{"id":"https://openalex.org/W4388951022","doi":"https://doi.org/10.1109/icccnt56998.2023.10307714","title":"Detecting Contradiction and Entailment in Multilingual Text","display_name":"Detecting Contradiction and Entailment in Multilingual Text","publication_year":2023,"publication_date":"2023-07-06","ids":{"openalex":"https://openalex.org/W4388951022","doi":"https://doi.org/10.1109/icccnt56998.2023.10307714"},"language":"en","primary_location":{"id":"doi:10.1109/icccnt56998.2023.10307714","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icccnt56998.2023.10307714","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045352546","display_name":"Abhigya Verma","orcid":"https://orcid.org/0000-0001-5928-8481"},"institutions":[{"id":"https://openalex.org/I4210143260","display_name":"Indira Gandhi Delhi Technical University for Women","ror":"https://ror.org/057c5p638","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210143260"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Abhigya Verma","raw_affiliation_strings":["Indira Gandhi Delhi Technical University for Women,Delhi,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indira Gandhi Delhi Technical University for Women,Delhi,India","institution_ids":["https://openalex.org/I4210143260"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093327552","display_name":"Jahnvi Srivastav","orcid":null},"institutions":[{"id":"https://openalex.org/I4210143260","display_name":"Indira Gandhi Delhi Technical University for Women","ror":"https://ror.org/057c5p638","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210143260"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Jahnvi Srivastav","raw_affiliation_strings":["Indira Gandhi Delhi Technical University for Women,Delhi,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indira Gandhi Delhi Technical University for Women,Delhi,India","institution_ids":["https://openalex.org/I4210143260"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113105259","display_name":"Pooja Gera","orcid":null},"institutions":[{"id":"https://openalex.org/I4210143260","display_name":"Indira Gandhi Delhi Technical University for Women","ror":"https://ror.org/057c5p638","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210143260"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Pooja Gera","raw_affiliation_strings":["Indira Gandhi Delhi Technical University for Women,Delhi,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indira Gandhi Delhi Technical University for Women,Delhi,India","institution_ids":["https://openalex.org/I4210143260"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021107821","display_name":"Amar Kumar Mohapatra","orcid":"https://orcid.org/0000-0002-8025-6879"},"institutions":[{"id":"https://openalex.org/I4210143260","display_name":"Indira Gandhi Delhi Technical University for Women","ror":"https://ror.org/057c5p638","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210143260"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"A. K. Mohapatra","raw_affiliation_strings":["Indira Gandhi Delhi Technical University for Women,Delhi,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indira Gandhi Delhi Technical University for Women,Delhi,India","institution_ids":["https://openalex.org/I4210143260"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210143260"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1747157,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"32","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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":0.9998000264167786,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9986000061035156,"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":0.9932000041007996,"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/contradiction","display_name":"Contradiction","score":0.8563857078552246},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8139193654060364},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.7253363728523254},{"id":"https://openalex.org/keywords/textual-entailment","display_name":"Textual entailment","score":0.708594560623169},{"id":"https://openalex.org/keywords/logical-consequence","display_name":"Logical consequence","score":0.6636927723884583},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.6407304406166077},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5544176697731018},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5161789059638977},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.47755083441734314},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.2072851061820984}],"concepts":[{"id":"https://openalex.org/C2776728590","wikidata":"https://www.wikidata.org/wiki/Q363948","display_name":"Contradiction","level":2,"score":0.8563857078552246},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8139193654060364},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7253363728523254},{"id":"https://openalex.org/C95318506","wikidata":"https://www.wikidata.org/wiki/Q6588467","display_name":"Textual entailment","level":3,"score":0.708594560623169},{"id":"https://openalex.org/C134752490","wikidata":"https://www.wikidata.org/wiki/Q374182","display_name":"Logical consequence","level":2,"score":0.6636927723884583},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.6407304406166077},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5544176697731018},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5161789059638977},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.47755083441734314},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.2072851061820984},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icccnt56998.2023.10307714","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icccnt56998.2023.10307714","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8700000047683716,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2798665661","https://openalex.org/W2896457183","https://openalex.org/W2945325682","https://openalex.org/W2962692632","https://openalex.org/W2965373594","https://openalex.org/W2970597249","https://openalex.org/W2988030942","https://openalex.org/W3008866797","https://openalex.org/W3035390927","https://openalex.org/W3037891159","https://openalex.org/W3110324508","https://openalex.org/W3128185314","https://openalex.org/W3138407803","https://openalex.org/W3157712880","https://openalex.org/W3163181833","https://openalex.org/W4221152720","https://openalex.org/W4323825842","https://openalex.org/W6755207826","https://openalex.org/W6763131180","https://openalex.org/W6763701032","https://openalex.org/W6766673545","https://openalex.org/W6769263558","https://openalex.org/W6810517592","https://openalex.org/W6844013476"],"related_works":["https://openalex.org/W2169644218","https://openalex.org/W12963412","https://openalex.org/W2250460949","https://openalex.org/W3158371345","https://openalex.org/W3141423438","https://openalex.org/W2071098659","https://openalex.org/W2627035043","https://openalex.org/W2250688396","https://openalex.org/W4200417912","https://openalex.org/W1893429831"],"abstract_inverted_index":{"With":[0],"many":[1],"applications,":[2],"including":[3,132],"text":[4,116],"categorization,":[5],"question-and-answer":[6],"systems,":[7],"and":[8,12,43,51,67,72,99,112,149],"sentiment":[9],"mapping,":[10],"entailment":[11,50,113],"contradiction":[13,52,111],"detection":[14],"in":[15,22,48,53,114,146],"multilingual":[16,40,55,115,136],"content":[17],"is":[18,107],"a":[19,54],"crucial":[20],"task":[21],"the":[23,32,38,44,62,79,101,133,141,152],"discipline":[24],"of":[25,34,65,128,135,154],"natural":[26,129],"language":[27,130,147],"processing.":[28],"This":[29],"study":[30],"examines":[31],"capabilities":[33],"two":[35],"advanced":[36],"models,":[37],"BERT-based":[39],"case":[41],"model":[42],"XLM-RoBERTa":[45,68,80],"large":[46],"model,":[47],"detecting":[49],"dataset":[56],"containing":[57],"15":[58],"diverse":[59],"languages.":[60],"While":[61],"initial":[63],"performance":[64],"BERT":[66],"models":[69,98],"was":[70],"30%":[71],"40%":[73],"respectively,":[74],"we":[75],"have":[76],"successfully":[77],"enhanced":[78],"model\u2019s":[81],"accuracy":[82],"to":[83,109,125],"an":[84],"impressive":[85],"70%":[86],"using":[87],"data":[88,103],"processing":[89,104,148],"techniques.":[90],"These":[91,138],"results":[92,139],"imply":[93],"that,":[94],"by":[95],"carefully":[96],"selecting":[97],"employing":[100],"relevant":[102,124],"techniques,":[105],"it":[106],"possible":[108],"detect":[110],"with":[117],"high":[118],"accuracy.":[119],"The":[120],"study\u2019s":[121],"outcomes":[122],"are":[123],"various":[126],"areas":[127],"processing,":[131],"analysis":[134],"text.":[137],"lay":[140],"groundwork":[142],"for":[143],"future":[144],"studies":[145],"can":[150],"guide":[151],"development":[153],"more":[155],"sophisticated":[156],"models.":[157]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
