{"id":"https://openalex.org/W4386804040","doi":"https://doi.org/10.1007/978-3-031-43418-1_25","title":"Neural Models for\u00a0Factual Inconsistency Classification with\u00a0Explanations","display_name":"Neural Models for\u00a0Factual Inconsistency Classification with\u00a0Explanations","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4386804040","doi":"https://doi.org/10.1007/978-3-031-43418-1_25"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-031-43418-1_25","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-031-43418-1_25","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1007/978-3-031-43418-1_25","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016540479","display_name":"Tathagata Raha","orcid":null},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Tathagata Raha","raw_affiliation_strings":["IIIT-Hyderabad, Hyderabad, India"],"affiliations":[{"raw_affiliation_string":"IIIT-Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I65181880"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069473673","display_name":"Mukund Choudhary","orcid":null},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Mukund Choudhary","raw_affiliation_strings":["IIIT-Hyderabad, Hyderabad, India"],"affiliations":[{"raw_affiliation_string":"IIIT-Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I65181880"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104130741","display_name":"Abhinav Menon","orcid":null},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Abhinav Menon","raw_affiliation_strings":["IIIT-Hyderabad, Hyderabad, India"],"affiliations":[{"raw_affiliation_string":"IIIT-Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I65181880"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008465855","display_name":"Harshit Gupta","orcid":"https://orcid.org/0000-0002-2910-9072"},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Harshit Gupta","raw_affiliation_strings":["IIIT-Hyderabad, Hyderabad, India"],"affiliations":[{"raw_affiliation_string":"IIIT-Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I65181880"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086708404","display_name":"KV Aditya Srivatsa","orcid":"https://orcid.org/0000-0002-7583-7580"},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"K. V. Aditya Srivatsa","raw_affiliation_strings":["IIIT-Hyderabad, Hyderabad, India"],"affiliations":[{"raw_affiliation_string":"IIIT-Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I65181880"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046755750","display_name":"Manish Gupta","orcid":"https://orcid.org/0000-0002-2843-3110"},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]},{"id":"https://openalex.org/I4210162141","display_name":"Microsoft (India)","ror":"https://ror.org/04ww0w091","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210162141"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Manish Gupta","raw_affiliation_strings":["IIIT-Hyderabad, Hyderabad, India","Microsoft, Hyderabad, India"],"affiliations":[{"raw_affiliation_string":"IIIT-Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I65181880"]},{"raw_affiliation_string":"Microsoft, Hyderabad, India","institution_ids":["https://openalex.org/I4210162141"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073786634","display_name":"Vasudeva Varma","orcid":"https://orcid.org/0000-0003-1923-1725"},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vasudeva Varma","raw_affiliation_strings":["IIIT-Hyderabad, Hyderabad, India"],"affiliations":[{"raw_affiliation_string":"IIIT-Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I65181880"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5046755750"],"corresponding_institution_ids":["https://openalex.org/I4210162141","https://openalex.org/I65181880"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":{"value":5000,"currency":"EUR","value_usd":5392},"fwci":2.0827,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.88605809,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"410","last_page":"427"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9919999837875366,"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/T10260","display_name":"Software Engineering Research","score":0.9894000291824341,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.8585871458053589},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.7079271078109741},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6417855024337769},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.5686776041984558},{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.5438145399093628},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5295834541320801},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5115721821784973},{"id":"https://openalex.org/keywords/natural-language-generation","display_name":"Natural language generation","score":0.4710887372493744},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.47038355469703674},{"id":"https://openalex.org/keywords/natural-language-understanding","display_name":"Natural language understanding","score":0.46055734157562256},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.4410560131072998},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"Knowledge