"MLP":[19,55],"neurons":[20,56,83],"-":[21,36,139],"which":[22],"we":[23,104],"call":[24],"entity":[25,51,120,143,172,191],"cells,":[26],"analogy":[28],"to":[29,132,186,218],"the":[30,64,95,106,142,147],"\"grandmother":[31],"cell\"":[32],"hypothesis":[33],"in":[34,45,86,189,209,221],"neuroscience":[35,222],"and":[37,125,158,162,205,212],"testing":[38],"whether":[39],"they":[40,169],"play":[41],"a":[42,74,101,111,127,214],"causal":[43,108],"role":[44],"factual":[46,207],"recall.":[47],"localize":[49],"candidate":[50],"cells":[52,151],"ranking":[54],"activation":[58],"consistency":[59],"across":[60,70,182],"varied":[61],"prompts":[62],"about":[63,223],"same":[65,150],"entity,":[66],"applying":[67],"procedure":[69],"seven":[71],"on":[73],"curated":[75],"subset":[76],"of":[77,226],"PopQA.":[78],"In":[79],"all":[80],"models,":[81,211],"localized":[82,112],"cluster":[84],"predominantly":[85],"early":[87],"layers,":[88],"an":[89],"empirical":[90,216],"pattern":[91],"not":[92],"imposed":[93],"architecture.":[96],"Using":[97],"Qwen2.5-7B":[98],"base":[99],"as":[100],"model":[102,183],"organism,":[103],"find":[105],"clearest":[107],"evidence:":[109],"suppressing":[110],"cell":[113,129],"selectively":[114],"erases":[115],"recall":[116],"its":[118],"matched":[119],"while":[121],"leaving":[122],"others":[123],"intact,":[124],"activating":[126],"single":[128],"is":[130,144,193],"sufficient":[131],"recover":[133],"correct":[134],"knowledge":[135,192,208],"most":[137],"entities":[138],"even":[140],"when":[141],"absent":[145],"context.":[148],"The":[149],"are":[152],"recovered":[153],"under":[154],"aliases,":[155],"acronyms,":[156],"misspellings,":[157],"multilingual":[159],"surface":[160,176],"forms,":[161],"remain":[163],"stable":[164],"through":[165],"instruction":[166],"tuning,":[167],"suggesting":[168],"encode":[170],"canonical":[171],"identity":[173],"rather":[174],"than":[175],"token":[177],"patterns.":[178],"Causal":[179],"signals":[180],"vary":[181],"families,":[184],"pointing":[185],"architectural":[187],"differences":[188],"how":[190],"organized.":[194],"These":[195],"findings":[196],"offer":[197],"concrete,":[198],"interpretable":[199],"access":[200],"points":[201],"understanding,":[203],"controlling,":[204],"correcting":[206],"draw":[213],"surprising":[215],"parallel":[217],"longstanding":[219],"questions":[220],"sparse":[224],"coding":[225],"concepts.":[227]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-04T00:00:00"}