{"id":"https://openalex.org/W3170615377","doi":"https://doi.org/10.1109/tip.2022.3173163","title":"Cluster-Guided Asymmetric Contrastive Learning for Unsupervised Person Re-Identification","display_name":"Cluster-Guided Asymmetric Contrastive Learning for Unsupervised Person Re-Identification","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W3170615377","doi":"https://doi.org/10.1109/tip.2022.3173163","mag":"3170615377","pmid":"https://pubmed.ncbi.nlm.nih.gov/35576408"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2022.3173163","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2022.3173163","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2106.07846","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101753482","display_name":"Mingkun Li","orcid":"https://orcid.org/0000-0003-3332-7168"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingkun Li","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876 P.R. China"],"raw_orcid":"https://orcid.org/0000-0003-3332-7168","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876 P.R. China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100654344","display_name":"Chun-Guang Li","orcid":"https://orcid.org/0000-0002-5716-268X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chun-Guang Li","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876 P.R. China"],"raw_orcid":"https://orcid.org/0000-0002-5716-268X","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876 P.R. China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100445470","display_name":"Jun Guo","orcid":"https://orcid.org/0000-0001-9045-1339"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Guo","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876 P.R. China"],"raw_orcid":"https://orcid.org/0000-0001-9045-1339","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876 P.R. China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.4579,"has_fulltext":false,"cited_by_count":114,"citation_normalized_percentile":{"value":0.98959302,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"31","issue":null,"first_page":"3606","last_page":"3617"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":1.0,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9937000274658203,"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7897672653198242},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.7502412796020508},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7306554317474365},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7190300226211548},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5730006694793701},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5692711472511292},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4930550754070282},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.4825441241264343},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42279714345932007},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.4217490553855896},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4183436632156372},{"id":"https://openalex.org/keywords/complete-linkage-clustering","display_name":"Complete-linkage clustering","score":0.41598042845726013},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.41254401206970215},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.20902186632156372},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.09638062119483948}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7897672653198242},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.7502412796020508},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7306554317474365},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7190300226211548},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5730006694793701},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5692711472511292},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4930550754070282},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.4825441241264343},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42279714345932007},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.4217490553855896},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4183436632156372},{"id":"https://openalex.org/C23822008","wikidata":"https://www.wikidata.org/wiki/Q5156437","display_name":"Complete-linkage clustering","level":5,"score":0.41598042845726013},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.41254401206970215},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.20902186632156372},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.09638062119483948},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000069558","descriptor_name":"Unsupervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069558","descriptor_name":"Unsupervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069558","descriptor_name":"Unsupervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069636","descriptor_name":"Pedestrians","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069636","descriptor_name":"Pedestrians","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069636","descriptor_name":"Pedestrians","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1109/tip.2022.3173163","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2022.3173163","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:35576408","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35576408","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null},{"id":"pmh:oai:arXiv.org:2106.07846","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