{"id":"https://openalex.org/W2952939310","doi":"https://doi.org/10.18653/v1/p19-1203","title":"Reinforced Dynamic Reasoning for Conversational Question Generation","display_name":"Reinforced Dynamic Reasoning for Conversational Question Generation","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2952939310","doi":"https://doi.org/10.18653/v1/p19-1203","mag":"2952939310"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p19-1203","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1203","pdf_url":"https://www.aclweb.org/anthology/P19-1203.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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P19-1203.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079034292","display_name":"Boyuan Pan","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Boyuan Pan","raw_affiliation_strings":["State Key Lab of CAD&CG, Zhejiang University"],"affiliations":[{"raw_affiliation_string":"State Key Lab of CAD&CG, Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100348629","display_name":"Hao Li","orcid":"https://orcid.org/0000-0002-7434-3896"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Li","raw_affiliation_strings":["State Key Lab of CAD&CG, Zhejiang University"],"affiliations":[{"raw_affiliation_string":"State Key Lab of CAD&CG, Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101616607","display_name":"Ziyu Yao","orcid":"https://orcid.org/0009-0007-4571-3505"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ziyu Yao","raw_affiliation_strings":["The Ohio State University"],"affiliations":[{"raw_affiliation_string":"The Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061528283","display_name":"Deng Cai","orcid":"https://orcid.org/0000-0003-3444-8383"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Deng Cai","raw_affiliation_strings":["Alibaba-Zhejiang University Joint Institute of Frontier Technologies","State Key Lab of CAD&CG, Zhejiang University"],"affiliations":[{"raw_affiliation_string":"Alibaba-Zhejiang University Joint Institute of Frontier Technologies","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"State Key Lab of CAD&CG, Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101488340","display_name":"Huan Sun","orcid":"https://orcid.org/0000-0001-6436-4813"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huan Sun","raw_affiliation_strings":["The Ohio State University"],"affiliations":[{"raw_affiliation_string":"The Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5061528283"],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":4.45491462,"has_fulltext":true,"cited_by_count":41,"citation_normalized_percentile":{"value":0.9513748,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2114","last_page":"2124"},"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":0.9988999962806702,"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/T12031","display_name":"Speech and dialogue systems","score":0.9926999807357788,"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/computer-science","display_name":"Computer science","score":0.8494490385055542},{"id":"https://openalex.org/keywords/conversation","display_name":"Conversation","score":0.7771228551864624},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7022749185562134},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.6995912194252014},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6267086863517761},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5673142671585083},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5441107153892517},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5389896035194397},{"id":"https://openalex.org/keywords/ask-price","display_name":"Ask price","score":0.4823572039604187},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.45398300886154175},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3727709650993347},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3384573459625244},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.08467882871627808}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8494490385055542},{"id":"https://openalex.org/C2777200299","wikidata":"https://www.wikidata.org/wiki/Q52943","display_name":"Conversation","level":2,"score":0.7771228551864624},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7022749185562134},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.6995912194252014},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6267086863517761},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5673142671585083},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5441107153892517},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5389896035194397},{"id":"https://openalex.org/C90329073","wikidata":"https://www.wikidata.org/wiki/Q914232","display_name":"Ask price","level":2,"score":0.4823572039604187},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.45398300886154175},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3727709650993347},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3384573459625244},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.08467882871627808},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C136264566","wikidata":"https://www.wikidata.org/wiki/Q159810","display_name":"Economy","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p19-1203","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1203","pdf_url":"https://www.aclweb.org/anthology/P19-1203.