{"id":"https://openalex.org/W3111969164","doi":"https://doi.org/10.1109/access.2020.3045166","title":"Collaborative Training of Gans in Continuous and Discrete Spaces for Text Generation","display_name":"Collaborative Training of Gans in Continuous and Discrete Spaces for Text Generation","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3111969164","doi":"https://doi.org/10.1109/access.2020.3045166","mag":"3111969164"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3045166","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3045166","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09296209.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09296209.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085991640","display_name":"Yanghoon Kim","orcid":"https://orcid.org/0000-0002-9236-0702"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Yanghoon Kim","raw_affiliation_strings":["Automation and Systems Research Institute, Seoul National University, Seoul, South Korea","Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Automation and Systems Research Institute, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016545538","display_name":"Seungpil Won","orcid":"https://orcid.org/0000-0002-3557-4157"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seungpil Won","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101424021","display_name":"Seunghyun Yoon","orcid":"https://orcid.org/0000-0002-7262-3579"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Seunghyun Yoon","raw_affiliation_strings":["Adobe Research, San Jose, CA, USA"],"affiliations":[{"raw_affiliation_string":"Adobe Research, San Jose, CA, USA","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077832834","display_name":"Kyomin Jung","orcid":"https://orcid.org/0000-0003-2547-7051"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kyomin Jung","raw_affiliation_strings":["Automation and Systems Research Institute, Seoul National University, Seoul, South Korea","Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Automation and Systems Research Institute, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5085991640"],"corresponding_institution_ids":["https://openalex.org/I139264467"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.5438,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.74829193,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"8","issue":null,"first_page":"226515","last_page":"226523"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9937999844551086,"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"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9909999966621399,"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":0.7770889401435852},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5667104125022888},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5441819429397583},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5046228170394897},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.46250149607658386},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.45692065358161926},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.45612043142318726},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4463005065917969},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4254341125488281},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.41630828380584717},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3629290759563446},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.32202816009521484}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7770889401435852},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5667104125022888},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5441819429397583},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5046228170394897},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.46250149607658386},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.45692065358161926},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.45612043142318726},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4463005065917969},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4254341125488281},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.41630828380584717},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3629290759563446},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.32202816009521484},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3045166","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3045166","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09296209.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d82f081423c34e1c918dfdddafac96dc","is_oa":true,"landing_page_url":"https://doaj.org/article/d82f081423c34e1c918dfdddafac96dc","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 226515-226523 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3045166","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3045166","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09296209.