{"id":"https://openalex.org/W3035359363","doi":"https://doi.org/10.24963/ijcai.2020/553","title":"ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language Generation","display_name":"ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language Generation","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3035359363","doi":"https://doi.org/10.24963/ijcai.2020/553","mag":"3035359363"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2020/553","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/553","pdf_url":"https://www.ijcai.org/proceedings/2020/0553.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2020/0553.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108692923","display_name":"Dongling Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongling Xiao","raw_affiliation_strings":["Baidu, Inc","Baidu Inc., China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu, Inc","institution_ids":["https://openalex.org/I98301712"]},{"raw_affiliation_string":"Baidu Inc., China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100399325","display_name":"Han Zhang","orcid":"https://orcid.org/0000-0002-6258-2486"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han Zhang","raw_affiliation_strings":["Baidu, Inc","Baidu Inc., China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu, Inc","institution_ids":["https://openalex.org/I98301712"]},{"raw_affiliation_string":"Baidu Inc., China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100416172","display_name":"Yukun Li","orcid":"https://orcid.org/0000-0002-5363-5849"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yukun Li","raw_affiliation_strings":["Baidu, Inc","Baidu Inc., China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu, Inc","institution_ids":["https://openalex.org/I98301712"]},{"raw_affiliation_string":"Baidu Inc., China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101870256","display_name":"Yu Sun","orcid":"https://orcid.org/0000-0002-5430-5534"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Sun","raw_affiliation_strings":["Baidu, Inc","Baidu Inc., China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu, Inc","institution_ids":["https://openalex.org/I98301712"]},{"raw_affiliation_string":"Baidu Inc., China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071362658","display_name":"Hao Tian","orcid":"https://orcid.org/0000-0002-4810-5798"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Tian","raw_affiliation_strings":["Baidu, Inc","Baidu Inc., China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu, Inc","institution_ids":["https://openalex.org/I98301712"]},{"raw_affiliation_string":"Baidu Inc., China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100677198","display_name":"Hua Wu","orcid":"https://orcid.org/0000-0002-5687-7800"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hua Wu","raw_affiliation_strings":["Baidu, Inc","Baidu Inc., China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu, Inc","institution_ids":["https://openalex.org/I98301712"]},{"raw_affiliation_string":"Baidu Inc., China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100386394","display_name":"Haifeng Wang","orcid":"https://orcid.org/0000-0002-0672-7468"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haifeng Wang","raw_affiliation_strings":["Baidu, Inc","Baidu Inc., China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu, Inc","institution_ids":["https://openalex.org/I98301712"]},{"raw_affiliation_string":"Baidu Inc., China","institution_ids":["https://openalex.org/I98301712"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I98301712"],"apc_list":null,"apc_paid":null,"fwci":9.4298,"has_fulltext":false,"cited_by_count":107,"citation_normalized_percentile":{"value":0.98529036,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3997","last_page":"4003"},"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":0.9995999932289124,"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":0.9940000176429749,"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":0.8433231115341187},{"id":"https://openalex.org/keywords/natural-language-generation","display_name":"Natural language generation","score":0.8145184516906738},{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.6395375728607178},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5311103463172913},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.49133673310279846},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46415695548057556},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4528648257255554},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.43342870473861694},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.41261959075927734},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.3508508801460266},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.11635357141494751}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8433231115341187},{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.8145184516906738},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.6395375728607178},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5311103463172913},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.49133673310279846},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46415695548057556},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4528648257255554},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.43342870473861694},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.41261959075927734},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.3508508801460266},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.11635357141494751},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2020/553","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/553","pdf_url":"https://www.ijcai.org/proceedings/2020/0553.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2020/553","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/553","pdf_url":"https://www.ijcai.org/proceedings/2020/0553.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.8799999952316284}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3035359363.pdf","grobid_xml":"https://content.openalex.org/works/W3035359363.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W2176263492","https://openalex.org/W2890166583","https://openalex.org/W2896457183","https://openalex.org/W2938830017","https://openalex.org/W2944931850","https://openalex.org/W2945260553","https://openalex.org/W2949615363","https://openalex.org/W2952468927","https://openalex.org/W2962739339","https://openalex.org/W2962965405","https://openalex.org/W2963748441","https://openalex.org/W2964032708","https://openalex.org/W2964223283","https://openalex.org/W2970419734","https://openalex.org/W2970597249","https://openalex.org/W2970796366","https://openalex.org/W2971116243","https://openalex.org/W2996264288","https://openalex.org/W2997200074","https://openalex.org/W3011411500","https://openalex.org/W3034999214","https://openalex.org/W3035451444","https://openalex.org/W3036120435","https://openalex.org/W4288089799","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W2955859849","https://openalex.org/W2152921782","https://openalex.org/W382594479","https://openalex.org/W3034878914","https://openalex.org/W2470045054","https://openalex.org/W2575772232","https://openalex.org/W2151245229","https://openalex.org/W2140902089","https://openalex.org/W1510553545","https://openalex.org/W3020827637"],"abstract_inverted_index":{"Current":[0],"pre-training":[1,31,87,96,120],"works":[2],"in":[3],"natural":[4],"language":[5,128],"generation":[6,48,53,57,68,129,138,141],"pay":[7],"little":[8],"attention":[9],"to":[10,29,59,74,94],"the":[11,39,72,100],"problem":[12],"of":[13,119,127],"exposure":[14],"bias":[15],"on":[16,124],"downstream":[17],"tasks.":[18],"To":[19,55],"address":[20],"this":[21,63],"issue,":[22],"we":[23],"propose":[24],"an":[25,46],"enhanced":[26],"multi-flow":[27],"sequence":[28,30],"and":[32,43,50,104,122,135,143,151],"fine-tuning":[33],"framework":[34,64],"named":[35],"ERNIE-GEN,":[36],"which":[37,98],"bridges":[38],"discrepancy":[40],"between":[41,102],"training":[42],"inference":[44],"with":[45,114],"infilling":[47],"mechanism":[49],"a":[51,66,115,125],"noise-aware":[52],"method.":[54],"make":[56],"closer":[58],"human":[60],"writing":[61],"patterns,":[62],"introduces":[65],"span-by-span":[67],"flow":[69],"that":[70,109],"trains":[71],"model":[73],"predict":[75],"semantically-complete":[76],"spans":[77],"consecutively":[78],"rather":[79],"than":[80],"predicting":[81],"word":[82],"by":[83],"word.":[84],"Unlike":[85],"existing":[86],"methods,":[88],"ERNIE-GEN":[89,110],"incorporates":[90],"multi-granularity":[91],"target":[92],"sampling":[93],"construct":[95],"data,":[97],"enhances":[99],"correlation":[101],"encoder":[103],"decoder.":[105],"Experimental":[106],"results":[107,113],"demonstrate":[108],"achieves":[111],"state-of-the-art":[112],"much":[116],"smaller":[117],"amount":[118],"data":[121],"parameters":[123],"range":[126],"tasks,":[130],"including":[131],"abstractive":[132],"summarization":[133],"(Gigaword":[134],"CNN/DailyMail),":[136],"question":[137,145],"(SQuAD),":[139],"dialogue":[140],"(Persona-Chat)":[142],"generative":[144],"answering":[146],"(CoQA).":[147],"The":[148],"source":[149],"codes":[150],"pre-trained":[152],"models":[153],"have":[154],"been":[155],"released":[156],"at":[157],"https://github.com/PaddlePaddle/ERNIE/ernie-gen.":[158]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":22},{"year":2022,"cited_by_count":31},{"year":2021,"cited_by_count":27},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
