{"id":"https://openalex.org/W2929742901","doi":"https://doi.org/10.18653/v1/w19-4303","title":"Generative Adversarial Networks for Text Using Word2vec Intermediaries","display_name":"Generative Adversarial Networks for Text Using Word2vec Intermediaries","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2929742901","doi":"https://doi.org/10.18653/v1/w19-4303","mag":"2929742901"},"language":"en","primary_location":{"id":"doi:10.18653/v1/w19-4303","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w19-4303","pdf_url":"https://www.aclweb.org/anthology/W19-4303.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 4th Workshop on Representation Learning for NLP (RepL4NLP-2019)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/W19-4303.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062563541","display_name":"Akshay Budhkar","orcid":null},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]},{"id":"https://openalex.org/I4210127509","display_name":"Vector Institute","ror":"https://ror.org/03kqdja62","country_code":"CA","type":"facility","lineage":["https://openalex.org/I4210127509"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Akshay Budhkar","raw_affiliation_strings":["Department of Computer Science, University of Toronto","Vector Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Toronto","institution_ids":["https://openalex.org/I185261750"]},{"raw_affiliation_string":"Vector Institute","institution_ids":["https://openalex.org/I4210127509"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043217036","display_name":"Krishnapriya Vishnubhotla","orcid":null},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Krishnapriya Vishnubhotla","raw_affiliation_strings":["Department of Computer Science, University of Toronto"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Toronto","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101918330","display_name":"Safwan Hossain","orcid":"https://orcid.org/0000-0002-4909-6651"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]},{"id":"https://openalex.org/I4210127509","display_name":"Vector Institute","ror":"https://ror.org/03kqdja62","country_code":"CA","type":"facility","lineage":["https://openalex.org/I4210127509"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Safwan Hossain","raw_affiliation_strings":["Department of Computer Science, University of Toronto","Vector Institute","University of Toronto, Toronto, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Toronto","institution_ids":["https://openalex.org/I185261750"]},{"raw_affiliation_string":"Vector Institute","institution_ids":["https://openalex.org/I4210127509"]},{"raw_affiliation_string":"University of Toronto, Toronto, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056256317","display_name":"Frank Rudzicz","orcid":"https://orcid.org/0000-0002-1139-3423"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Frank Rudzicz","raw_affiliation_strings":["University of Toronto, Toronto, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Toronto, Toronto, Canada","institution_ids":["https://openalex.org/I185261750"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0914,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.30179944,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"15","last_page":"26"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9993000030517578,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9887999892234802,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.970300018787384,"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/generative-grammar","display_name":"Generative grammar","score":0.8140236139297485},{"id":"https://openalex.org/keywords/word2vec","display_name":"Word2vec","score":0.7566535472869873},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7182066440582275},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6664683818817139},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.5282268524169922},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.521468997001648},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5037633776664734},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5010113716125488},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.4836631715297699},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.4523058235645294},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38971298933029175},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3852940499782562},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.36228305101394653},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.27695515751838684},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.2479250431060791},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13317301869392395},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.12960848212242126},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07941305637359619}],"concepts":[{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.8140236139297485},{"id":"https://openalex.org/C2776461190","wikidata":"https://www.wikidata.org/wiki/Q22673982","display_name":"Word2vec","level":3,"score":0.7566535472869873},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7182066440582275},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6664683818817139},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.5282268524169922},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.521468997001648},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5037633776664734},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5010113716125488},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.4836631715297699},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.4523058235645294},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38971298933029175},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3852940499782562},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.36228305101394653},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27695515751838684},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.2479250431060791},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13317301869392395},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.12960848212242126},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07941305637359619},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.18653/v1/w19-4303","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w19-4303","pdf_url":"https://www.aclweb.org/anthology/W19-4303.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 4th Workshop on Representation Learning for NLP (RepL4NLP-2019)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1904.02293","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1904.02293","pdf_url":"https://arxiv.org/pdf/1904.02293","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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:2929742901","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1904.02293.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"doi:10.48550/arxiv.1904.02293","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1904.02293","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"}],"best_oa_location":{"id":"doi:10.18653/v1/w19-4303","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w19-4303","pdf_url":"https://www.aclweb.org/anthology/W19-4303.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 4th Workshop on Representation Learning for NLP (RepL4NLP-2019)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7400000095367432,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309949","display_name":"Canadian Institute for Advanced Research","ror":"https://ror.org/01sdtdd95"},{"id":"https://openalex.org/F4320330223","display_name":"Vector Institute","ror":"https://ror.org/03kqdja62"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2929742901.pdf","grobid_xml":"https://content.openalex.org/works/W2929742901.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W168564468","https://openalex.org/W2086234878","https://openalex.org/W2099471712","https://openalex.org/W2101105183","https://openalex.org/W2115221470","https://openalex.org/W2125389028","https://openalex.org/W2153579005","https://openalex.org/W2173520492","https://openalex.org/W2547875792","https://openalex.org/W2565378226","https://openalex.org/W2577946330","https://openalex.org/W2593383075","https://openalex.org/W2616969219","https://openalex.org/W2620623908","https://openalex.org/W2784823820","https://openalex.org/W2792795990","https://openalex.org/W2893749619","https://openalex.org/W2904683980","https://openalex.org/W2962879692","https://openalex.org/W2963248348","https://openalex.org/W2963456134","https://openalex.org/W2963462013","https://openalex.org/W2964017345","https://openalex.org/W2964268978"],"related_works":["https://openalex.org/W3200548555","https://openalex.org/W3111969164","https://openalex.org/W3091334737","https://openalex.org/W3159174613","https://openalex.org/W2805750129","https://openalex.org/W3010866285","https://openalex.org/W2963110372","https://openalex.org/W2975288815","https://openalex.org/W3029462071","https://openalex.org/W2952456459","https://openalex.org/W2599026779","https://openalex.org/W2412320034","https://openalex.org/W2984602655","https://openalex.org/W3008589754","https://openalex.org/W2756413773","https://openalex.org/W3104038788","https://openalex.org/W2971894730","https://openalex.org/W2939496611","https://openalex.org/W3209492300","https://openalex.org/W2798273902"],"abstract_inverted_index":{"Generative":[0],"adversarial":[1],"networks":[2],"(GANs)":[3],"have":[4],"shown":[5],"considerable":[6],"success,":[7],"especially":[8],"in":[9],"the":[10,23,34],"realistic":[11],"generation":[12,24],"of":[13,25,37],"images.":[14],"In":[15],"this":[16],"work,":[17],"we":[18],"apply":[19],"similar":[20],"techniques":[21],"for":[22],"text.":[26],"We":[27],"propose":[28],"a":[29],"novel":[30],"approach":[31],"to":[32,48,56],"handle":[33],"discrete":[35,60],"nature":[36],"text,":[38],"during":[39],"training,":[40],"using":[41],"word":[42],"embeddings.":[43],"Our":[44],"method":[45],"is":[46],"agnostic":[47],"vocabulary":[49],"size":[50],"and":[51],"achieves":[52],"competitive":[53],"results":[54],"relative":[55],"methods":[57],"with":[58],"various":[59],"gradient":[61],"estimators.":[62]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}
