{"id":"https://openalex.org/W3134248572","doi":"https://doi.org/10.1017/s1351324922000031","title":"Topical language generation using transformers","display_name":"Topical language generation using transformers","publication_year":2022,"publication_date":"2022-02-04","ids":{"openalex":"https://openalex.org/W3134248572","doi":"https://doi.org/10.1017/s1351324922000031","mag":"3134248572"},"language":"en","primary_location":{"id":"doi:10.1017/s1351324922000031","is_oa":false,"landing_page_url":"https://doi.org/10.1017/s1351324922000031","pdf_url":null,"source":{"id":"https://openalex.org/S18088403","display_name":"Natural Language Engineering","issn_l":"1351-3249","issn":["1351-3249","1469-8110"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Natural Language Engineering","raw_type":"journal-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2103.06434","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051282919","display_name":"Rohola Zandie","orcid":null},"institutions":[{"id":"https://openalex.org/I131651094","display_name":"University of Denver","ror":"https://ror.org/04w7skc03","country_code":"US","type":"education","lineage":["https://openalex.org/I131651094"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Rohola Zandie","raw_affiliation_strings":["University of Denver;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Denver;","institution_ids":["https://openalex.org/I131651094"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041948053","display_name":"Mohammad H. Mahoor","orcid":"https://orcid.org/0000-0001-8923-4660"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mohammad H. Mahoor","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-8923-4660","affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5051282919"],"corresponding_institution_ids":["https://openalex.org/I131651094"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.00343932,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"29","issue":"2","first_page":"337","last_page":"359"},"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":0.9994999766349792,"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/T13083","display_name":"Advanced Text Analysis 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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7934706211090088},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.7320655584335327},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.5924660563468933},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.560382604598999},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4998619556427002},{"id":"https://openalex.org/keywords/fluency","display_name":"Fluency","score":0.48711562156677246},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.47933730483055115},{"id":"https://openalex.org/keywords/scripting-language","display_name":"Scripting language","score":0.422166109085083},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.420526385307312},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.41926872730255127},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4028368890285492},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3573489487171173}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7934706211090088},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.7320655584335327},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.5924660563468933},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.560382604598999},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4998619556427002},{"id":"https://openalex.org/C2777413886","wikidata":"https://www.wikidata.org/wiki/Q3276013","display_name":"Fluency","level":2,"score":0.48711562156677246},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.47933730483055115},{"id":"https://openalex.org/C61423126","wikidata":"https://www.wikidata.org/wiki/Q187432","display_name":"Scripting language","level":2,"score":0.422166109085083},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.420526385307312},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.41926872730255127},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4028368890285492},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3573489487171173},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"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":4,"locations":[{"id":"doi:10.1017/s1351324922000031","is_oa":false,"landing_page_url":"https://doi.org/10.1017/s1351324922000031","pdf_url":null,"source":{"id":"https://openalex.org/S18088403","display_name":"Natural Language Engineering","issn_l":"1351-3249","issn":["1351-3249","1469-8110"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Natural Language