{"id":"https://openalex.org/W3138368906","doi":"https://doi.org/10.1145/3447548.3467418","title":"Controllable Generation from Pre-trained Language Models via Inverse Prompting","display_name":"Controllable Generation from Pre-trained Language Models via Inverse Prompting","publication_year":2021,"publication_date":"2021-08-12","ids":{"openalex":"https://openalex.org/W3138368906","doi":"https://doi.org/10.1145/3447548.3467418","mag":"3138368906"},"language":"en","primary_location":{"id":"doi:10.1145/3447548.3467418","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3467418","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2103.10685","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Xu Zou","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xu Zou","raw_affiliation_strings":["Tsinghua University & Beijing Academy of Artificial Intelligence, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University & Beijing Academy of Artificial Intelligence, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Da Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Da Yin","raw_affiliation_strings":["Tsinghua University & Beijing Academy of Artificial Intelligence, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University & Beijing Academy of Artificial Intelligence, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Qingyang Zhong","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingyang Zhong","raw_affiliation_strings":["Tsinghua University & Beijing Academy of Artificial Intelligence, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University & Beijing Academy of Artificial Intelligence, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hongxia Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongxia Yang","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhilin Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhilin Yang","raw_affiliation_strings":["Recurrent AI, Ltd & Beijing Academy of Artificial Intelligence, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Recurrent AI, Ltd & Beijing Academy of Artificial Intelligence, Beijing, China","institution_ids":["https://openalex.org/I4210100255"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jie Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Tang","raw_affiliation_strings":["Tsinghua University & Beijing Academy of Artificial Intelligence, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University & Beijing Academy of Artificial Intelligence, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":2.7991,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.91884123,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2450","last_page":"2460"},"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":0.9975000023841858,"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":0.9948999881744385,"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/language-model","display_name":"Language model","score":0.7190999984741211},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.5568000078201294},{"id":"https://openalex.org/keywords/natural-language-generation","display_name":"Natural language generation","score":0.5157999992370605},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.49079999327659607},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4887999892234802},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4699999988079071},{"id":"https://openalex.org/keywords/text-generation","display_name":"Text generation","score":0.42170000076293945}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7595000267028809},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.7190999984741211},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.5568000078201294},{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.5157999992370605},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5022000074386597},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5011000037193298},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.49079999327659607},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4887999892234802},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4699999988079071},{"id":"https://openalex.org/C2985684807","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Text generation","level":2,"score":0.42170000076293945},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.4196999967098236},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.31279999017715454},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.31029999256134033},{"id":"https://openalex.org/C133162039","wikidata":"https://www.wikidata.org/wiki/Q1061077","display_name":"Code generation","level":3,"score":0.29649999737739563},{"id":"https://openalex.org/C18552078","wikidata":"https://www.wikidata.org/wiki/Q255615","display_name":"Code-switching","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.2892000079154968},{"id":"https://openalex.org/C2993724205","wikidata":"https://www.wikidata.org/wiki/Q315","display_name":"Human language","level":2,"score":0.27619999647140503},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C3018907156","wikidata":"https://www.wikidata.org/wiki/Q7785058","display_name":"Third generation","level":2,"score":0.25440001487731934}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3447548.3467418","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3467418","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2103.10685","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2103.10685","pdf_url":"https://arxiv.org/pdf/2103.10685","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2103.10685","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2103.10685","pdf_url":"https://arxiv.org/pdf/2103.10685","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2037043950","https://openalex.org/W2059488546","https://openalex.org/W2154241802","https://openalex.org/W2250539671","https://openalex.org/W2952771545","https://openalex.org/W2998453866","https://openalex.org/W7016021835"],"related_works":[],"abstract_inverted_index":{"Large-scale":[0],"pre-trained":[1],"language":[2,35,93],"models":[3],"have":[4],"demonstrated":[5],"strong":[6],"capabilities":[7],"of":[8,34,56,106,138],"generating":[9],"realistic":[10],"text.":[11],"However,":[12],"it":[13],"remains":[14],"challenging":[15],"to":[16,48,60,64,95,133],"control":[17,50],"the":[18,32,67,74,77,80,104,124,139,161],"generation":[19,109,129,146],"results.":[20],"Previous":[21],"approaches":[22],"such":[23],"as":[24],"prompting":[25,58],"are":[26],"far":[27],"from":[28],"sufficient,":[29],"which":[30,72],"limits":[31],"usage":[33],"models.":[36],"To":[37],"tackle":[38],"this":[39],"challenge,":[40],"we":[41,88],"propose":[42],"an":[43],"innovative":[44],"method,":[45],"inverse":[46,57],"prompting,":[47],"better":[49,85],"text":[51,63,82],"generation.":[52],"The":[53],"core":[54],"idea":[55],"is":[59,131,163],"use":[61],"generated":[62,81],"inversely":[65],"predict":[66],"prompt":[68,78],"during":[69],"beam":[70],"search,":[71],"enhances":[73],"relevance":[75],"between":[76],"and":[79,83,110,126],"provides":[84],"controllability.":[86],"Empirically,":[87],"pre-train":[89],"a":[90,97],"large-scale":[91],"Chinese":[92],"model":[94],"perform":[96],"systematic":[98],"study":[99],"using":[100],"human":[101,134],"evaluation":[102],"on":[103,136],"tasks":[105],"open-domain":[107,111],"poem":[108,145],"long-form":[112],"question":[113],"answering.":[114],"Our":[115],"results":[116],"show":[117],"that":[118,127],"our":[119,128,144,151],"proposed":[120],"method":[121],"substantially":[122],"outperforms":[123],"baselines":[125],"quality":[130],"close":[132],"performance":[135],"some":[137],"tasks.":[140],"Narrators":[141],"can":[142,154],"try":[143],"demo":[147,153],"at":[148,157],"https://pretrain.aminer.cn/apps/poetry.html,":[149],"while":[150],"QA":[152],"be":[155],"found":[156],"https://pretrain.aminer.cn/app/qa.":[158],"For":[159],"researchers,":[160],"code":[162],"provided":[164],"in":[165],"https://github.com/THUDM/InversePrompting.":[166]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":6}],"updated_date":"2026-04-06T07:47:59.780226","created_date":"2021-03-29T00:00:00"}