{"id":"https://openalex.org/W2936696202","doi":"https://doi.org/10.1109/wacv45572.2020.9093390","title":"Active Adversarial Domain Adaptation","display_name":"Active Adversarial Domain Adaptation","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W2936696202","doi":"https://doi.org/10.1109/wacv45572.2020.9093390","mag":"2936696202"},"language":"en","primary_location":{"id":"doi:10.1109/wacv45572.2020.9093390","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093390","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1904.07848","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046487166","display_name":"Jong-Chyi Su","orcid":"https://orcid.org/0000-0002-7933-8308"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jong-Chyi Su","raw_affiliation_strings":["UMass Amherst","[UMass, Amherst]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UMass Amherst","institution_ids":["https://openalex.org/I24603500"]},{"raw_affiliation_string":"[UMass, Amherst]","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112904753","display_name":"Yi\u2013Hsuan Tsai","orcid":"https://orcid.org/0000-0003-2107-4300"},"institutions":[{"id":"https://openalex.org/I4210107353","display_name":"NEC (United States)","ror":"https://ror.org/01v791m31","country_code":"US","type":"company","lineage":["https://openalex.org/I118347220","https://openalex.org/I4210107353"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yi-Hsuan Tsai","raw_affiliation_strings":["NEC Laboratories America"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NEC Laboratories America","institution_ids":["https://openalex.org/I4210107353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072573916","display_name":"Kihyuk Sohn","orcid":"https://orcid.org/0000-0003-4303-8319"},"institutions":[{"id":"https://openalex.org/I4210107353","display_name":"NEC (United States)","ror":"https://ror.org/01v791m31","country_code":"US","type":"company","lineage":["https://openalex.org/I118347220","https://openalex.org/I4210107353"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kihyuk Sohn","raw_affiliation_strings":["NEC Laboratories America"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NEC Laboratories America","institution_ids":["https://openalex.org/I4210107353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089927825","display_name":"Buyu Liu","orcid":"https://orcid.org/0009-0004-5534-7463"},"institutions":[{"id":"https://openalex.org/I4210107353","display_name":"NEC (United States)","ror":"https://ror.org/01v791m31","country_code":"US","type":"company","lineage":["https://openalex.org/I118347220","https://openalex.org/I4210107353"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Buyu Liu","raw_affiliation_strings":["NEC Laboratories America"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NEC Laboratories America","institution_ids":["https://openalex.org/I4210107353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052551454","display_name":"Subhransu Maji","orcid":"https://orcid.org/0000-0002-3869-9334"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Subhransu Maji","raw_affiliation_strings":["UMass Amherst","[UMass, Amherst]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UMass Amherst","institution_ids":["https://openalex.org/I24603500"]},{"raw_affiliation_string":"[UMass, Amherst]","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046609009","display_name":"Manmohan Chandraker","orcid":"https://orcid.org/0000-0003-4683-2454"},"institutions":[{"id":"https://openalex.org/I4210107353","display_name":"NEC (United States)","ror":"https://ror.org/01v791m31","country_code":"US","type":"company","lineage":["https://openalex.org/I118347220","https://openalex.org/I4210107353"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Manmohan Chandraker","raw_affiliation_strings":["NEC Laboratories America"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NEC Laboratories America","institution_ids":["https://openalex.org/I4210107353"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"728","last_page":"737"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9855999946594238,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9842000007629395,"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/discriminative-model","display_name":"Discriminative