Engineering","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2103.06434","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2103.06434","pdf_url":"https://arxiv.org/pdf/2103.06434","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:3134248572","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2103.06434.pdf","pdf_url":null,"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":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2103.06434","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2103.06434","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2103.06434","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2103.06434","pdf_url":"https://arxiv.org/pdf/2103.06434","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.8600000143051147,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3134248572.pdf","grobid_xml":"https://content.openalex.org/works/W3134248572.grobid-xml"},"referenced_works_count":56,"referenced_works":["https://openalex.org/W46679369","https://openalex.org/W1880262756","https://openalex.org/W1983249544","https://openalex.org/W1983874169","https://openalex.org/W2019515298","https://openalex.org/W2038043464","https://openalex.org/W2114199242","https://openalex.org/W2117756735","https://openalex.org/W2147152072","https://openalex.org/W2153579005","https://openalex.org/W2165599843","https://openalex.org/W2210838531","https://openalex.org/W2253795368","https://openalex.org/W2373570000","https://openalex.org/W2521114121","https://openalex.org/W2577946330","https://openalex.org/W2735642330","https://openalex.org/W2740094762","https://openalex.org/W2741986794","https://openalex.org/W2757836268","https://openalex.org/W2788321882","https://openalex.org/W2797786618","https://openalex.org/W2890276793","https://openalex.org/W2916772188","https://openalex.org/W2962966012","https://openalex.org/W2963034998","https://openalex.org/W2963035145","https://openalex.org/W2963123301","https://openalex.org/W2963174344","https://openalex.org/W2963223306","https://openalex.org/W2963248348","https://openalex.org/W2963283805","https://openalex.org/W2963403868","https://openalex.org/W2963631950","https://openalex.org/W2963667126","https://openalex.org/W2964008635","https://openalex.org/W2964268978","https://openalex.org/W2970476646","https://openalex.org/W2970641574","https://openalex.org/W2970777192","https://openalex.org/W2971524460","https://openalex.org/W2972664115","https://openalex.org/W2972916088","https://openalex.org/W2973049837","https://openalex.org/W2986068180","https://openalex.org/W2995404354","https://openalex.org/W2996287690","https://openalex.org/W3035068109","https://openalex.org/W6601894380","https://openalex.org/W6639619044","https://openalex.org/W6684489972","https://openalex.org/W6739901393","https://openalex.org/W6741121127","https://openalex.org/W6761551260","https://openalex.org/W6767057552","https://openalex.org/W6778883912"],"related_works":["https://openalex.org/W2897193746","https://openalex.org/W2803295639","https://openalex.org/W3137121515","https://openalex.org/W2970789589","https://openalex.org/W2418993857","https://openalex.org/W1571842286","https://openalex.org/W2375677381","https://openalex.org/W3007474616","https://openalex.org/W3092956426","https://openalex.org/W2951719623","https://openalex.org/W654937010","https://openalex.org/W2261925631","https://openalex.org/W3020267361","https://openalex.org/W2045966063","https://openalex.org/W2135479201","https://openalex.org/W2187946878","https://openalex.org/W2989639774","https://openalex.org/W2790359648","https://openalex.org/W2808185155","https://openalex.org/W2112648537"],"abstract_inverted_index":{"Abstract":[0],"Large-scale":[1],"transformer-based":[2],"language":[3,54],"models":[4],"(LMs)":[5],"demonstrate":[6,149],"impressive":[7],"capabilities":[8],"in":[9,127,165],"open-text":[10],"generation.":[11],"However,":[12],"controlling":[13],"the":[14,20,33,40,68,83,89,93,97,102,120,123,128,139,143,154],"generated":[15,129,144],"text\u2019s":[16],"properties":[17,141],"such":[18],"as":[19,77,82,88],"topic,":[21],"style,":[22],"and":[23,27,38,85,116,160],"sentiment":[24],"is":[25],"challenging":[26],"often":[28],"requires":[29],"significant":[30],"changes":[31],"to":[32,118,136],"model":[34,41,111,152],"architecture":[35],"or":[36],"retraining":[37],"fine-tuning":[39],"on":[42,157],"new":[43,114],"supervised":[44],"data.":[45],"This":[46,131],"paper":[47],"presents":[48],"a":[49,59,78],"novel":[50],"approach":[51],"for":[52],"topical":[53,124,140],"generation":[55],"(TLG)":[56],"by":[57,112],"combining":[58],"pre-trained":[60],"LM":[61,80],"with":[62,74],"topic":[63,75,98],"modeling":[64],"information.":[65],"We":[66],"cast":[67],"problem":[69],"using":[70],"Bayesian":[71],"probability":[72,87,99],"formulation":[73],"probabilities":[76,81],"prior,":[79],"likelihood,":[84],"TLG":[86],"posterior.":[90],"In":[91],"learning":[92],"model,":[94],"we":[95,108],"derive":[96],"distribution":[100],"from":[101],"user-provided":[103],"document\u2019s":[104],"natural":[105],"structure.":[106],"Furthermore,":[107],"extend":[109],"our":[110,151],"introducing":[113],"parameters":[115],"functions":[117],"influence":[119],"quantity":[121],"of":[122,142],"features":[125],"presented":[126],"text.":[130,145],"feature":[132],"would":[133],"allow":[134],"us":[135],"easily":[137],"control":[138],"Our":[146],"experimental":[147],"results":[148,156],"that":[150],"outperforms":[153],"state-of-the-art":[155],"coherency,":[158],"diversity,":[159],"fluency":[161],"while":[162],"being":[163],"faster":[164],"decoding.":[166]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
