{"id":"https://openalex.org/W4385573325","doi":"https://doi.org/10.18653/v1/2022.emnlp-main.801","title":"ZeroGen: Efficient Zero-shot Learning via Dataset Generation","display_name":"ZeroGen: Efficient Zero-shot Learning via Dataset Generation","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4385573325","doi":"https://doi.org/10.18653/v1/2022.emnlp-main.801"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2022.emnlp-main.801","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.emnlp-main.801","pdf_url":"https://aclanthology.org/2022.emnlp-main.801.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 2022 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2022.emnlp-main.801.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102844797","display_name":"Jiacheng Ye","orcid":"https://orcid.org/0009-0008-6306-311X"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]},{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN","HK"],"is_corresponding":true,"raw_author_name":"Jiacheng Ye","raw_affiliation_strings":["\u2662 Shanghai AI Laboratory \u2663 Huawei Noah's Ark Lab \u2661 University of Washington \u2660 The University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"\u2662 Shanghai AI Laboratory \u2663 Huawei Noah's Ark Lab \u2661 University of Washington \u2660 The University of Hong Kong","institution_ids":["https://openalex.org/I2250955327","https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067047605","display_name":"Jiahui Gao","orcid":"https://orcid.org/0000-0002-4244-174X"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]},{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN","HK"],"is_corresponding":false,"raw_author_name":"Jiahui Gao","raw_affiliation_strings":["\u2662 Shanghai AI Laboratory \u2663 Huawei Noah's Ark Lab \u2661 University of Washington \u2660 The University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"\u2662 Shanghai AI Laboratory \u2663 Huawei Noah's Ark Lab \u2661 University of Washington \u2660 The University of Hong Kong","institution_ids":["https://openalex.org/I2250955327","https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075350251","display_name":"Qintong Li","orcid":"https://orcid.org/0000-0002-8447-9770"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["CN","HK"],"is_corresponding":false,"raw_author_name":"Qintong Li","raw_affiliation_strings":["\u2662 Shanghai AI Laboratory \u2663 Huawei Noah's Ark Lab \u2661 University of Washington \u2660 The University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"\u2662 Shanghai AI Laboratory \u2663 Huawei Noah's Ark Lab \u2661 University of Washington \u2660 The University of Hong Kong","institution_ids":["https://openalex.org/I2250955327","https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066768790","display_name":"Hang Xu","orcid":"https://orcid.org/0000-0003-4176-0738"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]},{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN","HK"],"is_corresponding":false,"raw_author_name":"Hang Xu","raw_affiliation_strings":["\u2662 Shanghai AI Laboratory \u2663 Huawei Noah's Ark Lab \u2661 University of Washington \u2660 The University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"\u2662 Shanghai AI Laboratory \u2663 Huawei Noah's Ark Lab \u2661 University of Washington \u2660 The University of Hong Kong","institution_ids":["https://openalex.org/I2250955327","https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100524347","display_name":"Jiangtao Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]},{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN","HK"],"is_corresponding":false,"raw_author_name":"Jiangtao Feng","raw_affiliation_strings":["\u2662 Shanghai AI Laboratory \u2663 Huawei Noah's Ark Lab \u2661 University of Washington \u2660 The University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"\u2662 Shanghai AI Laboratory \u2663 Huawei Noah's Ark Lab \u2661 University of Washington \u2660 The University of Hong Kong","institution_ids":["https://openalex.org/I2250955327","https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100667025","display_name":"Zhiyong Wu","orcid":"https://orcid.org/0000-0002-6527-5502"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["CN","HK"],"is_corresponding":false,"raw_author_name":"Zhiyong Wu","raw_affiliation_strings":["\u2662 Shanghai AI Laboratory \u2663 Huawei Noah's Ark Lab \u2661 University of Washington \u2660 The University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"\u2662 Shanghai AI Laboratory \u2663 Huawei Noah's Ark Lab \u2661 University of Washington \u2660 The University of Hong Kong","institution_ids":["https://openalex.org/I2250955327","https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100402028","display_name":"Changyuan Yu","orcid":"https://orcid.org/0000-0002-3185-0441"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["CN","HK"],"is_corresponding":false,"raw_author_name":"Tao Yu","raw_affiliation_strings":["\u2662 Shanghai AI Laboratory \u2663 Huawei Noah's Ark Lab \u2661 University of Washington \u2660 The University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"\u2662 Shanghai AI Laboratory \u2663 Huawei Noah's Ark Lab \u2661 University of Washington \u2660 The University of Hong Kong","institution_ids":["https://openalex.org/I2250955327","https://openalex.org/I889458895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014554970","display_name":"Lingpeng Kong","orcid":"https://orcid.org/0000-0002-9033-2724"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]},{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN","HK"],"is_corresponding":false,"raw_author_name":"Lingpeng Kong","raw_affiliation_strings":["\u2662 Shanghai AI Laboratory \u2663 Huawei Noah's Ark Lab \u2661 University of Washington \u2660 The University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"\u2662 Shanghai AI Laboratory \u2663 Huawei Noah's Ark Lab \u2661 University of Washington \u2660 The University of Hong Kong","institution_ids":["https://openalex.org/I2250955327","https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5102844797"],"corresponding_institution_ids":["https://openalex.org/I2250955327","https://openalex.org/I889458895"],"apc_list":null,"apc_paid":null,"fwci":12.479,"has_fulltext":true,"cited_by_count":96,"citation_normalized_percentile":{"value":0.98928041,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"11653","last_page":"11669"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9990000128746033,"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":0.9825000166893005,"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":0.8107047080993652},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.732485294342041},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7085610628128052},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6806659698486328},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6490026712417603},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.5982860326766968},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5761607885360718},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5453566312789917},{"id":"https://openalex.org/keywords/zero","display_name":"Zero (linguistics)","score":0.5263270735740662},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4469152092933655},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.41231709718704224}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8107047080993652},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.732485294342041},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7085610628128052},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6806659698486328},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6490026712417603},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.5982860326766968},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5761607885360718},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5453566312789917},{"id":"https://openalex.org/C2780813799","wikidata":"https://www.wikidata.org/wiki/Q3274237","display_name":"Zero (linguistics)","level":2,"score":0.5263270735740662},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4469152092933655},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.41231709718704224},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2022.emnlp-main.801","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.emnlp-main.801","pdf_url":"https://aclanthology.org/2022.emnlp-main.801.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 2022 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2022.emnlp-main.801","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.emnlp-main.801","pdf_url":"https://aclanthology.org/2022.emnlp-main.801.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 2022 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"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":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4385573325.pdf"},"referenced_works_count":66,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1821462560","https://openalex.org/W2113459411","https://openalex.org/W2250539671","https://openalex.org/W2251939518","https://openalex.org/W2551396370","https://openalex.org/W2557436004","https://openalex.org/W2767206889","https://openalex.org/W2938704169","https://openalex.org/W2948947170","https://openalex.org/W2949555952","https://openalex.org/W2952902402","https://openalex.org/W2963096510","https://openalex.org/W2963748441","https://openalex.org/W2965373594","https://openalex.org/W2968297680","https://openalex.org/W2970476646","https://openalex.org/W2973049837","https://openalex.org/W2978017171","https://openalex.org/W2979691890","https://openalex.org/W2980282514","https://openalex.org/W2988975212","https://openalex.org/W2996428491","https://openalex.org/W2998183051","https://openalex.org/W2998184481","https://openalex.org/W3010293452","https://openalex.org/W3034457371","https://openalex.org/W3038012435","https://openalex.org/W3044438666","https://openalex.org/W3098267758","https://openalex.org/W3099180151","https://openalex.org/W3099655892","https://openalex.org/W3101007570","https://openalex.org/W3105484636","https://openalex.org/W3105966348","https://openalex.org/W3106954555","https://openalex.org/W3116594510","https://openalex.org/W3120832022","https://openalex.org/W3128710690","https://openalex.org/W3134354193","https://openalex.org/W3154200459","https://openalex.org/W3160638507","https://openalex.org/W3170233084","https://openalex.org/W3170369042","https://openalex.org/W3173799534","https://openalex.org/W3198963017","https://openalex.org/W3201090304","https://openalex.org/W3201363102","https://openalex.org/W3205068155","https://openalex.org/W4205857304","https://openalex.org/W4206636317","https://openalex.org/W4221143046","https://openalex.org/W4221149883","https://openalex.org/W4226053218","https://openalex.org/W4226498390","https://openalex.org/W4253067820","https://openalex.org/W4286987939","https://openalex.org/W4287332927","https://openalex.org/W4287391717","https://openalex.org/W4287716221","https://openalex.org/W4288351520","https://openalex.org/W4288620900","https://openalex.org/W4288631803","https://openalex.org/W4384306313","https://openalex.org/W4385567008","https://openalex.org/W4385574293"],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W4287117424","https://openalex.org/W4387506531","https://openalex.org/W2087346071","https://openalex.org/W4238433571","https://openalex.org/W2967848559","https://openalex.org/W4299831724"],"abstract_inverted_index":{"There":[0],"is":[1],"a":[2,26,34,40,53],"growing":[3],"interest":[4],"in":[5,46],"dataset":[6,41],"generation":[7,114],"recently":[8],"due":[9],"to":[10,85],"the":[11,60,63,73,104,133],"superior":[12],"generative":[13],"capacity":[14],"of":[15,62,80,106,135],"large":[16],"pre-trained":[17],"language":[18,130],"models":[19],"(PLMs).":[20],"In":[21],"this":[22],"paper,":[23],"we":[24,37,51,94],"study":[25],"flexible":[27],"and":[28,92,111,117,128],"efficient":[29,70],"zero-short":[30],"learning":[31],"method,":[32],"ZeroGen.Given":[33],"zero-shot":[35],"task,":[36],"first":[38],"generate":[39],"from":[42,89,103],"scratch":[43],"using":[44],"PLMs":[45,86],"an":[47],"unsupervised":[48],"manner.":[49],"Then,":[50],"train":[52],"tiny":[54],"task":[55,75],"model":[56,76],"(e.g.,":[57,87],"LSTM)":[58],"under":[59],"supervision":[61],"synthesized":[64],"dataset.":[65],"This":[66],"approach":[67],"allows":[68],"highly":[69],"inference":[71],"as":[72],"final":[74],"only":[77],"has":[78],"orders":[79],"magnitude":[81],"fewer":[82],"parameters":[83],"comparing":[84],"GPT2-XL).Apart":[88],"being":[90],"annotation-free":[91],"efficient,":[93],"argue":[95],"that":[96],"ZeroGen":[97],"can":[98],"also":[99],"provide":[100],"useful":[101],"insights":[102],"perspective":[105],"data-free":[107],"model-agnostic":[108],"knowledge":[109],"distillation,":[110],"unreferenced":[112],"text":[113,124],"evaluation.":[115],"Experiments":[116],"analysis":[118],"on":[119],"different":[120],"NLP":[121],"tasks,":[122],"namely,":[123],"classification,":[125],"question":[126],"answering,":[127],"natural":[129],"inference,":[131],"show":[132],"effectiveness":[134],"ZeroGen.":[136]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":33},{"year":2024,"cited_by_count":21},{"year":2023,"cited_by_count":32},{"year":2022,"cited_by_count":4}],"updated_date":"2026-04-29T09:16:38.111599","created_date":"2025-10-10T00:00:00"}