model","score":0.8014751076698303},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7353566884994507},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6987060308456421},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6390044689178467},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.6272455453872681},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.606974720954895},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5572935938835144},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5231555700302124},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.48119622468948364},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4734601378440857},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4700079560279846},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4650942087173462},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.45431140065193176},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4222777783870697},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14221268892288208},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.08643504977226257},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.05893760919570923}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8014751076698303},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7353566884994507},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6987060308456421},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6390044689178467},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.6272455453872681},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.606974720954895},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5572935938835144},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5231555700302124},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.48119622468948364},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4734601378440857},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4700079560279846},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4650942087173462},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.45431140065193176},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4222777783870697},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14221268892288208},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.08643504977226257},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.05893760919570923},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/wacv45572.2020.9093390","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093390","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1904.07848","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1904.07848","pdf_url":"https://arxiv.org/pdf/1904.07848","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":"","raw_type":"text"},{"id":"mag:2936696202","is_oa":true,"landing_page_url":"https://www.arxiv.org/pdf/1904.07848","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.1904.07848","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1904.07848","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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1904.07848","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1904.07848","pdf_url":"https://arxiv.org/pdf/1904.07848","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":"","raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.75,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G4190268200","display_name":"CAREER:Towards Perceptual Agents That See and Reason Like Humans","funder_award_id":"1749833","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":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2936696202.pdf"},"referenced_works_count":110,"referenced_works":["https://openalex.org/W77777798","https://openalex.org/W149023494","https://openalex.org/W189742998","https://openalex.org/W603830301","https://openalex.org/W1484084878","https://openalex.org/W1513874326","https://openalex.org/W1522301498","https://openalex.org/W1565327149","https://openalex.org/W1580375566","https://openalex.org/W1599935123","https://openalex.org/W1722318740","https://openalex.org/W1773652845","https://openalex.org/W1861492603","https://openalex.org/W1932070659","https://openalex.org/W1956202674","https://openalex.org/W1977612207","https://openalex.org/W2016405781","https://openalex.org/W2026581312","https://openalex.org/W2062118960","https://openalex.org/W2096943734","https://openalex.org/W2097908878","https://openalex.org/W2099471712","https://openalex.org/W2103851188","https://openalex.org/W2104094955","https://openalex.org/W2105523772","https://openalex.org/W2109279964","https://openalex.org/W2110091014","https://openalex.org/W2112796928","https://openalex.org/W2117539524","https://openalex.org/W2119720396","https://openalex.org/W2124244761","https://openalex.org/W2140539195","https://openalex.org/W2145494108","https://openalex.org/W2149933564","https://openalex.org/W2150066425","https://openalex.org/W2161033259","https://openalex.org/W2170612786","https://openalex.org/W2194775991","https://openalex.org/W2214409633","https://openalex.org/W2262342046","https://openalex.org/W2279034837","https://openalex.org/W2335728318","https://openalex.org/W2340897893","https://openalex.org/W2460470859","https://openalex.org/W2511131004","https://openalex.org/W2562192638","https://openalex.org/W2565639579","https://openalex.org/W2593021375","https://openalex.org/W2593768305","https