{"id":"https://openalex.org/W4290943347","doi":"https://doi.org/10.1145/3534678.3539069","title":"COBART: Controlled, Optimized, Bidirectional and Auto-Regressive Transformer for Ad Headline Generation","display_name":"COBART: Controlled, Optimized, Bidirectional and Auto-Regressive Transformer for Ad Headline Generation","publication_year":2022,"publication_date":"2022-08-12","ids":{"openalex":"https://openalex.org/W4290943347","doi":"https://doi.org/10.1145/3534678.3539069"},"language":"en","primary_location":{"id":"doi:10.1145/3534678.3539069","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3534678.3539069","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005536808","display_name":"Yashal Shakti Kanungo","orcid":null},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yashal Shakti Kanungo","raw_affiliation_strings":["Amazon, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Amazon, Seattle, WA, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049116525","display_name":"Gyanendra Das","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gyanendra Das","raw_affiliation_strings":["Amazon, Bangalore, India"],"affiliations":[{"raw_affiliation_string":"Amazon, Bangalore, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072724686","display_name":"A Pooja","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pooja A","raw_affiliation_strings":["Amazon, Bangalore, India"],"affiliations":[{"raw_affiliation_string":"Amazon, Bangalore, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109167303","display_name":"Sumit Negi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sumit Negi","raw_affiliation_strings":["Amazon, Bangalore, India"],"affiliations":[{"raw_affiliation_string":"Amazon, Bangalore, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5005536808"],"corresponding_institution_ids":["https://openalex.org/I1311688040"],"apc_list":null,"apc_paid":null,"fwci":0.7276,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.70938375,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3127","last_page":"3136"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11574","display_name":"Artificial Intelligence in Games","score":0.9936000108718872,"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/T11574","display_name":"Artificial Intelligence in Games","score":0.9936000108718872,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9886000156402588,"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/T11197","display_name":"Digital Games and Media","score":0.9866999983787537,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/headline","display_name":"Headline","score":0.9632032513618469},{"id":"https://openalex.org/keywords/prefix","display_name":"Prefix","score":0.8025248646736145},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7622720003128052},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6548917293548584},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5077906250953674},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11236408352851868},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.07393831014633179},{"id":"https://openalex.org/keywords/advertising","display_name":"Advertising","score":0.07362797856330872}],"concepts":[{"id":"https://openalex.org/C2778689934","wikidata":"https://www.wikidata.org/wiki/Q1313396","display_name":"Headline","level":2,"score":0.9632032513618469},{"id":"https://openalex.org/C141603448","wikidata":"https://www.wikidata.org/wiki/Q134830","display_name":"Prefix","level":2,"score":0.8025248646736145},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7622720003128052},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6548917293548584},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5077906250953674},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11236408352851868},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.07393831014633179},{"id":"https://openalex.org/C112698675","wikidata":"https://www.wikidata.org/wiki/Q37038","display_name":"Advertising","level":1,"score":0.07362797856330872},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","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/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":1,"locations":[{"id":"doi:10.1145/3534678.3539069","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3534678.3539069","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5600000023841858}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W2119717200","https://openalex.org/W2953171463","https://openalex.org/W2996832783","https://openalex.org/W2997920211"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W4285135530","https://openalex.org/W2380567098","https://openalex.org/W2035489689","https://openalex.org/W906669285","https://openalex.org/W1553197492","https://openalex.org/W85886512","https://openalex.org/W2515595154","https://openalex.org/W1514610457","https://openalex.org/W2996936737"],"abstract_inverted_index":{"Online":[0],"ads":[1],"are":[2,10],"essential":[3],"to":[4,42,72,95],"all":[5],"businesses":[6],"and":[7,23,29,35,68,90,100,111],"ad":[8,33,83,122],"headlines":[9,21,78],"one":[11],"of":[12,76],"their":[13,26],"core":[14],"creative":[15,37,98],"component.":[16],"Existing":[17],"methods":[18],"can":[19,91],"generate":[20,43],"automatically":[22],"also":[24,69,88],"optimize":[25],"click-through-rate":[27],"(CTR)":[28],"quality.":[30],"However,":[31],"evolving":[32],"formats":[34],"changing":[36],"requirements":[38,99],"make":[39],"it":[40],"difficult":[41],"optimized":[44],"&":[45],"customized":[46],"headlines.":[47],"We":[48],"propose":[49],"a":[50,106,112],"novel":[51],"method":[52,86],"that":[53],"uses":[54],"prefix":[55],"control":[56,73],"tokens":[57],"along":[58],"with":[59],"BART":[60],"[16]":[61],"fine-tuning.":[62],"It":[63],"yields":[64],"the":[65,74],"highest":[66],"CTR":[67,117],"allows":[70],"users":[71],"length":[75],"generated":[77],"for":[79],"use":[80],"across":[81],"different":[82],"formats.":[84],"The":[85],"is":[87],"flexible":[89],"easily":[92],"be":[93],"adapted":[94],"other":[96],"architectures,":[97],"optimization":[101],"criteria.":[102],"Our":[103],"experiments":[104],"demonstrate":[105],"25.82%":[107],"increment":[108,114],"in":[109,115],"Rouge-L":[110],"5.82%":[113],"estimated":[116],"over":[118],"previously":[119],"published":[120],"strong":[121],"headline":[123],"generation":[124],"baseline.":[125]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}