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6600000262260437}],"awards":[{"id":"https://openalex.org/G1103364132","display_name":null,"funder_award_id":"10073144","funder_id":"https://openalex.org/F4320321681","funder_display_name":"Ministry of Trade, Industry and Energy"},{"id":"https://openalex.org/G342704958","display_name":null,"funder_award_id":"funded","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G626505518","display_name":null,"funder_award_id":"No. 201","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G8265331568","display_name":null,"funder_award_id":"2016M3C4A7952632","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G834017027","display_name":null,"funder_award_id":"ACCESS","funder_id":"https://openalex.org/F4320320671","funder_display_name":"National Research Foundation"},{"id":"https://openalex.org/G8582691448","display_name":null,"funder_award_id":"MOTIE, Korea","funder_id":"https://openalex.org/F4320321681","funder_display_name":"Ministry of Trade, Industry and Energy"},{"id":"https://openalex.org/G992484961","display_name":null,"funder_award_id":"Korea","funder_id":"https://openalex.org/F4320321681","funder_display_name":"Ministry of Trade, Industry and Energy"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320321681","display_name":"Ministry of Trade, Industry and Energy","ror":"https://ror.org/008nkqk13"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3111969164.pdf","grobid_xml":"https://content.openalex.org/works/W3111969164.grobid-xml"},"referenced_works_count":56,"referenced_works":["https://openalex.org/W648786980","https://openalex.org/W1522301498","https://openalex.org/W1840435438","https://openalex.org/W1889081078","https://openalex.org/W1895577753","https://openalex.org/W2099471712","https://openalex.org/W2101105183","https://openalex.org/W2119717200","https://openalex.org/W2187089797","https://openalex.org/W2525778437","https://openalex.org/W2565378226","https://openalex.org/W2593383075","https://openalex.org/W2616969219","https://openalex.org/W2622385665","https://openalex.org/W2625357353","https://openalex.org/W2807747378","https://openalex.org/W2888506554","https://openalex.org/W2891177506","https://openalex.org/W2891521313","https://openalex.org/W2908747729","https://openalex.org/W2933374552","https://openalex.org/W2951824008","https://openalex.org/W2962770929","https://openalex.org/W2962793481","https://openalex.org/W2962935506","https://openalex.org/W2963167310","https://openalex.org/W2963216928","https://openalex.org/W2963248348","https://openalex.org/W2963456134","https://openalex.org/W2963684088","https://openalex.org/W2963730239","https://openalex.org/W2964017345","https://openalex.org/W2964061924","https://openalex.org/W2964121744","https://openalex.org/W2964268978","https://openalex.org/W2970454257","https://openalex.org/W4288348623","https://openalex.org/W4294294142","https://openalex.org/W4320013936","https://openalex.org/W6621543089","https://openalex.org/W6631190155","https://openalex.org/W6639432524","https://openalex.org/W6685352114","https://openalex.org/W6727862155","https://openalex.org/W6731128057","https://openalex.org/W6734351891","https://openalex.org/W6738090124","https://openalex.org/W6738966219","https://openalex.org/W6739349799","https://openalex.org/W6741042381","https://openalex.org/W6744415713","https://openalex.org/W6747262243","https://openalex.org/W6752378359","https://openalex.org/W6753811152","https://openalex.org/W6754386131","https://openalex.org/W6757992745"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W2159052453","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W2502115930","https://openalex.org/W2803255133","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W4386815338"],"abstract_inverted_index":{"Applying":[0],"generative":[1],"adversarial":[2,127,155],"networks":[3],"(GANs)":[4],"to":[5,11,54,66,71,116,184],"text-related":[6],"tasks":[7],"is":[8,138],"challenging":[9],"due":[10,53],"the":[12,31,44,64,73,102,106,134,153,159],"discrete":[13,38,75,88,147],"nature":[14],"of":[15,19,105],"language.":[16],"One":[17],"line":[18],"research":[20],"resolves":[21],"this":[22,91],"issue":[23],"by":[24],"employing":[25],"reinforcement":[26],"learning":[27,124],"(RL)":[28],"and":[29,49,108,141,187],"optimizing":[30],"next-word":[32],"sampling":[33],"policy":[34],"directly":[35,139],"in":[36,69,129,145,162],"a":[37,95,123,130,146],"action":[39],"space.":[40,132,148],"Such":[41],"methods":[42,79],"compute":[43],"rewards":[45],"from":[46],"complete":[47,135],"sentences":[48],"avoid":[50],"error":[51],"accumulation":[52],"exposure":[55],"bias.":[56],"Other":[57],"approaches":[58],"employ":[59],"approximation":[60],"techniques":[61],"that":[62,84,100,174],"map":[63],"text":[65,97,160,180],"continuous":[67,131],"representation":[68],"order":[70],"circumvent":[72],"non-differentiable":[74],"process.":[76],"Particularly,":[77],"autoencoder-based":[78],"effectively":[80,157],"produce":[81],"robust":[82],"representations":[83,161],"can":[85],"model":[86,176],"complex":[87],"structures.":[89],"In":[90],"article,":[92],"we":[93],"propose":[94],"novel":[96],"GAN":[98],"architecture":[99],"promotes":[101],"collaborative":[103,150],"training":[104,128],"continuous-space":[107],"discrete-space":[109],"methods.":[110],"Our":[111],"method":[112],"employs":[113],"an":[114,118],"autoencoder":[115],"learn":[117],"implicit":[119],"data":[120],"manifold,":[121],"providing":[122],"objective":[125],"for":[126],"Furthermore,":[133],"textual":[136],"output":[137],"evaluated":[140],"updated":[142],"via":[143],"RL":[144],"The":[149,165],"interplay":[151],"between":[152],"two":[154],"trainings":[156],"regularize":[158],"different":[163],"spaces.":[164],"experimental":[166],"results":[167],"on":[168],"three":[169],"standard":[170],"benchmark":[171],"datasets":[172],"show":[173],"our":[175],"substantially":[177],"outperforms":[178],"state-of-the-art":[179],"GANs":[181],"with":[182],"respect":[183],"quality,":[185],"diversity,":[186],"global":[188],"consistency.":[189]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}