{"id":"https://openalex.org/W3100836396","doi":"https://doi.org/10.18653/v1/2020.coling-main.467","title":"CosMo: Conditional Seq2Seq-based Mixture Model for Zero-Shot Commonsense Question Answering","display_name":"CosMo: Conditional Seq2Seq-based Mixture Model for Zero-Shot Commonsense Question Answering","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3100836396","doi":"https://doi.org/10.18653/v1/2020.coling-main.467","mag":"3100836396"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2020.coling-main.467","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2020.coling-main.467","pdf_url":"https://www.aclweb.org/anthology/2020.coling-main.467.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":"Proceedings of the 28th International Conference on Computational Linguistics","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/2020.coling-main.467.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034364701","display_name":"Farhad Moghimifar","orcid":null},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Farhad Moghimifar","raw_affiliation_strings":["The School of ITEE, The University of Queensland, Australia","University of Queensland, Brisbane, Australia"],"affiliations":[{"raw_affiliation_string":"The School of ITEE, The University of Queensland, Australia","institution_ids":["https://openalex.org/I165143802"]},{"raw_affiliation_string":"University of Queensland, Brisbane, Australia","institution_ids":["https://openalex.org/I165143802"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008486397","display_name":"Lizhen Qu","orcid":"https://orcid.org/0000-0002-7764-431X"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Lizhen Qu","raw_affiliation_strings":["Faculty of Information Technology, Monash University, Australia","Monash University, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Technology, Monash University, Australia","institution_ids":["https://openalex.org/I56590836"]},{"raw_affiliation_string":"Monash University, Melbourne, Australia","institution_ids":["https://openalex.org/I56590836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100690532","display_name":"Yue Zhuo","orcid":"https://orcid.org/0000-0002-5739-1896"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yue Zhuo","raw_affiliation_strings":["School of CSE, The University of New South Wales, Australia"],"affiliations":[{"raw_affiliation_string":"School of CSE, The University of New South Wales, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014648528","display_name":"Mahsa Baktashmotlagh","orcid":"https://orcid.org/0000-0001-5255-8194"},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]},{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Mahsa Baktashmotlagh","raw_affiliation_strings":["The School of ITEE, The University of Queensland, Australia","Monash University, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"The School of ITEE, The University of Queensland, Australia","institution_ids":["https://openalex.org/I165143802"]},{"raw_affiliation_string":"Monash University, Melbourne, Australia","institution_ids":["https://openalex.org/I56590836"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081525024","display_name":"Gholamreza Haffari","orcid":"https://orcid.org/0000-0001-7326-8380"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]},{"id":"https://openalex.org/I165143802","display_name":"University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Gholamreza Haffari","raw_affiliation_strings":["Faculty of Information Technology, Monash University, Australia","University of Queensland, Brisbane, Australia"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Technology, Monash University, Australia","institution_ids":["https://openalex.org/I56590836"]},{"raw_affiliation_string":"University of Queensland, Brisbane, Australia","institution_ids":["https://openalex.org/I165143802"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5034364701"],"corresponding_institution_ids":["https://openalex.org/I165143802"],"apc_list":null,"apc_paid":null,"fwci":0.2743,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.65464797,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"5347","last_page":"5359"},"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":0.9951000213623047,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9914000034332275,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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-reasoning","display_name":"Commonsense