2106.07846","pdf_url":"https://arxiv.org/pdf/2106.07846","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:2106.07846","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2106.07846","pdf_url":"https://arxiv.org/pdf/2106.07846","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":[{"score":0.7099999785423279,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G392600865","display_name":null,"funder_award_id":"61876022","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8719100474","display_name":null,"funder_award_id":"62076031","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":67,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1673310716","https://openalex.org/W1882958252","https://openalex.org/W1949591461","https://openalex.org/W2144796873","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2204750386","https://openalex.org/W2441160157","https://openalex.org/W2511791013","https://openalex.org/W2531440880","https://openalex.org/W2798991696","https://openalex.org/W2799107345","https://openalex.org/W2884366600","https://openalex.org/W2896016251","https://openalex.org/W2904427185","https://openalex.org/W2957037461","https://openalex.org/W2962859295","https://openalex.org/W2962923976","https://openalex.org/W2963000559","https://openalex.org/W2963047834","https://openalex.org/W2963275094","https://openalex.org/W2963495051","https://openalex.org/W2963557071","https://openalex.org/W2963721283","https://openalex.org/W2963826681","https://openalex.org/W2963975998","https://openalex.org/W2964044605","https://openalex.org/W2988852559","https://openalex.org/W2995852213","https://openalex.org/W3034607353","https://openalex.org/W3034903425","https://openalex.org/W3034978746","https://openalex.org/W3035060554","https://openalex.org/W3035070480","https://openalex.org/W3035402405","https://openalex.org/W3035524453","https://openalex.org/W3036224891","https://openalex.org/W3045296664","https://openalex.org/W3080420240","https://openalex.org/W3080606204","https://openalex.org/W3087124270","https://openalex.org/W3095987504","https://openalex.org/W3103165805","https://openalex.org/W3106772544","https://openalex.org/W3106858249","https://openalex.org/W3107668149","https://openalex.org/W3109976102","https://openalex.org/W3171007011","https://openalex.org/W3176033671","https://openalex.org/W3177342236","https://openalex.org/W3216850458","https://openalex.org/W4246193833","https://openalex.org/W4297775537","https://openalex.org/W6631190155","https://openalex.org/W6639480849","https://openalex.org/W6684191040","https://openalex.org/W6728374919","https://openalex.org/W6736894310","https://openalex.org/W6737664043","https://openalex.org/W6771395016","https://openalex.org/W6774314701","https://openalex.org/W6779326418","https://openalex.org/W6779510507","https://openalex.org/W6779997284","https://openalex.org/W6781804219","https://openalex.org/W6786614245"],"related_works":["https://openalex.org/W3174759195","https://openalex.org/W3167013339","https://openalex.org/W4287121366","https://openalex.org/W60493759","https://openalex.org/W3213069564","https://openalex.org/W4386437125","https://openalex.org/W4308619659","https://openalex.org/W4389072551","https://openalex.org/W4378421684","https://openalex.org/W4294203825"],"abstract_inverted_index":{"Unsupervised":[0],"person":[1,21,74,88],"re-identification":[2],"(Re-ID)":[3],"aims":[4],"to":[5,59,67,96,119,129],"match":[6],"pedestrian":[7],"images":[8],"from":[9,30],"different":[10,136],"camera":[11],"views":[12],"in":[13,52,90,101],"an":[14],"unsupervised":[15,20,73,87],"setting.":[16],"Existing":[17],"methods":[18],"for":[19,72,86],"Re-ID":[22],"are":[23,47,117],"usually":[24],"built":[25],"upon":[26],"the":[27,33,40,43,61,98,121,130,153,168],"pseudo":[28],"labels":[29],"clustering.":[31],"However,":[32],"result":[34,93,132],"of":[35,42,65,171],"clustering":[36,92,131],"depends":[37],"heavily":[38],"on":[39,163],"quality":[41],"learned":[44],"features,":[45],"which":[46,91],"overwhelmingly":[48],"dominated":[49],"by":[50],"colors":[51,66],"images.":[53],"In":[54,109,141],"this":[55],"paper,":[56],"we":[57,77,143],"attempt":[58],"suppress":[60],"negative":[62],"dominating":[63],"influence":[64],"learn":[68,124],"more":[69],"effective":[70],"features":[71,126],"Re-ID.":[75],"Specifically,":[76],"propose":[78],"a":[79,102,146],"Cluster-guided":[80],"Asymmetric":[81],"Contrastive":[82],"Learning":[83],"(CACL)":[84],"approach":[85],"Re-ID,":[89],"is":[94],"leveraged":[95],"guide":[97],"feature":[99],"learning":[100,107,116],"properly":[103],"designed":[104],"asymmetric":[105],"contrastive":[106,115],"framework.":[108],"CACL,":[110],"both":[111],"instance-level":[112],"and":[113,134,150],"cluster-level":[114],"employed":[118],"help":[120],"siamese":[122],"network":[123],"discriminant":[125],"with":[127],"respect":[128],"within":[133],"between":[135],"data":[137],"augmentation":[138],"views,":[139],"respectively.":[140],"addition,":[142],"also":[144],"present":[145],"cluster":[147,154],"refinement":[148,155],"method,":[149],"validate":[151],"that":[152],"step":[156],"helps":[157],"CACL":[158],"significantly.":[159],"Extensive":[160],"experiments":[161],"conducted":[162],"three":[164],"benchmark":[165],"datasets":[166],"demonstrate":[167],"superior":[169],"performance":[170],"our":[172],"proposal.":[173]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":35},{"year":2024,"cited_by_count":43},{"year":2023,"cited_by_count":23},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}