{"id":"https://openalex.org/W4402352271","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651121","title":"Learning Choice Nuance for Multiple-Choice Commonsense Question Answering","display_name":"Learning Choice Nuance for Multiple-Choice Commonsense Question Answering","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402352271","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651121"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10651121","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10651121","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","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/A5103268737","display_name":"Dongyu Yang","orcid":"https://orcid.org/0000-0001-8194-9012"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongyu Yang","raw_affiliation_strings":["Tianjin University,Tianjin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University,Tianjin,China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014571716","display_name":"Wenqing Deng","orcid":"https://orcid.org/0009-0008-7004-1242"},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Wenqing Deng","raw_affiliation_strings":["Griffith University,Brisbane,Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Griffith University,Brisbane,Australia","institution_ids":["https://openalex.org/I11701301"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100621319","display_name":"Zhe Wang","orcid":"https://orcid.org/0000-0002-3759-2041"},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Zhe Wang","raw_affiliation_strings":["Griffith University,Brisbane,Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Griffith University,Brisbane,Australia","institution_ids":["https://openalex.org/I11701301"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031190010","display_name":"Kewen Wang","orcid":"https://orcid.org/0000-0002-0542-3761"},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Kewen Wang","raw_affiliation_strings":["Griffith University,Brisbane,Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Griffith University,Brisbane,Australia","institution_ids":["https://openalex.org/I11701301"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100301805","display_name":"Zhiqiang Zhuang","orcid":"https://orcid.org/0009-0007-7136-7722"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqiang Zhuang","raw_affiliation_strings":["Tianjin University,Tianjin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University,Tianjin,China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100348486","display_name":"Hao Li","orcid":"https://orcid.org/0000-0003-4468-5972"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Li","raw_affiliation_strings":["Tianjin University,Tianjin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University,Tianjin,China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14705422,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9976999759674072,"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"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9959999918937683,"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/commonsense-knowledge","display_name":"Commonsense knowledge","score":0.8372065424919128},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.7944930791854858},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.652922511100769},{"id":"https://openalex.org/keywords/commonsense-reasoning","display_name":"Commonsense reasoning","score":0.6352927088737488},{"id":"https://openalex.org/keywords/multiple-choice","display_name":"Multiple choice","score":0.6191619038581848},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.509800374507904},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4372590482234955},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.10635524988174438},{"id":"https://openalex.org/keywords/philosophy","display_name":"Philosophy","score":0.10255762934684753},{"id":"https://openalex.org/keywords/knowledge-extraction","display_name":"Knowledge extraction","score":0.08719635009765625}],"concepts":[{"id":"https://openalex.org/C30542707","wikidata":"https://www.wikidata.org/wiki/Q1603203","display_name":"Commonsense knowledge","level":3,"score":0.8372065424919128},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.7944930791854858},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.652922511100769},{"id":"https://openalex.org/C193221554","wikidata":"https://www.wikidata.org/wiki/Q5153664","display_name":"Commonsense reasoning","level":2,"score":0.6352927088737488},{"id":"https://openalex.org/C176730311","wikidata":"https://www.wikidata.org/wiki/Q867668","display_name":"Multiple choice","level":3,"score":0.6191619038581848},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.509800374507904},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4372590482234955},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.10635524988174438},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.10255762934684753},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.08719635009765625},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10651121","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10651121","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W2080133951","https://openalex.org/W2561529111","https://openalex.org/W2604314403","https://openalex.org/W2890894339","https://openalex.org/W2896457183","https://openalex.org/W2899663614","https://openalex.org/W2963748441","https://openalex.org/W2963895422","https://openalex.org/W2963907629","https://openalex.org/W2964120615","https://openalex.org/W2968917279","https://openalex.org/W2983995706","https://openalex.org/W3034987253","https://openalex.org/W3097986428","https://openalex.org/W3162922479","https://openalex.org/W3172335055","https://openalex.org/W3192478068","https://openalex.org/W4200629408","https://openalex.org/W4205509257","https://openalex.org/W4221143046","https://openalex.org/W4231449374","https://openalex.org/W4313191056","https://openalex.org/W4385573630","https://openalex.org/W6738893770","https://openalex.org/W6755829550","https://openalex.org/W6809646742","https://openalex.org/W6810671341"],"related_works":["https://openalex.org/W3035583586","https://openalex.org/W4320165839","https://openalex.org/W2151799802","https://openalex.org/W4385488510","https://openalex.org/W2196562041","https://openalex.org/W2073302931","https://openalex.org/W3206107299","https://openalex.org/W3082691151","https://openalex.org/W4287633646","https://openalex.org/W4313191056"],"abstract_inverted_index":{"Existing":[0],"models":[1,13],"for":[2,20,44,72],"commonsense":[3],"question":[4,35,84],"answering":[5],"(CQA)":[6],"usually":[7],"focus":[8,118],"on":[9,119,124,134],"combining":[10],"pre-trained":[11],"language":[12],"(PLMs)":[14],"and":[15,36,76,98,107],"structured":[16],"knowledge":[17,93,102,122],"graphs":[18],"(KGs)":[19],"joint":[21],"reasoning.":[22],"However,":[23],"such":[24],"approaches":[25],"encode":[26],"a":[27,31,37,64],"QA":[28],"context":[29],"(i.e.,":[30],"pair":[32],"of":[33],"the":[34,51,91,99,109,115,125,145],"choice)":[38],"separately":[39],"from":[40],"other":[41],"choices,":[42,52,113,126],"ineffective":[43],"explicitly":[45,88],"capturing":[46],"useful":[47],"subtle":[48],"differences":[49],"among":[50,70,111],"which":[53],"results":[54,133],"in":[55,58],"incorrect":[56],"answers":[57],"some":[59],"cases.":[60],"This":[61],"paper":[62],"proposes":[63],"novel":[65],"model":[66,116],"LNC":[67,87,140],"(Learning":[68],"Nuance":[69],"Choices)":[71],"addressing":[73],"this":[74],"problem":[75],"thus":[77],"provides":[78],"an":[79],"improved":[80],"approach":[81],"to":[82,95,104,117,144],"multiple-choice":[83],"answering.":[85],"Specifically,":[86],"interacts":[89],"between":[90],"text":[92],"corresponding":[94,103],"each":[96,105],"choice":[97],"external":[100],"KG":[101],"choice,":[106],"removes":[108],"commonalities":[110],"similar":[112,130],"allowing":[114],"different":[120],"relevant":[121],"based":[123],"thereby":[127],"distinguishing":[128],"semantically":[129],"choices.":[131],"Experimental":[132],"major":[135],"benchmark":[136],"datasets":[137],"show":[138],"that":[139],"is":[141],"competitive":[142],"comparing":[143],"baseline":[146],"models.":[147]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
