{"id":"https://openalex.org/W4416035497","doi":"https://doi.org/10.18653/v1/2025.emnlp-main.1540","title":"FLUID QA: A Multilingual Benchmark for Figurative Language Usage in Dialogue across English, Chinese, and Korean","display_name":"FLUID QA: A Multilingual Benchmark for Figurative Language Usage in Dialogue across English, Chinese, and Korean","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416035497","doi":"https://doi.org/10.18653/v1/2025.emnlp-main.1540"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2025.emnlp-main.1540","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.emnlp-main.1540","pdf_url":"https://aclanthology.org/2025.emnlp-main.1540.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.emnlp-main.1540.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080415861","display_name":"Seoyoon Park","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Seoyoon Park","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020930808","display_name":"HyunJung Choi","orcid":"https://orcid.org/0009-0006-8947-6444"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hyeji Choi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100665021","display_name":"Minseon Kim","orcid":"https://orcid.org/0000-0003-0221-4080"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Minseon Kim","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103053587","display_name":"Subin An","orcid":"https://orcid.org/0009-0007-2921-2284"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Subin An","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063926829","display_name":"Xiaonan Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaonan Wang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111362957","display_name":"Gyuri Choi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gyuri Choi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5109359178","display_name":"Hansaem Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hansaem Kim","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5080415861"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.4958,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.92156487,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"30268","last_page":"30282"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12031","display_name":"Speech and dialogue systems","score":0.32170000672340393,"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/T12031","display_name":"Speech and dialogue systems","score":0.32170000672340393,"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/T11431","display_name":"Action Observation and Synchronization","score":0.13109999895095825,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11148","display_name":"Language, Metaphor, and Cognition","score":0.1216999962925911,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/literal-and-figurative-language","display_name":"Literal and figurative language","score":0.6639999747276306},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.48069998621940613},{"id":"https://openalex.org/keywords/metaphor","display_name":"Metaphor","score":0.3433000147342682},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.31369999051094055},{"id":"https://openalex.org/keywords/language-understanding","display_name":"Language understanding","score":0.311599999666214},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.30230000615119934}],"concepts":[{"id":"https://openalex.org/C46182478","wikidata":"https://www.wikidata.org/wiki/Q7363315","display_name":"Literal and figurative language","level":2,"score":0.6639999747276306},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6158999800682068},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.5888000130653381},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5302000045776367},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5241000056266785},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.48069998621940613},{"id":"https://openalex.org/C2778311575","wikidata":"https://www.wikidata.org/wiki/Q18534","display_name":"Metaphor","level":2,"score":0.3433000147342682},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.31369999051094055},{"id":"https://openalex.org/C2983448237","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Language understanding","level":2,"score":0.311599999666214},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.30230000615119934},{"id":"https://openalex.org/C155092808","wikidata":"https://www.wikidata.org/wiki/Q182557","display_name":"Computational linguistics","level":2,"score":0.2992999851703644},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2687000036239624}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.emnlp-main.1540","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.emnlp-main.1540","pdf_url":"https://aclanthology.org/2025.emnlp-main.1540.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.emnlp-main.1540","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.emnlp-main.1540","pdf_url":"https://aclanthology.org/2025.emnlp-main.1540.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321314","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416035497.pdf","grobid_xml":"https://content.openalex.org/works/W4416035497.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Figurative":[0],"language":[1,16],"conveys":[2],"stance,":[3],"emotion,":[4],"and":[5,55,91,98],"social":[6],"nuance,":[7],"making":[8],"its":[9],"appropriate":[10],"use":[11,32],"essential":[12],"in":[13,21,35,50,89],"dialogue.While":[14],"large":[15],"models":[17,77],"(LLMs)":[18],"often":[19],"succeed":[20],"recognizing":[22],"figurative":[23,48,59,110],"expressions":[24],"at":[25],"the":[26,42],"sentence":[27],"level,":[28],"their":[29],"ability":[30],"to":[31],"them":[33],"coherently":[34],"conversation":[36],"remains":[37],"uncertain.We":[38],"introduce":[39],"FLUID":[40,86],"QA,":[41,87],"first":[43],"multilingual":[44],"benchmark":[45],"that":[46,78],"evaluates":[47],"usage":[49],"dialogue":[51],"across":[52,112],"English,":[53],"Korean,":[54],"Chinese.Each":[56],"item":[57],"embeds":[58],"choices":[60],"into":[61],"multi-turn":[62],"contexts.To":[63],"support":[64],"interpretation,":[65],"we":[66],"include":[67],"FLUTE-bi,":[68],"a":[69,74,104],"sentence-level":[70],"diagnostic":[71],"task.Results":[72],"reveal":[73],"persistent":[75],"gap:":[76],"perform":[79],"well":[80],"on":[81,85],"FLUTE-bi":[82],"frequently":[83],"fail":[84],"especially":[88],"sarcasm":[90],"metaphor.These":[92],"errors":[93],"reflect":[94],"systematic":[95],"rhetorical":[96],"confusion":[97],"limited":[99],"discourse":[100],"reasoning.FLUID":[101],"QA":[102],"provides":[103],"scalable":[105],"framework":[106],"for":[107],"assessing":[108],"usage-level":[109],"competence":[111],"languages.":[113]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-28T08:17:26.163206","created_date":"2025-11-08T00:00:00"}