{"id":"https://openalex.org/W7138849739","doi":"https://doi.org/10.48550/arxiv.2603.17912","title":"Pretrained Multilingual Transformers Reveal Quantitative Distance Between Human Languages","display_name":"Pretrained Multilingual Transformers Reveal Quantitative Distance Between Human Languages","publication_year":2026,"publication_date":"2026-03-18","ids":{"openalex":"https://openalex.org/W7138849739","doi":"https://doi.org/10.48550/arxiv.2603.17912"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.17912","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17912","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":null,"license_id":null,"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.2603.17912","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130007262","display_name":"Yue Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhao, Yue","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130109997","display_name":"Jiatao Gu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Jiatao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029729156","display_name":"Paloma Jereti\u010d","orcid":"https://orcid.org/0000-0003-4680-8577"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jereti\u010d, Paloma","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129834705","display_name":"Weijie Su","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Su, Weijie","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5130007262"],"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/T12090","display_name":"Language and cultural evolution","score":0.779699981212616,"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"}},"topics":[{"id":"https://openalex.org/T12090","display_name":"Language and cultural evolution","score":0.779699981212616,"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"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.0843999981880188,"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/T12380","display_name":"Authorship Attribution and Profiling","score":0.01590000092983246,"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/fidelity","display_name":"Fidelity","score":0.5468000173568726},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.4350999891757965},{"id":"https://openalex.org/keywords/tracing","display_name":"Tracing","score":0.43290001153945923},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.42910000681877136},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4117000102996826},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.3928000032901764},{"id":"https://openalex.org/keywords/distance-measures","display_name":"Distance measures","score":0.3889000117778778}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7085000276565552},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5810999870300293},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.5468000173568726},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5268999934196472},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.4350999891757965},{"id":"https://openalex.org/C138673069","wikidata":"https://www.wikidata.org/wiki/Q322229","display_name":"Tracing","level":2,"score":0.43290001153945923},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.42910000681877136},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4117000102996826},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.3928000032901764},{"id":"https://openalex.org/C2639959","wikidata":"https://www.wikidata.org/wiki/Q1344778","display_name":"Distance measures","level":2,"score":0.3889000117778778},{"id":"https://openalex.org/C155092808","wikidata":"https://www.wikidata.org/wiki/Q182557","display_name":"Computational linguistics","level":2,"score":0.366100013256073},{"id":"https://openalex.org/C197902243","wikidata":"https://www.wikidata.org/wiki/Q23718","display_name":"Cardinal direction","level":2,"score":0.33869999647140503},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.31279999017715454},{"id":"https://openalex.org/C2780035574","wikidata":"https://www.wikidata.org/wiki/Q30081","display_name":"Multilingualism","level":2,"score":0.30239999294281006},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.2996000051498413},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2838999927043915},{"id":"https://openalex.org/C5349765","wikidata":"https://www.wikidata.org/wiki/Q5282866","display_name":"Distance matrices in phylogeny","level":2,"score":0.2680000066757202}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.17912","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17912","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.17912","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17912","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6014106273651123,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Understanding":[0],"the":[1,63,101,121],"distance":[2,37,103],"between":[3,104],"human":[4,13],"languages":[5,105],"is":[6],"central":[7],"to":[8,34,110],"linguistics,":[9],"anthropology,":[10],"and":[11,30,91,113,131,137],"tracing":[12],"evolutionary":[14],"history.":[15],"Yet,":[16],"while":[17],"linguistics":[18],"has":[19],"long":[20],"provided":[21],"rich":[22],"qualitative":[23],"accounts":[24],"of":[25,68,76,116],"cross-linguistic":[26,77],"variation,":[27],"a":[28,45,72,111,144,156],"unified":[29],"scalable":[31],"quantitative":[32,176],"approach":[33],"measuring":[35,92],"language":[36,51],"remains":[38],"lacking.":[39],"In":[40],"this":[41],"paper,":[42],"we":[43,60,99,118],"introduce":[44],"method":[46],"that":[47,62,120],"leverages":[48],"pretrained":[49],"multilingual":[50,170,182],"models":[52,70,171],"as":[53,88,143],"systematic":[54],"instruments":[55],"for":[56,159,175],"linguistic":[57,126,161,177],"measurement.":[58],"Specifically,":[59],"show":[61],"spontaneously":[64],"emerged":[65],"attention":[66,86],"mechanisms":[67],"these":[69],"provide":[71],"robust,":[73],"tokenization-agnostic":[74],"measure":[75],"distance,":[78],"termed":[79],"Attention":[80],"Transport":[81],"Distance":[82],"(ATD).":[83],"By":[84],"treating":[85],"matrices":[87],"probability":[89],"distributions":[90],"their":[93],"geometric":[94],"divergence":[95],"via":[96],"optimal":[97],"transport,":[98],"quantify":[100],"representational":[102],"during":[106],"translation.":[107,152],"Applying":[108],"ATD":[109,142],"large":[112],"diverse":[114],"set":[115],"languages,":[117],"demonstrate":[119],"resulting":[122],"distances":[123],"recover":[124],"established":[125],"groupings":[127],"with":[128,135],"high":[129],"fidelity":[130],"reveal":[132],"patterns":[133],"aligned":[134],"geographic":[136],"contact-induced":[138],"relationships.":[139],"Furthermore,":[140],"incorporating":[141],"regularizer":[145],"improves":[146],"transfer":[147],"performance":[148],"in":[149],"low-resource":[150],"machine":[151],"Our":[153],"results":[154],"establish":[155],"principled":[157],"foundation":[158],"testing":[160],"hypotheses":[162],"using":[163],"artificial":[164],"neural":[165],"networks.":[166],"This":[167],"framework":[168],"transforms":[169],"into":[172],"powerful":[173],"tools":[174],"discovery,":[178],"facilitating":[179],"more":[180],"equitable":[181],"AI.":[183]},"counts_by_year":[],"updated_date":"2026-03-20T20:54:20.808490","created_date":"2026-03-20T00:00:00"}