base","score":0.4390254616737366},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.41594916582107544},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3436095118522644}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8585871458053589},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7079271078109741},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6417855024337769},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.5686776041984558},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.5438145399093628},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5295834541320801},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5115721821784973},{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.4710887372493744},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.47038355469703674},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.46055734157562256},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.4410560131072998},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.4390254616737366},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.41594916582107544},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3436095118522644}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-031-43418-1_25","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-031-43418-1_25","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.1007/978-3-031-43418-1_25","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-031-43418-1_25","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6700000166893005}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1532503642","https://openalex.org/W1840435438","https://openalex.org/W2282821441","https://openalex.org/W2339329611","https://openalex.org/W2768957049","https://openalex.org/W2788403449","https://openalex.org/W2941681871","https://openalex.org/W2954646118","https://openalex.org/W2963846996","https://openalex.org/W2963961878","https://openalex.org/W2971034336","https://openalex.org/W2981852735","https://openalex.org/W3034188538","https://openalex.org/W3034383590","https://openalex.org/W3034850762","https://openalex.org/W3034999214","https://openalex.org/W3035317050","https://openalex.org/W3035628711","https://openalex.org/W3099080236","https://openalex.org/W3107647534","https://openalex.org/W3117745048","https://openalex.org/W3141940864","https://openalex.org/W3153193605","https://openalex.org/W3153947101","https://openalex.org/W3154685255","https://openalex.org/W3173343821","https://openalex.org/W3214464111","https://openalex.org/W4205179624","https://openalex.org/W6600195168","https://openalex.org/W6702248584","https://openalex.org/W6739901393","https://openalex.org/W6763240421","https://openalex.org/W6778883912","https://openalex.org/W6810143613","https://openalex.org/W6810242208"],"related_works":["https://openalex.org/W4214678372","https://openalex.org/W1605559518","https://openalex.org/W4214601164","https://openalex.org/W3134247745","https://openalex.org/W4226243593","https://openalex.org/W3172691639","https://openalex.org/W2963582704","https://openalex.org/W4285816982","https://openalex.org/W3034800807","https://openalex.org/W4287758468"],"abstract_inverted_index":{"Factual":[0],"consistency":[1],"is":[2,15,37,152,230],"one":[3],"of":[4,62,78,103,130,141,171,261],"the":[5,144,252,270,275],"most":[6],"important":[7,17],"requirements":[8],"when":[9],"editing":[10],"high":[11],"quality":[12],"documents.":[13],"It":[14],"extremely":[16],"for":[18,265],"automatic":[19],"text":[20],"generation":[21],"systems":[22],"like":[23],"summarization,":[24],"question":[25],"answering,":[26],"dialog":[27],"modeling,":[28],"and":[29,75,134,139,160,200,214,216,224,247,277],"language":[30,64,240],"modeling.":[31],"Still,":[32],"automated":[33],"factual":[34,79,104],"inconsistency":[35,145,177,222,229,266],"detection":[36],"rather":[38],"under-studied.":[39],"Existing":[40],"work":[41,72,95],"has":[42,69],"focused":[43],"on":[44,73,107],"(a)":[45],"finding":[46],"fake":[47],"news":[48],"keeping":[49],"a":[50,112,169,182,258],"knowledge":[51,85],"base":[52,86],"in":[53,81,87,96],"context,":[54],"or":[55],"(b)":[56],"detecting":[57,74],"broad":[58],"contradiction":[59],"(as":[60],"part":[61],"natural":[63,239],"inference":[65],"literature).":[66],"However,":[67],"there":[68],"been":[70],"no":[71],"explaining":[76],"types":[77,102,223,227],"inconsistencies":[80],"text,":[82],"without":[83],"any":[84],"context.":[88],"In":[89],"this":[90,108,165],"paper,":[91],"we":[92,110,163],"leverage":[93,164],"existing":[94],"linguistics":[97],"to":[98,147,167,175,220,232],"formally":[99],"define":[100],"five":[101,271],"inconsistencies.":[105],"Based":[106],"categorization,":[109],"contribute":[111],"novel":[113],"dataset,":[114],"FICLE":[115],"(Factual":[116],"Inconsistency":[117],"CLassification":[118],"with":[119,121,137,179,236],"Explanation),":[120],"$$\\sim":[122,262],"$$":[123,263],"8K":[124],"samples":[125],"where":[126],"each":[127],"sample":[128],"consists":[129],"two":[131,157],"sentences":[132],"(claim":[133],"context)":[135,184],"annotated":[136],"type":[138,178,267],"span":[140],"inconsistency.":[142],"When":[143],"relates":[146],"an":[148],"entity":[149,203,226],"type,":[150],"it":[151],"labeled":[153],"as":[154,242,244],"well":[155,243],"at":[156],"levels":[158],"(coarse":[159],"fine-grained).":[161],"Further,":[162],"dataset":[166,278],"train":[168],"pipeline":[170],"four":[172],"neural":[173],"models":[174],"predict":[176,221],"explanations,":[180],"given":[181],"(claim,":[183],"sentence":[185],"pair.":[186],"Explanations":[187],"include":[188],"inconsistent":[189,193,196,202,210,225],"claim":[190,197,213],"fact":[191],"triple,":[192],"context":[194],"span,":[195],"component,":[198],"coarse":[199],"fine-grained":[201],"types.":[204],"The":[205],"proposed":[206,255],"system":[207],"first":[208],"predicts":[209],"spans":[211],"from":[212],"context;":[215],"then":[217],"uses":[218],"them":[219],"(when":[228],"due":[231],"entities).":[233],"We":[234,273],"experiment":[235],"multiple":[237],"Transformer-based":[238],"classification":[241,268],"generative":[245],"models,":[246],"find":[248],"that":[249],"DeBERTa":[250],"performs":[251],"best.":[253],"Our":[254],"methods":[256],"provide":[257],"weighted":[259],"F1":[260],"87%":[264],"across":[269],"classes.":[272],"make":[274],"code":[276],"publicly":[279],"available":[280],"(":[281],"https://github.com/blitzprecision/FICLE":[282],").":[283]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}