{"id":"https://openalex.org/W7164919513","doi":"https://doi.org/10.48550/arxiv.2606.15643","title":"Extending Item Response Theory for Efficient and Meaningful Multilingual Evaluation","display_name":"Extending Item Response Theory for Efficient and Meaningful Multilingual Evaluation","publication_year":2026,"publication_date":"2026-06-14","ids":{"openalex":"https://openalex.org/W7164919513","doi":"https://doi.org/10.48550/arxiv.2606.15643"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.15643","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.15643","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.15643","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092031150","display_name":"Gili Lior","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lior, Gili","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008910283","display_name":"Tzviel Frostig","orcid":"https://orcid.org/0000-0003-2761-8380"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Frostig, Tzviel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138726871","display_name":"Gabriel Stanovsky","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stanovsky, Gabriel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5035283714","display_name":"Matan Eyal","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eyal, Matan","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/T10467","display_name":"Psychometric Methodologies and Testing","score":0.6621000170707703,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10467","display_name":"Psychometric Methodologies and Testing","score":0.6621000170707703,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.08259999752044678,"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":0.03290000185370445,"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/conflation","display_name":"Conflation","score":0.6937999725341797},{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.5256999731063843},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5249000191688538},{"id":"https://openalex.org/keywords/item-response-theory","display_name":"Item response theory","score":0.44679999351501465},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.3756999969482422},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.3598000109195709},{"id":"https://openalex.org/keywords/binary-data","display_name":"Binary data","score":0.30379998683929443}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7056000232696533},{"id":"https://openalex.org/C130440534","wikidata":"https://www.wikidata.org/wiki/Q14946528","display_name":"Conflation","level":2,"score":0.6937999725341797},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6492000222206116},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5559999942779541},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.5256999731063843},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5249000191688538},{"id":"https://openalex.org/C19875794","wikidata":"https://www.wikidata.org/wiki/Q1207340","display_name":"Item response theory","level":3,"score":0.44679999351501465},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.3756999969482422},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3598000109195709},{"id":"https://openalex.org/C2779190172","wikidata":"https://www.wikidata.org/wiki/Q4913888","display_name":"Binary data","level":3,"score":0.30379998683929443},{"id":"https://openalex.org/C2780035574","wikidata":"https://www.wikidata.org/wiki/Q30081","display_name":"Multilingualism","level":2,"score":0.3003999888896942},{"id":"https://openalex.org/C106347477","wikidata":"https://www.wikidata.org/wiki/Q5384228","display_name":"Equating","level":3,"score":0.289900004863739},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.2727999985218048},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27239999175071716},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.26429998874664307},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.25189998745918274},{"id":"https://openalex.org/C2986587452","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical analysis","level":2,"score":0.2506999969482422},{"id":"https://openalex.org/C155092808","wikidata":"https://www.wikidata.org/wiki/Q182557","display_name":"Computational linguistics","level":2,"score":0.25060001015663147}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.15643","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.15643","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.15643","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.15643","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":"Preprint"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7479299902915955,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multilingual":[0],"benchmarks":[1],"are":[2,32],"central":[3],"to":[4],"evaluating":[5],"large":[6],"language":[7,69],"models":[8],"(LLMs)":[9],"across":[10,80,116],"languages,":[11,26,120,129],"but":[12],"they":[13],"suffer":[14],"from":[15,68],"three":[16,48,92],"issues:":[17],"exhaustive":[18],"evaluation":[19],"scales":[20],"linearly":[21],"with":[22,49,60,101],"the":[23,107],"number":[24],"of":[25,83],"automatic":[27],"translation":[28,113],"introduces":[29],"errors":[30,114],"that":[31,87,134],"easily":[33],"missed":[34],"at":[35],"scale,":[36],"and":[37,42,71,130],"some":[38],"items":[39,133],"conflate":[40],"general":[41],"culture-specific":[43,132],"knowledge.":[44],"We":[45],"address":[46],"all":[47,117],"a":[50,127],"unified":[51],"statistical":[52],"framework,":[53],"Multilingual-IRT,":[54],"which":[55],"extends":[56],"Item":[57],"Response":[58],"Theory":[59],"per-language":[61,72],"difficulty":[62],"deviations,":[63],"split":[64],"discriminability":[65],"separating":[66],"content":[67],"effects,":[70],"ability":[73],"residuals.":[74],"Fitting":[75],"Multilingual-IRT":[76],"on":[77],"25":[78],"LLMs":[79],"29":[81],"languages":[82],"MMLU-Pro-X,":[84],"we":[85],"show":[86],"its":[88],"fitted":[89],"parameters":[90],"support":[91],"practical":[93],"applications:":[94],"predicting":[95],"unobserved":[96],"(item,":[97],"LLM,":[98],"language)":[99],"instances":[100],"11-16%":[102],"lower":[103],"binary":[104],"cross-entropy":[105],"than":[106],"strongest":[108],"accuracy-based":[109,122,135],"baseline,":[110],"surfacing":[111],"candidate":[112],"distributed":[115],"28":[118],"non-English":[119],"whereas":[121],"baselines":[123,136],"concentrate":[124],"detections":[125],"in":[126],"few":[128],"recovering":[131],"miss.":[137]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-17T00:00:00"}
