{"id":"https://openalex.org/W4411549757","doi":"https://doi.org/10.1145/3701716.3715567","title":"Cross-Lingual Text Classification with Large Language Models","display_name":"Cross-Lingual Text Classification with Large Language Models","publication_year":2025,"publication_date":"2025-05-08","ids":{"openalex":"https://openalex.org/W4411549757","doi":"https://doi.org/10.1145/3701716.3715567"},"language":"en","primary_location":{"id":"doi:10.1145/3701716.3715567","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3701716.3715567","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3701716.3715567","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3701716.3715567","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102741786","display_name":"Bin Han","orcid":"https://orcid.org/0000-0002-5280-9456"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Bin Han","raw_affiliation_strings":["University of Washington, Seattle, Washington, USA"],"affiliations":[{"raw_affiliation_string":"University of Washington, Seattle, Washington, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109466230","display_name":"Seung Ji Yang","orcid":"https://orcid.org/0000-0003-3239-9645"},"institutions":[{"id":"https://openalex.org/I4210134091","display_name":"Yahoo (United States)","ror":"https://ror.org/040dkzz12","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134091"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sean T. Yang","raw_affiliation_strings":["Yahoo Research, Sunnyvale, California, USA"],"affiliations":[{"raw_affiliation_string":"Yahoo Research, Sunnyvale, California, USA","institution_ids":["https://openalex.org/I4210134091"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044096493","display_name":"Christopher C. LuVogt","orcid":"https://orcid.org/0009-0002-2567-1305"},"institutions":[{"id":"https://openalex.org/I4210134091","display_name":"Yahoo (United States)","ror":"https://ror.org/040dkzz12","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134091"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christopher LuVogt","raw_affiliation_strings":["Yahoo Research, Sunnyvale, California, USA"],"affiliations":[{"raw_affiliation_string":"Yahoo Research, Sunnyvale, California, USA","institution_ids":["https://openalex.org/I4210134091"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102741786"],"corresponding_institution_ids":["https://openalex.org/I201448701"],"apc_list":null,"apc_paid":null,"fwci":2.7855,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.91067186,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1005","last_page":"1008"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9991000294685364,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9975000023841858,"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/computer-science","display_name":"Computer science","score":0.7761207818984985},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6758197546005249},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5927943587303162}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7761207818984985},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6758197546005249},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5927943587303162}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3701716.3715567","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3701716.3715567","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3701716.3715567","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3701716.3715567","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3701716.3715567","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3701716.3715567","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.7599999904632568,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411549757.pdf","grobid_xml":"https://content.openalex.org/works/W4411549757.grobid-xml"},"referenced_works_count":6,"referenced_works":["https://openalex.org/W3100880133","https://openalex.org/W3198651167","https://openalex.org/W4378509449","https://openalex.org/W4385571470","https://openalex.org/W4389520692","https://openalex.org/W4399116034"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Cross-lingual":[0],"text":[1,15,74],"classification":[2,75,145],"involves":[3],"using":[4,77],"a":[5,116],"model":[6,71,128],"trained":[7],"on":[8,72,120],"data":[9,27],"in":[10,16,21,30,52,129,146],"one":[11,68],"language":[12,35,50,65,113,141],"to":[13],"classify":[14],"another,":[17],"which":[18],"is":[19,28],"crucial":[20],"global":[22],"web":[23],"applications":[24],"where":[25],"labeled":[26],"scarce":[29],"certain":[31],"languages.":[32],"Although":[33],"multilingual":[34],"models":[36,51,66,114,142],"have":[37],"been":[38],"leveraged":[39],"for":[40,143],"such":[41],"tasks,":[42],"few":[43],"studies":[44],"investigate":[45],"the":[46,60,104,125,137],"ability":[47],"of":[48,62,139],"large":[49,64,112,140],"cross-lingual":[53,73,144],"classification.":[54],"In":[55],"this":[56],"paper,":[57],"we":[58],"evaluate":[59],"performance":[61,118],"four":[63],"and":[67,91,103],"smaller":[69],"encoder-only":[70,127],"tasks":[76],"two":[78],"benchmark":[79],"datasets.":[80],"We":[81],"assess":[82],"three":[83],"task":[84],"settings-direct-test":[85],"without":[86],"fine-tuning,":[87,90],"direct-test":[88],"with":[89,93],"translate-test":[92,105],"fine-tuning.":[94],"Our":[95],"findings":[96],"demonstrate":[97],"that":[98],"fine-tuning":[99],"consistently":[100],"improves":[101],"performance,":[102],"method":[106],"slightly":[107],"outperforms":[108],"others.":[109],"Furthermore,":[110],"while":[111],"experience":[115],"slight":[117],"drop":[119],"non-English":[121],"languages,":[122],"they":[123],"outperform":[124],"baseline":[126],"many":[130],"cases.":[131],"This":[132],"study":[133],"provides":[134],"insights":[135],"into":[136],"effectiveness":[138],"practical":[147],"applications.":[148]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}
