{"id":"https://openalex.org/W3191406681","doi":"https://doi.org/10.24963/ijcai.2021/534","title":"Improving Text Generation with Dynamic Masking and Recovering","display_name":"Improving Text Generation with Dynamic Masking and Recovering","publication_year":2021,"publication_date":"2021-08-01","ids":{"openalex":"https://openalex.org/W3191406681","doi":"https://doi.org/10.24963/ijcai.2021/534","mag":"3191406681"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2021/534","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2021/534","pdf_url":"https://www.ijcai.org/proceedings/2021/0534.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2021/0534.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100676625","display_name":"Zhidong Liu","orcid":"https://orcid.org/0000-0002-1584-3743"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhidong Liu","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100369260","display_name":"Junhui Li","orcid":"https://orcid.org/0000-0001-7829-6348"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junhui Li","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101923144","display_name":"Muhua Zhu","orcid":"https://orcid.org/0000-0002-6519-2379"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Muhua Zhu","raw_affiliation_strings":["Tencent News, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tencent News, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100676625"],"corresponding_institution_ids":["https://openalex.org/I3923682"],"apc_list":null,"apc_paid":null,"fwci":0.1936,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.48781359,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3878","last_page":"3884"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9998999834060669,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9998999834060669,"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":0.9991000294685364,"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":0.9983999729156494,"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":0.8787124156951904},{"id":"https://openalex.org/keywords/text-generation","display_name":"Text generation","score":0.6880669593811035},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.6709083914756775},{"id":"https://openalex.org/keywords/generality","display_name":"Generality","score":0.6539429426193237},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5777561664581299},{"id":"https://openalex.org/keywords/closed-captioning","display_name":"Closed captioning","score":0.5565605759620667},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5434731245040894},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.4909982979297638},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.47866830229759216},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47593215107917786},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4399496614933014},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.42188209295272827},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.36277300119400024},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1727140247821808}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8787124156951904},{"id":"https://openalex.org/C2985684807","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Text generation","level":2,"score":0.6880669593811035},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.6709083914756775},{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.6539429426193237},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5777561664581299},{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.5565605759620667},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5434731245040894},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.4909982979297638},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.47866830229759216},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47593215107917786},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4399496614933014},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.42188209295272827},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.36277300119400024},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1727140247821808},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","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},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2021/534","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2021/534","pdf_url":"https://www.ijcai.org/proceedings/2021/0534.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2021/534","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2021/534","pdf_url":"https://www.ijcai.org/proceedings/2021/0534.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.4399999976158142}],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5249178904","display_name":null,"funder_award_id":"Grant No. 6","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5678221373","display_name":null,"funder_award_id":"61876120","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5848258319","display_name":null,"funder_award_id":"0 and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7726157001","display_name":null,"funder_award_id":"Grant No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3191406681.pdf","grobid_xml":"https://content.openalex.org/works/W3191406681.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W222053410","https://openalex.org/W639708223","https://openalex.org/W1861492603","https://openalex.org/W1956340063","https://openalex.org/W2123301721","https://openalex.org/W2154652894","https://openalex.org/W2277195237","https://openalex.org/W2481240925","https://openalex.org/W2506483933","https://openalex.org/W2546938941","https://openalex.org/W2758950307","https://openalex.org/W2767899794","https://openalex.org/W2896457183","https://openalex.org/W2914120296","https://openalex.org/W2933138175","https://openalex.org/W2952468927","https://openalex.org/W2952809536","https://openalex.org/W2962784628","https://openalex.org/W2962905474","https://openalex.org/W2963212250","https://openalex.org/W2963216553","https://openalex.org/W2964048171","https://openalex.org/W2964345285","https://openalex.org/W2966469393","https://openalex.org/W2971087717","https://openalex.org/W2998508940","https://openalex.org/W3191852631","https://openalex.org/W4300677102","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W4210416330","https://openalex.org/W2775506363","https://openalex.org/W3088136942","https://openalex.org/W4290852288","https://openalex.org/W2949362007","https://openalex.org/W4283207562","https://openalex.org/W2963177403","https://openalex.org/W2988673764","https://openalex.org/W2996388263","https://openalex.org/W4388685619"],"abstract_inverted_index":{"Due":[0],"to":[1,21,49,104,115],"different":[2,12],"types":[3],"of":[4,25,60,79,93,159],"inputs,":[5],"diverse":[6],"text":[7,55,125],"generation":[8,27,38,56,126],"tasks":[9,28,127],"may":[10,32],"adopt":[11],"encoder-decoder":[13,62],"frameworks.":[14,63],"Thus":[15],"most":[16],"existing":[17],"approaches":[18],"that":[19,138],"aim":[20],"improve":[22,144],"the":[23,51,58,82,87,106,139,155],"robustness":[24],"certain":[26],"are":[29],"input-relevant,":[30],"and":[31,134,157],"not":[33],"work":[34],"well":[35],"for":[36,54],"other":[37],"tasks.":[39],"Alternatively,":[40],"in":[41],"this":[42,90],"paper":[43],"we":[44,71,99,110],"present":[45],"a":[46],"universal":[47],"approach":[48,141],"enhance":[50],"language":[52],"representation":[53],"on":[57,81,123],"base":[59],"generic":[61],"This":[64,153],"is":[65],"done":[66],"from":[67],"two":[68],"levels.":[69],"First,":[70],"introduce":[72],"randomness":[73],"by":[74],"randomly":[75],"masking":[76],"some":[77],"percentage":[78],"tokens":[80],"decoder":[83],"side":[84],"when":[85],"training":[86],"models.":[88],"In":[89],"way,":[91],"instead":[92],"using":[94,149],"ground":[95],"truth":[96],"history":[97],"context,":[98],"use":[100],"its":[101],"corrupted":[102],"version":[103],"predict":[105],"next":[107],"token.":[108],"Then":[109],"propose":[111],"an":[112],"auxiliary":[113],"task":[114],"properly":[116],"recover":[117],"those":[118],"masked":[119],"tokens.":[120],"Experimental":[121],"results":[122],"several":[124],"including":[128],"machine":[129],"translation":[130],"(MT),":[131],"AMR-to-text":[132],"generation,":[133],"image":[135],"captioning":[136],"show":[137],"proposed":[140,161],"can":[142],"significantly":[143],"over":[145],"competitive":[146],"baselines":[147],"without":[148],"any":[150],"task-specific":[151],"techniques.":[152],"suggests":[154],"effectiveness":[156],"generality":[158],"our":[160],"approach.":[162]},"counts_by_year":[{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}