{"id":"https://openalex.org/W3170407658","doi":"https://doi.org/10.1145/3447548.3467306","title":"Labeled Data Generation with Inexact Supervision","display_name":"Labeled Data Generation with Inexact Supervision","publication_year":2021,"publication_date":"2021-08-12","ids":{"openalex":"https://openalex.org/W3170407658","doi":"https://doi.org/10.1145/3447548.3467306","mag":"3170407658"},"language":"en","primary_location":{"id":"doi:10.1145/3447548.3467306","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3467306","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 &amp; 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/A5091395218","display_name":"Enyan Dai","orcid":"https://orcid.org/0000-0001-9715-0280"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Enyan Dai","raw_affiliation_strings":["The Pennsylvania State University, State College, PA, USA"],"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, State College, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058670321","display_name":"Kai Shu","orcid":"https://orcid.org/0000-0002-6043-1764"},"institutions":[{"id":"https://openalex.org/I180949307","display_name":"Illinois Institute of Technology","ror":"https://ror.org/037t3ry66","country_code":"US","type":"education","lineage":["https://openalex.org/I180949307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kai Shu","raw_affiliation_strings":["Illinois Institute of Technology, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"Illinois Institute of Technology, Chicago, IL, USA","institution_ids":["https://openalex.org/I180949307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006850220","display_name":"Yiwei Sun","orcid":"https://orcid.org/0000-0002-1259-5131"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiwei Sun","raw_affiliation_strings":["The Pennsylvania State University, State College, PA, USA"],"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, State College, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011048500","display_name":"Suhang Wang","orcid":"https://orcid.org/0000-0003-3448-4878"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Suhang Wang","raw_affiliation_strings":["The Pennsylvania State University, State College, PA, USA"],"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, State College, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5091395218"],"corresponding_institution_ids":["https://openalex.org/I130769515"],"apc_list":null,"apc_paid":null,"fwci":0.4079,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.67708816,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"218","last_page":"226"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9991999864578247,"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":0.9991999864578247,"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":0.9991000294685364,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9987999796867371,"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":0.852755606174469},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.826860785484314},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.7027460336685181},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6615127921104431},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6574088931083679},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5846815705299377},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4823957681655884},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.45492592453956604},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4315376281738281}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.852755606174469},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.826860785484314},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.7027460336685181},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6615127921104431},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6574088931083679},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5846815705299377},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4823957681655884},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.45492592453956604},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4315376281738281},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3447548.3467306","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3467306","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 &amp; Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5099999904632568,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G7065690185","display_name":null,"funder_award_id":"IIS-1909702, IIS1955851","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W652269744","https://openalex.org/W1921293667","https://openalex.org/W2163605009","https://openalex.org/W2188365844","https://openalex.org/W2194775991","https://openalex.org/W2293363371","https://openalex.org/W2548275288","https://openalex.org/W2552383788","https://openalex.org/W2577784528","https://openalex.org/W2769041395","https://openalex.org/W2802500193","https://openalex.org/W2907225248","https://openalex.org/W2924476266","https://openalex.org/W2932399282","https://openalex.org/W2951004968","https://openalex.org/W2962369866","https://openalex.org/W2963403868","https://openalex.org/W2963486920","https://openalex.org/W2963545832","https://openalex.org/W2964222296","https://openalex.org/W2966540341","https://openalex.org/W3127946721","https://openalex.org/W4235216760","https://openalex.org/W6600339457","https://openalex.org/W6600339963","https://openalex.org/W6814250579"],"related_works":["https://openalex.org/W3210196349","https://openalex.org/W4214728004","https://openalex.org/W4377865163","https://openalex.org/W2950181282","https://openalex.org/W2963261224","https://openalex.org/W2798287483","https://openalex.org/W3193857078","https://openalex.org/W2888956734","https://openalex.org/W2913410650","https://openalex.org/W3208304128"],"abstract_inverted_index":{"The":[0,22],"recent":[1],"advanced":[2],"deep":[3,25,65],"learning":[4,30,189],"techniques":[5],"have":[6],"shown":[7],"the":[8,86,108,120,144,149,196,212,215,228],"promising":[9,125],"results":[10,205],"in":[11,28],"various":[12,52],"domains":[13],"such":[14,54],"as":[15,55,176],"computer":[16],"vision":[17],"and":[18,59,100,132,195,201,208],"natural":[19],"language":[20],"processing.":[21],"success":[23],"of":[24,37,57,69,98,162,214],"neural":[26],"networks":[27],"supervised":[29],"heavily":[31],"relies":[32],"on":[33,151,206],"a":[34,159,171],"large":[35],"amount":[36],"labeled":[38,42,140,163,182,221],"data.":[39],"However,":[40,148],"obtaining":[41],"data":[43,77,141,164,183,191,222],"with":[44,78,96,102,135,166,192],"target":[45,87,112,121,136,185,202,229],"labels":[46,110],"is":[47,72,124,153],"often":[48],"challenging":[49],"due":[50],"to":[51,75,85,119,126,138,142,226],"reasons":[53],"cost":[56],"labeling":[58],"privacy":[60],"issues,":[61],"which":[62,105,178],"challenges":[63],"existing":[64],"models.":[66],"In":[67],"spite":[68],"that,":[70],"it":[71],"relatively":[73],"easy":[74],"obtain":[76],"inexact":[79,167,193,199,224],"supervision,":[80],"i.e.,":[81],"having":[82],"labels/tags":[83],"related":[84,118],"task.":[88,231],"For":[89],"example,":[90],"social":[91],"media":[92],"platforms":[93],"are":[94,106,116],"overwhelmed":[95],"billions":[97],"posts":[99],"images":[101],"self-customized":[103],"tags,":[104],"not":[107],"exact":[109],"for":[111,184,218],"classification":[113,146,186,230],"tasks":[114,187],"but":[115],"usually":[117],"labels.":[122],"It":[123],"leverage":[127],"these":[128],"tags":[129],"(inexact":[130],"supervision)":[131],"their":[133],"relations":[134,197],"classes":[137],"generate":[139],"facilitate":[143,227],"downstream":[145],"tasks.":[147],"work":[150],"this":[152],"rather":[154],"limited.":[155],"Therefore,":[156],"we":[157],"study":[158],"novel":[160,172],"problem":[161],"generation":[165],"supervision.":[168],"We":[169],"propose":[170],"generative":[173],"framework":[174],"named":[175],"ADDES":[177,217],"can":[179],"synthesize":[180],"high-quality":[181],"by":[188],"from":[190,223],"supervision":[194,200,225],"between":[198],"classes.":[203],"Experimental":[204],"image":[207],"text":[209],"datasets":[210],"demonstrate":[211],"effectiveness":[213],"proposed":[216],"generating":[219],"realistic":[220]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
