{"id":"https://openalex.org/W4412887842","doi":"https://doi.org/10.18653/v1/2025.findings-acl.929","title":"FactLens: Benchmarking Fine-Grained Fact Verification","display_name":"FactLens: Benchmarking Fine-Grained Fact Verification","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412887842","doi":"https://doi.org/10.18653/v1/2025.findings-acl.929"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.findings-acl.929","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.929","pdf_url":"https://aclanthology.org/2025.findings-acl.929.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: ACL 2025","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.findings-acl.929.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114230565","display_name":"Kushan Mitra","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kushan Mitra","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057103463","display_name":"Dan Zhang","orcid":"https://orcid.org/0000-0002-6330-0217"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dan Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040390469","display_name":"Sajjadur Rahman","orcid":"https://orcid.org/0000-0003-4210-1582"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sajjadur Rahman","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5056213327","display_name":"Estevam Hruschka","orcid":"https://orcid.org/0000-0003-1499-2808"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Estevam Hruschka","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7588,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.87748137,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"18085","last_page":"18096"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10215","display_name":"Semantic Web and Ontologies","score":0.9675999879837036,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9675999879837036,"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/T11986","display_name":"Scientific Computing and Data Management","score":0.9574999809265137,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9419999718666077,"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/benchmarking","display_name":"Benchmarking","score":0.8946409225463867},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6953386664390564},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.0697380006313324}],"concepts":[{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.8946409225463867},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6953386664390564},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0697380006313324},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-acl.929","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.929","pdf_url":"https://aclanthology.org/2025.findings-acl.929.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: ACL 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.findings-acl.929","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.929","pdf_url":"https://aclanthology.org/2025.findings-acl.929.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: ACL 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":0.46000000834465027,"display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412887842.pdf","grobid_xml":"https://content.openalex.org/works/W4412887842.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W2059640416","https://openalex.org/W1490753184","https://openalex.org/W2284465472","https://openalex.org/W2291782699"],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"have":[4],"shown":[5],"impressive":[6],"capability":[7],"in":[8,90],"language":[9],"generation":[10],"and":[11,18,30,87,101,124,147,150],"understanding,":[12],"but":[13],"their":[14],"tendency":[15],"to":[16,49,107,135],"hallucinate":[17],"produce":[19],"factually":[20],"incorrect":[21],"information":[22],"remains":[23],"a":[24,45,61,115],"key":[25],"limitation.To":[26],"verify":[27],"LLM-generated":[28],"contents":[29],"claims":[31,68],"from":[32],"other":[33],"sources,":[34],"traditional":[35],"verification":[36,161],"approaches":[37],"often":[38],"rely":[39],"on":[40,158],"holistic":[41],"models":[42],"that":[43],"assign":[44],"single":[46],"factuality":[47],"label":[48],"complex":[50,67],"claims,":[51],"potentially":[52],"obscuring":[53],"nuanced":[54],"errors.In":[55],"this":[56],"paper,":[57],"we":[58,151],"advocate":[59],"for":[60,75,79,117],"shift":[62],"towards":[63],"fine-grained":[64,119],"verification,":[65,77,121],"where":[66],"are":[69],"broken":[70],"down":[71],"into":[72],"smaller":[73],"sub-claims":[74,94],"individual":[76],"allowing":[78],"more":[80],"precise":[81],"identification":[82],"of":[83,127,155],"inaccuracies,":[84],"improved":[85],"transparency,":[86],"reduced":[88],"ambiguity":[89],"evidence":[91],"retrieval.However,":[92],"generating":[93],"poses":[95],"challenges,":[96],"such":[97],"as":[98],"maintaining":[99],"context":[100],"ensuring":[102],"semantic":[103],"equivalence":[104],"with":[105,122],"respect":[106],"the":[108,153,159],"original":[109],"claim.We":[110],"introduce":[111],"FactLens":[112,145],"1":[113],",":[114],"benchmark":[116,130],"evaluating":[118],"fact":[120],"metrics":[123],"automated":[125,144],"evaluators":[126,146],"sub-claim":[128,156],"quality.The":[129],"data":[131],"is":[132],"manually":[133],"curated":[134],"ensure":[136],"high-quality":[137],"ground":[138],"truth.Our":[139],"results":[140],"show":[141],"alignment":[142],"between":[143],"human":[148],"judgments,":[149],"discuss":[152],"impact":[154],"characteristics":[157],"overall":[160],"performance.":[162]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}