reasoning","score":0.8194127082824707},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7213956117630005},{"id":"https://openalex.org/keywords/commonsense-knowledge","display_name":"Commonsense knowledge","score":0.6537238359451294},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5400979518890381},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5226571559906006},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.44149428606033325},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.42876309156417847},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4201924800872803},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.20937922596931458},{"id":"https://openalex.org/keywords/knowledge-based-systems","display_name":"Knowledge-based systems","score":0.14466872811317444}],"concepts":[{"id":"https://openalex.org/C193221554","wikidata":"https://www.wikidata.org/wiki/Q5153664","display_name":"Commonsense reasoning","level":2,"score":0.8194127082824707},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7213956117630005},{"id":"https://openalex.org/C30542707","wikidata":"https://www.wikidata.org/wiki/Q1603203","display_name":"Commonsense knowledge","level":3,"score":0.6537238359451294},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5400979518890381},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5226571559906006},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.44149428606033325},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.42876309156417847},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4201924800872803},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.20937922596931458},{"id":"https://openalex.org/C115925183","wikidata":"https://www.wikidata.org/wiki/Q1412694","display_name":"Knowledge-based systems","level":2,"score":0.14466872811317444},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.18653/v1/2020.coling-main.467","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2020.coling-main.467","pdf_url":"https://www.aclweb.org/anthology/2020.coling-main.467.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":"Proceedings of the 28th International Conference on Computational Linguistics","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2011.00777","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2011.00777","pdf_url":"https://arxiv.org/pdf/2011.00777","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3100836396","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2011.00777","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:monash.edu:openaire/e07adcc8-9c45-4356-bc22-8e9869981dde","is_oa":true,"landing_page_url":"https://research.monash.edu/en/publications/e07adcc8-9c45-4356-bc22-8e9869981dde","pdf_url":null,"source":{"id":"https://openalex.org/S4306402625","display_name":"Monash University Research Portal (Monash University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I56590836","host_organization_name":"Monash University","host_organization_lineage":["https://openalex.org/I56590836"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Moghimifar, F, Qu, L, Zhuo, Y, Baktashmotlagh, M & Haffari, R 2020, CosMo : Conditional SEQ2SEQ-based Mixture model for zero-shot commonsense question answering. in N Bel & C Zong (eds), COLING 2020 : The 28th International Conference on Computational Linguistics, Proceedings of the Conference., 467, Association for Computational Linguistics (ACL), Stroudsburg PA USA, pp. 5347-5359, International Conference on Computational Linguistics 2020, Barcelona, Spain, 8/12/20. https://doi.org/10.18653/v1/2020.coling-main.467","raw_type":"contributionToPeriodical"},{"id":"pmh:oai:monash.edu:publications/e07adcc8-9c45-4356-bc22-8e9869981dde","is_oa":true,"landing_page_url":"http://www.scopus.com/inward/record.url?scp=85105304158&partnerID=8YFLogxK","pdf_url":null,"source":{"id":"https://openalex.org/S4306402625","display_name":"Monash University Research Portal (Monash University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I56590836","host_organization_name":"Monash University","host_organization_lineage":["https://openalex.org/I56590836"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Moghimifar , F , Qu , L , Zhuo , Y , Baktashmotlagh , M & Haffari , R 2020 , CosMo : Conditional SEQ2SEQ-based Mixture model for zero-shot commonsense question answering . in N Bel & C Zong (eds) , COLING 2020 : The 28th International Conference on Computational Linguistics, Proceedings of the Conference . , 467 , Association for Computational Linguistics (ACL) , Stroudsburg PA USA , pp. 5347-5359 , International Conference on Computational Linguistics 2020 , Barcelona , Spain , 8/12/20 . https://doi.org/10.18653/v1/2020.coling-main.467","raw_type":"contributionToPeriodical"},{"id":"doi:10.48550/arxiv.2011.00777","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2011.00777","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.18653/v1/2020.coling-main.467","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2020.coling-main.467","pdf_url":"https://www.aclweb.org/anthology/2020.coling-main.467.