{"id":"https://openalex.org/W2625357353","doi":"https://doi.org/10.48550/arxiv.1706.03850","title":"Adversarial Feature Matching for Text Generation","display_name":"Adversarial Feature Matching for Text Generation","publication_year":2017,"publication_date":"2017-06-12","ids":{"openalex":"https://openalex.org/W2625357353","doi":"https://doi.org/10.48550/arxiv.1706.03850","mag":"2625357353"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:1706.03850","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1706.03850","pdf_url":"https://arxiv.org/pdf/1706.03850","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,"listed_in":[],"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"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1706.03850","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101959000","display_name":"Yizhe Zhang","orcid":"https://orcid.org/0000-0002-9599-7995","observed_orcids":["https://orcid.org/0000-0002-9599-7995"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yizhe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066666034","display_name":"Zhe Gan","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gan, Zhe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055225377","display_name":"Kai Fan","orcid":"https://orcid.org/0000-0002-8256-0807","observed_orcids":["https://orcid.org/0000-0002-8256-0807"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan, Kai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017769599","display_name":"Zhi Chen","orcid":"https://orcid.org/0000-0002-4734-368X","observed_orcids":["https://orcid.org/0000-0002-4734-368X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Zhi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056639842","display_name":"Ricardo Henao","orcid":"https://orcid.org/0000-0003-4980-845X","observed_orcids":["https://orcid.org/0000-0003-4980-845X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Henao, Ricardo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013573244","display_name":"Dinghan Shen","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Dinghan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5016448581","display_name":"Lawrence Carin","orcid":"https://orcid.org/0000-0001-6277-7948","observed_orcids":["https://orcid.org/0000-0001-6277-7948"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Carin, Lawrence","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":292,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4006","last_page":"4015"},"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":0.551800012588501,"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":0.551800012588501,"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/T10028","display_name":"Topic Modeling","score":0.40869998931884766,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.017999999225139618,"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/text-generation","display_name":"text generation","score":0.7509999871253967},{"id":"https://openalex.org/keywords/generative-adversarial-networks","display_name":"generative adversarial networks","score":0.9660000205039978},{"id":"https://openalex.org/keywords/adversarial-training","display_name":"adversarial training","score":0.8209999799728394},{"id":"https://openalex.org/keywords/mode-collapse","display_name":"mode collapse","score":0.9229999780654907},{"id":"https://openalex.org/keywords/synthetic-text","display_name":"synthetic text","score":0.5249999761581421}],"concepts":[{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.8958467841148376},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7619068622589111},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.7061092853546143},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6850030422210693},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6727907657623291},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6619847416877747},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6367352604866028},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6277800798416138},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.596066951751709},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5147287845611572},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.47494247555732727},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42106959223747253},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33780425786972046},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.328673779964447},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27392271161079407},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09968909621238708},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07064273953437805},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"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/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","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/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"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":3,"locations":[{"id":"pmh:oai:arXiv.org:1706.03850","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1706.03850","pdf_url":"https://arxiv.org/pdf/1706.03850","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,"listed_in":[],"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":"doi:10.48550/arxiv.1706.03850","doi":"https://doi.org/10.48550/arxiv.1706.03850","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1706.03850","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,"listed_in":[],"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":false,"raw_source_name":null,"raw_type":"Preprint"},{"id":"mag:2964017345","doi":null,"is_oa":false,"landing_page_url":"http://proceedings.mlr.press/v70/zhang17b/zhang17b.