{"id":"https://openalex.org/W4416034603","doi":"https://doi.org/10.18653/v1/2025.findings-emnlp.664","title":"Dialectal Toxicity Detection: Evaluating LLM-as-a-Judge Consistency Across Language Varieties","display_name":"Dialectal Toxicity Detection: Evaluating LLM-as-a-Judge Consistency Across Language Varieties","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416034603","doi":"https://doi.org/10.18653/v1/2025.findings-emnlp.664"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2025.findings-emnlp.664","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.664","pdf_url":"https://aclanthology.org/2025.findings-emnlp.664.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":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.findings-emnlp.664.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101827902","display_name":"Fahim Faisal","orcid":"https://orcid.org/0000-0001-9835-6299"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fahim Faisal","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100738190","display_name":"Md. Mushfiqur Rahman","orcid":"https://orcid.org/0000-0003-3010-1198"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Md Mushfiqur Rahman","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5013793053","display_name":"Antonios Anastasopoulos","orcid":"https://orcid.org/0000-0002-8544-246X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Antonios Anastasopoulos","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":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"12429","last_page":"12452"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.3617999851703644,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.3617999851703644,"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":0.19439999759197235,"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":0.10360000282526016,"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/consistency","display_name":"Consistency (knowledge bases)","score":0.6488000154495239},{"id":"https://openalex.org/keywords/variation","display_name":"Variation (astronomy)","score":0.2526000142097473},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.24889999628067017},{"id":"https://openalex.org/keywords/affect","display_name":"Affect (linguistics)","score":0.22450000047683716}],"concepts":[{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6488000154495239},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4537000060081482},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41119998693466187},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3912999927997589},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3328000009059906},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.3172000050544739},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3172000050544739},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.2526000142097473},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.24889999628067017},{"id":"https://openalex.org/C2776035688","wikidata":"https://www.wikidata.org/wiki/Q1606558","display_name":"Affect (linguistics)","level":2,"score":0.22450000047683716}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-emnlp.664","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.664","pdf_url":"https://aclanthology.org/2025.findings-emnlp.664.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":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.findings-emnlp.664","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.664","pdf_url":"https://aclanthology.org/2025.findings-emnlp.664.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":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1262899742","display_name":"Collaborative Research: RI: Small: NL(V)P: Natural Language (Variety) Processing","funder_award_id":"2125466","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416034603.pdf","grobid_xml":"https://content.openalex.org/works/W4416034603.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"There":[0],"has":[1],"been":[2],"little":[3],"systematic":[4],"study":[5],"on":[6,77],"how":[7],"dialectal":[8,30,97],"differences":[9],"affect":[10],"toxicity":[11,49],"detection":[12],"by":[13],"modern":[14],"LLMs.Furthermore,":[15],"although":[16],"using":[17],"LLMs":[18,52,76,92],"as":[19],"evaluators":[20],"(\"LLM-as-a-judge\")":[21],"is":[22,32],"a":[23,47,57],"growing":[24],"research":[25],"area,":[26],"their":[27,78,110],"sensitivity":[28],"to":[29,80,95],"nuances":[31],"still":[33],"underexplored":[34],"and":[35,63,70,86,99],"requires":[36],"more":[37],"focused":[38],"attention.In":[39],"this":[40],"paper,":[41],"we":[42],"address":[43],"these":[44],"gaps":[45],"through":[46,60],"comprehensive":[48],"evaluation":[50],"of":[51],"across":[53],"diverse":[54],"dialects.We":[55],"create":[56],"multi-dialect":[58],"dataset":[59],"synthetic":[61],"transformations":[62],"human-assisted":[64],"translations,":[65],"covering":[66],"10":[67],"language":[68],"clusters":[69],"60":[71],"varieties.We":[72],"then":[73],"evaluate":[74],"five":[75],"ability":[79],"assess":[81],"toxicity,":[82],"measuring":[83],"multilingual,":[84],"dialectal,":[85],"LLMhuman":[87],"consistency.Our":[88],"findings":[89],"show":[90],"that":[91],"are":[93],"sensitive":[94],"both":[96],"shifts":[98],"low-resource":[100],"multilingual":[101],"variation,":[102],"though":[103],"the":[104],"most":[105],"persistent":[106],"challenge":[107],"remains":[108],"aligning":[109],"predictions":[111],"with":[112],"human":[113],"judgments.":[114]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-08T00:00:00"}