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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p19-1203","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1203","pdf_url":"https://www.aclweb.org/anthology/P19-1203.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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2952939310.pdf","grobid_xml":"https://content.openalex.org/works/W2952939310.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W10957333","https://openalex.org/W1518951372","https://openalex.org/W1531374185","https://openalex.org/W1555380324","https://openalex.org/W1591706642","https://openalex.org/W1902237438","https://openalex.org/W2095705004","https://openalex.org/W2101105183","https://openalex.org/W2109609717","https://openalex.org/W2119717200","https://openalex.org/W2130942839","https://openalex.org/W2143177362","https://openalex.org/W2154652894","https://openalex.org/W2250539671","https://openalex.org/W2250794458","https://openalex.org/W2551396370","https://openalex.org/W2552027021","https://openalex.org/W2606333299","https://openalex.org/W2606974598","https://openalex.org/W2612228435","https://openalex.org/W2626182443","https://openalex.org/W2739749670","https://openalex.org/W2756487349","https://openalex.org/W2786472750","https://openalex.org/W2804292122","https://openalex.org/W2886983157","https://openalex.org/W2888302696","https://openalex.org/W2894293047","https://openalex.org/W2896342318","https://openalex.org/W2904631866","https://openalex.org/W2951831170","https://openalex.org/W2951883832","https://openalex.org/W2952230306","https://openalex.org/W2962717047","https://openalex.org/W2962883855","https://openalex.org/W2962970841","https://openalex.org/W2962977247","https://openalex.org/W2962985038","https://openalex.org/W2963167310","https://openalex.org/W2963206148","https://openalex.org/W2963351776","https://openalex.org/W2963748441","https://openalex.org/W2963797754","https://openalex.org/W2963871484","https://openalex.org/W2964165364","https://openalex.org/W2964223283","https://openalex.org/W2964236999","https://openalex.org/W4289489602"],"related_works":["https://openalex.org/W1968552888","https://openalex.org/W1527532029","https://openalex.org/W2374116601","https://openalex.org/W3093134843","https://openalex.org/W2378167147","https://openalex.org/W3210777354","https://openalex.org/W2772323916","https://openalex.org/W2281307425","https://openalex.org/W1511346092","https://openalex.org/W2464405057"],"abstract_inverted_index":{"This":[0],"paper":[1],"investigates":[2],"a":[3,15,19,22,33,51,59,77,81,111,126],"new":[4,60],"task":[5,35],"named":[6,62],"Conversational":[7],"Question":[8],"Generation":[9],"(CQG)":[10],"which":[11,67],"is":[12,32,68],"to":[13,84,93,117,153,164],"generate":[14],"question":[16,113,123],"based":[17,69],"on":[18,70,132],"passage":[20,98],"and":[21,91,120,149],"conversation":[23],"history":[24],"(i.e.,":[25],"previous":[26],"turns":[27],"of":[28,50,141,157],"question-answer":[29],"pairs).":[30],"CQG":[31],"crucial":[34],"for":[36,169],"developing":[37],"intelligent":[38],"agents":[39],"that":[40,55],"can":[41],"drive":[42],"question-answering":[43,167],"style":[44],"conversations":[45,168],"or":[46],"test":[47],"user":[48],"understanding":[49],"given":[52],"passage.":[53],"Towards":[54],"end,":[56],"we":[57,109,160],"propose":[58],"approach":[61],"Reinforced":[63],"Dynamic":[64],"Reasoning":[65],"network,":[66],"the":[71,97,100,122,133,139,155],"general":[72,101],"encoder-decoder":[73,102],"framework":[74],"but":[75],"incorporates":[76],"reasoning":[78],"procedure":[79],"in":[80,144,171],"dynamic":[82],"manner":[83],"better":[85],"understand":[86],"what":[87,92],"has":[88],"been":[89],"asked":[90],"ask":[94],"next":[95],"about":[96],"into":[99],"framework.":[103],"To":[104],"encourage":[105],"producing":[106],"meaningful":[107],"questions,":[108],"leverage":[110],"popular":[112],"answering":[114],"(QA)":[115],"model":[116,150],"provide":[118],"feedback":[119],"fine-tune":[121],"generator":[124],"using":[125],"reinforcement":[127],"learning":[128],"mechanism.":[129],"Empirical":[130],"results":[131],"recently":[134],"released":[135],"CoQA":[136],"dataset":[137],"demonstrate":[138],"effectiveness":[140],"our":[142,158],"method":[143],"comparison":[145],"with":[146],"various":[147],"baselines":[148],"variants.":[151],"Moreover,":[152],"show":[154],"applicability":[156],"method,":[159],"also":[161],"apply":[162],"it":[163],"create":[165],"multi-turn":[166],"passages":[170],"SQuAD.":[172]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":14},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}