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306419644","display_name":"International Conference on Machine Learning","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Machine Learning","raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1706.03850","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1706.03850","pdf_url":"https://arxiv.org/pdf/1706.03850","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,"listed_in":[],"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"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"},{"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/W2625357353.pdf","grobid_xml":"https://content.openalex.org/works/W2625357353.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W10548402","https://openalex.org/W648786980","https://openalex.org/W930928758","https://openalex.org/W1487641199","https://openalex.org/W1566289585","https://openalex.org/W1606347560","https://openalex.org/W1832693441","https://openalex.org/W1836465849","https://openalex.org/W1959608418","https://openalex.org/W2064675550","https://openalex.org/W2079735306","https://openalex.org/W2099057450","https://openalex.org/W2099471712","https://openalex.org/W2101105183","https://openalex.org/W2119717200","https://openalex.org/W2125389028","https://openalex.org/W2130942839","https://openalex.org/W2170738476","https://openalex.org/W2174424190","https://openalex.org/W2187089797","https://openalex.org/W2202109488","https://openalex.org/W2210838531","https://openalex.org/W2212660284","https://openalex.org/W2411541852","https://openalex.org/W2412320034","https://openalex.org/W2419501139","https://openalex.org/W2432004435","https://openalex.org/W2434741482","https://openalex.org/W2441221256","https://openalex.org/W2521028896","https://openalex.org/W2527569769","https://openalex.org/W2542835211","https://openalex.org/W2547875792","https://openalex.org/W2548228487","https://openalex.org/W2554314924","https://openalex.org/W2557046619","https://openalex.org/W2579277680","https://openalex.org/W2581485081","https://openalex.org/W2581637843","https://openalex.org/W2949300694","https://openalex.org/W2950635152","https://openalex.org/W2952230511","https://openalex.org/W2963167310","https://openalex.org/W2963921497","https://openalex.org/W2964025273","https://openalex.org/W2964121744","https://openalex.org/W2964167449","https://openalex.org/W2964268978","https://openalex.org/W3037567775","https://openalex.org/W6884735978"],"related_works":["https://openalex.org/W2891641674","https://openalex.org/W2972862192","https://openalex.org/W4306832680","https://openalex.org/W4375869252","https://openalex.org/W2895824518","https://openalex.org/W6920537955","https://openalex.org/W2969990170","https://openalex.org/W2995028880","https://openalex.org/W2763823773","https://openalex.org/W3136302691"],"abstract_inverted_index":{"The":[0],"Generative":[1],"Adversarial":[2],"Network":[3],"(GAN)":[4],"has":[5],"achieved":[6],"great":[7],"success":[8],"in":[9,97],"generating":[10,36],"realistic":[11,37],"(real-valued)":[12],"synthetic":[13,76],"data.":[14],"However,":[15],"convergence":[16],"issues":[17],"and":[18,51,75,100],"difficulties":[19],"dealing":[20],"with":[21],"discrete":[22],"data":[23],"hinder":[24],"the":[25,60,68,89],"applicability":[26],"of":[27,58,63,73],"GAN":[28],"to":[29],"text.":[30],"We":[31,42],"propose":[32,66],"a":[33,44,52,79],"framework":[34],"for":[35],"text":[38],"via":[39,78],"adversarial":[40,85],"training.":[41],"employ":[43],"long":[45],"short-term":[46],"memory":[47],"network":[48,54],"as":[49,55],"generator,":[50],"convolutional":[53],"discriminator.":[56],"Instead":[57],"using":[59],"standard":[61],"objective":[62],"GAN,":[64],"we":[65],"matching":[67],"high-dimensional":[69],"latent":[70],"feature":[71],"distributions":[72],"real":[74],"sentences,":[77],"kernelized":[80],"discrepancy":[81],"metric.":[82],"This":[83],"eases":[84],"training":[86],"by":[87],"alleviating":[88],"mode-collapsing":[90],"problem.":[91],"Our":[92],"experiments":[93],"show":[94],"superior":[95],"performance":[96],"quantitative":[98],"evaluation,":[99],"demonstrate":[101],"that":[102],"our":[103],"model":[104],"can":[105],"generate":[106],"realistic-looking":[107],"sentences.":[108]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":26},{"year":2023,"cited_by_count":25},{"year":2022,"cited_by_count":24},{"year":2021,"cited_by_count":44},{"year":2020,"cited_by_count":64},{"year":2019,"cited_by_count":59},{"year":2018,"cited_by_count":36},{"year":2017,"cited_by_count":2}],"updated_date":"2026-11-05T12:25:35.769452","created_date":"2017-06-23T00:00:00"}