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":"Proceedings of the 28th International Conference on Computational Linguistics","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7099999785423279,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3100836396.pdf","grobid_xml":"https://content.openalex.org/works/W3100836396.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2143177362","https://openalex.org/W2555661914","https://openalex.org/W2766508367","https://openalex.org/W2886424491","https://openalex.org/W2910453440","https://openalex.org/W2936262349","https://openalex.org/W2948608684","https://openalex.org/W2950513705","https://openalex.org/W2952347738","https://openalex.org/W2963101081","https://openalex.org/W2963341956","https://openalex.org/W2963430447","https://openalex.org/W2963684875","https://openalex.org/W2964207259","https://openalex.org/W2965373594","https://openalex.org/W2971979242","https://openalex.org/W2983995706","https://openalex.org/W2985671014","https://openalex.org/W2990752173","https://openalex.org/W2996428491","https://openalex.org/W2997545008","https://openalex.org/W2998374885","https://openalex.org/W2999210089","https://openalex.org/W3007306981","https://openalex.org/W3012590175","https://openalex.org/W3015440086","https://openalex.org/W3015759694","https://openalex.org/W3015773279","https://openalex.org/W3023427030","https://openalex.org/W3094815596"],"related_works":["https://openalex.org/W3035583586","https://openalex.org/W2948036864","https://openalex.org/W2985671014","https://openalex.org/W3212208515","https://openalex.org/W3207553988","https://openalex.org/W2977745385","https://openalex.org/W3162291398","https://openalex.org/W2974040294","https://openalex.org/W3197499179","https://openalex.org/W3174464510","https://openalex.org/W3213785694","https://openalex.org/W2399458388","https://openalex.org/W3213148810","https://openalex.org/W2133422947","https://openalex.org/W1597904069","https://openalex.org/W3201027158","https://openalex.org/W3094101859","https://openalex.org/W2974810665","https://openalex.org/W82332555","https://openalex.org/W2079322253"],"abstract_inverted_index":{"Commonsense":[0],"reasoning":[1,64,90],"refers":[2],"to":[3,33,47,61,72,86,117,139,160],"the":[4,16,26,59,88,106,134,145,163],"ability":[5,60],"of":[6,15,21,40,74,79,108,136,147,158],"evaluating":[7],"a":[8,22,76,123],"social":[9,23,41,81],"situation":[10],"and":[11,19,110],"acting":[12],"accordingly.":[13],"Identification":[14],"implicit":[17,80],"causes":[18],"effects":[20],"context":[24],"is":[25],"driving":[27],"capability":[28],"which":[29,102,121],"can":[30],"enable":[31],"machines":[32],"perform":[34,62],"commonsense":[35,63,130,149],"reasoning.":[36,131],"The":[37,152],"dynamic":[38,109,124],"world":[39],"interactions":[42],"requires":[43],"context-dependent":[44,119],"on-demand":[45],"systems":[46],"infer":[48],"such":[49],"underlying":[50],"information.":[51],"However,":[52],"current":[53],"approaches":[54],"in":[55],"this":[56,93],"realm":[57],"lack":[58],"upon":[65],"facing":[66],"an":[67,156],"unseen":[68],"situation,":[69],"mostly":[70],"due":[71],"incapability":[73],"identifying":[75],"diverse":[77,111],"range":[78],"relations.":[82],"Hence":[83],"they":[84],"fail":[85],"estimate":[87],"correct":[89],"path.":[91],"In":[92],"paper,":[94],"we":[95,143],"present":[96],"Conditional":[97],"SEQ2SEQ-based":[98],"Mixture":[99],"model":[100,138],"(COSMO),":[101],"provides":[103],"us":[104],"with":[105],"capabilities":[107],"content":[112],"generation.":[113],"We":[114],"use":[115],"COSMO":[116],"generate":[118],"clauses,":[120],"form":[122],"Knowledge":[125],"Graph":[126],"(KG)":[127],"on-the-fly":[128],"for":[129],"To":[132],"show":[133],"adaptability":[135],"our":[137],"context-dependant":[140],"knowledge":[141],"generation,":[142],"address":[144],"task":[146],"zero-shot":[148],"question":[150],"answering.":[151],"empirical":[153],"results":[154],"indicate":[155],"improvement":[157],"up":[159],"+5.2%":[161],"over":[162],"state-of-the-art":[164],"models.":[165]},"counts_by_year":[{"year":2021,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}