://openalex.org/W2613718673","https://openalex.org/W2736885633","https://openalex.org/W2739068567","https://openalex.org/W2777262900","https://openalex.org/W2783822844","https://openalex.org/W2785787385","https://openalex.org/W2795155917","https://openalex.org/W2798593490","https://openalex.org/W2798681837","https://openalex.org/W2885018852","https://openalex.org/W2885304161","https://openalex.org/W2885722640","https://openalex.org/W2888083906","https://openalex.org/W2891975605","https://openalex.org/W2899771611","https://openalex.org/W2914331073","https://openalex.org/W2948069880","https://openalex.org/W2949071206","https://openalex.org/W2962808524","https://openalex.org/W2962823940","https://openalex.org/W2963107255","https://openalex.org/W2963902936","https://openalex.org/W2964115968","https://openalex.org/W2968382122","https://openalex.org/W2981429991","https://openalex.org/W3010381534","https://openalex.org/W4206723194","https://openalex.org/W6603082663","https://openalex.org/W6607672814","https://openalex.org/W6618347045","https://openalex.org/W6620707391","https://openalex.org/W6628826841","https://openalex.org/W6631190155","https://openalex.org/W6633949838","https://openalex.org/W6637542466","https://openalex.org/W6637618735","https://openalex.org/W6639102338","https://openalex.org/W6640846115","https://openalex.org/W6644536952","https://openalex.org/W6675410418","https://openalex.org/W6676587327","https://openalex.org/W6677757056","https://openalex.org/W6681588610","https://openalex.org/W6682132143","https://openalex.org/W6684215405","https://openalex.org/W6684642658","https://openalex.org/W6695692224","https://openalex.org/W6703116779","https://openalex.org/W6725448924","https://openalex.org/W6730623217","https://openalex.org/W6734269522","https://openalex.org/W6741753795","https://openalex.org/W6745620410","https://openalex.org/W6746282794","https://openalex.org/W6747231328","https://openalex.org/W6747983729","https://openalex.org/W6750426974","https://openalex.org/W6753562897","https://openalex.org/W6753928293","https://openalex.org/W6756040250","https://openalex.org/W6766536910"],"related_works":["https://openalex.org/W2970996626","https://openalex.org/W3129504552","https://openalex.org/W3080746376","https://openalex.org/W3100804201","https://openalex.org/W3087277061","https://openalex.org/W3131936169","https://openalex.org/W3039655375","https://openalex.org/W2997704356","https://openalex.org/W2998666297","https://openalex.org/W2986915914","https://openalex.org/W2926393255","https://openalex.org/W3003384866","https://openalex.org/W3127214617","https://openalex.org/W2993655808","https://openalex.org/W2885722640","https://openalex.org/W3007227736","https://openalex.org/W3016907911","https://openalex.org/W3095686447","https://openalex.org/W2903457322","https://openalex.org/W3110059533"],"abstract_inverted_index":{"We":[0,88],"propose":[1],"an":[2],"active":[3,13,86],"learning":[4,105],"approach":[5],"for":[6,31,57,85,100],"transferring":[7],"representations":[8],"across":[9,34],"domains.":[10,35],"Our":[11],"approach,":[12],"adversarial":[14,25],"domain":[15,26,40,101,109,117,142],"adaptation":[16,102,143],"(AADA),":[17],"explores":[18],"a":[19,39,81],"duality":[20],"between":[21],"two":[22,92,134],"related":[23],"problems:":[24],"alignment":[27],"and":[28,72,103,128],"importance":[29,62],"sampling":[30,130],"adapting":[32],"models":[33],"The":[36],"former":[37],"uses":[38],"discriminative":[41],"model":[42,51],"to":[43,52,55,75],"align":[44],"domains,":[45],"while":[46,114],"the":[47,50,107,115,133,151],"latter":[48],"utilizes":[49],"weigh":[53],"samples":[54,66],"account":[56],"distribution":[58],"shifts.":[59],"Specifically,":[60],"our":[61],"weight":[63],"promotes":[64],"unlabeled":[65],"with":[67],"large":[68],"uncertainty":[69],"in":[70,97],"classification":[71],"diversity":[73],"compared":[74],"la-beled":[76],"examples,":[77],"thus":[78],"serving":[79],"as":[80,146],"sample":[82],"selection":[83],"scheme":[84],"learning.":[87],"show":[89],"that":[90,150],"these":[91],"views":[93],"can":[94],"be":[95],"unified":[96],"one":[98],"framework":[99],"transfer":[104],"when":[106,132],"source":[108],"has":[110],"many":[111],"labeled":[112],"examples":[113,162],"target":[116],"does":[118],"not.":[119],"AADA":[120],"provides":[121],"significant":[122],"improvements":[123],"over":[124,153],"fine-tuning":[125],"based":[126],"approaches":[127,155],"other":[129],"methods":[131],"domains":[135],"are":[136],"closely":[137],"related.":[138],"Results":[139],"on":[140],"challenging":[141],"tasks":[144],"such":[145],"object":[147],"detection":[148],"demonstrate":[149],"advantage":[152],"baseline":[154],"is":[156],"retained":[157],"even":[158],"after":[159],"hundreds":[160],"of":[161],"being":[163],"actively":[164],"annotated.":[165]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
