{"id":"https://openalex.org/W3199345866","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534027","title":"Question Generation via Multi-stage Answers Editing Network","display_name":"Question Generation via Multi-stage Answers Editing Network","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3199345866","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534027","mag":"3199345866"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9534027","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534027","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","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/A5050223298","display_name":"Liuyin Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Liuyin Wang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000541408","display_name":"Dongming Sheng","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongming Sheng","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022672030","display_name":"Hai-Tao Zheng","orcid":"https://orcid.org/0000-0001-5128-5649"},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hai-Tao Zheng","raw_affiliation_strings":["Tsinghua ShenZhen International Graduate School, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua ShenZhen International Graduate School, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5050223298"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.136,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.55011802,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"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":1.0,"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":1.0,"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":0.9980999827384949,"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":0.9923999905586243,"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/computer-science","display_name":"Computer science","score":0.8623747229576111},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6873066425323486},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6371972560882568},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5944976806640625},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5406602621078491},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5299999117851257},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5275763273239136},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5131731629371643},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5066736340522766},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.454733669757843},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.4515605568885803},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.1516733467578888}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8623747229576111},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6873066425323486},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6371972560882568},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5944976806640625},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5406602621078491},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5299999117851257},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5275763273239136},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5131731629371643},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5066736340522766},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.454733669757843},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.4515605568885803},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.1516733467578888},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9534027","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534027","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.4099999964237213,"display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G176748560","display_name":null,"funder_award_id":"HW2018002","funder_id":"https://openalex.org/F4320322392","funder_display_name":"Tsinghua University"},{"id":"https://openalex.org/G2754657687","display_name":null,"funder_award_id":"2021A1515012640","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G8195756990","display_name":null,"funder_award_id":"61773229,6201101015","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320322392","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W803028973","https://openalex.org/W1522301498","https://openalex.org/W1531374185","https://openalex.org/W1902237438","https://openalex.org/W2064675550","https://openalex.org/W2101105183","https://openalex.org/W2119717200","https://openalex.org/W2130942839","https://openalex.org/W2133564696","https://openalex.org/W2151466713","https://openalex.org/W2154652894","https://openalex.org/W2168430651","https://openalex.org/W2176263492","https://openalex.org/W2606333299","https://openalex.org/W2606974598","https://openalex.org/W2740747242","https://openalex.org/W2741176794","https://openalex.org/W2757978590","https://openalex.org/W2886505372","https://openalex.org/W2889670144","https://openalex.org/W2890166583","https://openalex.org/W2891946694","https://openalex.org/W2951785908","https://openalex.org/W2952939310","https://openalex.org/W2962717047","https://openalex.org/W2963084599","https://openalex.org/W2963248296","https://openalex.org/W2963748441","https://openalex.org/W2964121744","https://openalex.org/W2964165364","https://openalex.org/W2964308564","https://openalex.org/W2970489252","https://openalex.org/W2970647290","https://openalex.org/W2970796366","https://openalex.org/W3032689177","https://openalex.org/W6622762108","https://openalex.org/W6631190155","https://openalex.org/W6631875545","https://openalex.org/W6679434410","https://openalex.org/W6679436768","https://openalex.org/W6682631176","https://openalex.org/W6685322675","https://openalex.org/W6753189187","https://openalex.org/W6898505805"],"related_works":["https://openalex.org/W2384605597","https://openalex.org/W2387743295","https://openalex.org/W2115758952","https://openalex.org/W3082787378","https://openalex.org/W2136007095","https://openalex.org/W2366230879","https://openalex.org/W3208425359","https://openalex.org/W2349927912","https://openalex.org/W3159777597","https://openalex.org/W4212839359"],"abstract_inverted_index":{"Automatic":[0],"question":[1,43,65],"generation":[2],"from":[3,36],"a":[4,9],"sentence":[5,89],"or":[6],"paragraph":[7],"is":[8],"challenging":[10],"task.":[11],"Recently,":[12],"impressive":[13],"progress":[14],"has":[15],"been":[16],"made,":[17],"mainly":[18],"owing":[19],"to":[20,32,62,91,137],"the":[21,37,41,64,67,71,76,85,93,102,106,111,116,120,124,128,133,139,160],"advance":[22],"of":[23,141,165],"deep":[24],"neural":[25,29],"networks.":[26],"However,":[27],"existing":[28],"approaches":[30],"tend":[31],"simply":[33],"copy":[34],"words":[35],"given":[38],"answer,":[39],"making":[40],"generated":[42,142],"equivocal":[44],"and":[45,82,88,123,144,152,168],"informatively":[46],"redundant.":[47],"In":[48,70,105,127],"this":[49],"work,":[50],"we":[51,74,109,131],"propose":[52],"an":[53,79,98],"edit-based":[54],"network,":[55],"named":[56],"Multi-stage":[57],"Answers":[58],"Editing":[59],"Network":[60],"(MultiEdit),":[61],"generate":[63],"in":[66,163],"three-stage":[68],"operations.":[69],"initial":[72],"stage,":[73,108,130],"convert":[75],"answer":[77,103],"into":[78],"edit":[80,86,110,125],"vector":[81,87],"then":[83],"combine":[84],"representation":[90,113,122],"initialize":[92],"decoder,":[94],"which":[95],"helps":[96],"choose":[97],"interrogative":[99],"word":[100],"matching":[101],"type.":[104],"second":[107],"contextual":[112],"by":[114],"computing":[115],"weighted":[117],"average":[118],"between":[119],"context":[121],"vector.":[126],"final":[129],"adopt":[132],"additional":[134],"reinforcement":[135],"learning":[136],"improve":[138],"effectiveness":[140],"semantics":[143],"evaluation":[145],"indicators.":[146],"Experimental":[147],"results":[148],"on":[149],"both":[150,166],"Chinese":[151],"English":[153],"datasets":[154],"show":[155],"that":[156],"our":[157],"approach":[158],"outperforms":[159],"state-of-the-art":[161],"methods":[162],"terms":[164],"automatic":[167],"human":[169],"evaluation.":[170]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
