{"id":"https://openalex.org/W4206911578","doi":"https://doi.org/10.1109/tnnls.2022.3140235","title":"Residual Tuning: Toward Novel Category Discovery Without Labels","display_name":"Residual Tuning: Toward Novel Category Discovery Without Labels","publication_year":2022,"publication_date":"2022-01-24","ids":{"openalex":"https://openalex.org/W4206911578","doi":"https://doi.org/10.1109/tnnls.2022.3140235","pmid":"https://pubmed.ncbi.nlm.nih.gov/35073270"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3140235","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3140235","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://lirias.kuleuven.be/retrieve/da91a5fe-6b4a-4e26-b149-a2e8ba8977ca","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004895426","display_name":"Yu Liu","orcid":"https://orcid.org/0000-0002-2067-9175"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Liu","raw_affiliation_strings":["International School of Information Science and Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0002-2067-9175","affiliations":[{"raw_affiliation_string":"International School of Information Science and Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074816094","display_name":"Tinne Tuytelaars","orcid":"https://orcid.org/0000-0003-3307-9723"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Tinne Tuytelaars","raw_affiliation_strings":["ESAT-PSI, KU Leuven, Leuven, Belgium"],"raw_orcid":"https://orcid.org/0000-0003-3307-9723","affiliations":[{"raw_affiliation_string":"ESAT-PSI, KU Leuven, Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.1491,"has_fulltext":true,"cited_by_count":24,"citation_normalized_percentile":{"value":0.92533694,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"34","issue":"10","first_page":"7271","last_page":"7285"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","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/T12535","display_name":"Machine Learning and Data Classification","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/T12072","display_name":"Machine Learning and Algorithms","score":0.9976000189781189,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9961000084877014,"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/residual","display_name":"Residual","score":0.8153865933418274},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4300042986869812},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3799769878387451},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32695773243904114},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.32510966062545776},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.17688864469528198}],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.8153865933418274},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4300042986869812},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3799769878387451},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32695773243904114},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.32510966062545776},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.17688864469528198}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tnnls.2022.3140235","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3140235","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:35073270","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35073270","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 neural networks and learning systems","raw_type":null},{"id":"pmh:oai:lirias2repo.kuleuven.be:20.500.12942/689521","is_oa":true,"landing_page_url":"https://lirias.kuleuven.be/handle/20.500.12942/689521","pdf_url":"https://lirias.kuleuven.be/retrieve/da91a5fe-6b4a-4e26-b149-a2e8ba8977ca","source":{"id":"https://openalex.org/S7407055369","display_name":"Lirias","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":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems, vol. 34 (10), (1-15)","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:lirias2repo.kuleuven.be:20.500.12942/689521","is_oa":true,"landing_page_url":"https://lirias.kuleuven.be/handle/20.500.12942/689521","pdf_url":"https://lirias.kuleuven.be/retrieve/da91a5fe-6b4a-4e26-b149-a2e8ba8977ca","source":{"id":"https://openalex.org/S7407055369","display_name":"Lirias","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":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems, vol. 34 (10), (1-15)","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2634789579","display_name":null,"funder_award_id":"62102061","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6070953436","display_name":null,"funder_award_id":"DUT21RC(3)024","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G969578015","display_name":"Structure from Semantics","funder_award_id":"G086617N","funder_id":"https://openalex.org/F4320321730","funder_display_name":"Fonds Wetenschappelijk Onderzoek"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321730","display_name":"Fonds Wetenschappelijk Onderzoek","ror":"https://ror.org/03qtxy027"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4206911578.pdf","grobid_xml":"https://content.openalex.org/works/W4206911578.grobid-xml"},"referenced_works_count":67,"referenced_works":["https://openalex.org/W1682403713","https://openalex.org/W1903029394","https://openalex.org/W1934184906","https://openalex.org/W2051549110","https://openalex.org/W2141350700","https://openalex.org/W2194775991","https://openalex.org/W2554616628","https://openalex.org/W2560647685","https://openalex.org/W2773004715","https://openalex.org/W2782276075","https://openalex.org/W2788388592","https://openalex.org/W2799012717","https://openalex.org/W2883725317","https://openalex.org/W2884282566","https://openalex.org/W2948734064","https://openalex.org/W2954929116","https://openalex.org/W2962852342","https://openalex.org/W2962966271","https://openalex.org/W2963072899","https://openalex.org/W2963588172","https://openalex.org/W2963936013","https://openalex.org/W2964189064","https://openalex.org/W2966730026","https://openalex.org/W2974317861","https://openalex.org/W2981864462","https://openalex.org/W2984353870","https://openalex.org/W2985891137","https://openalex.org/W2987741655","https://openalex.org/W2990604239","https://openalex.org/W2998655644","https://openalex.org/W3009864380","https://openalex.org/W3011986058","https://openalex.org/W3013057819","https://openalex.org/W3021931813","https://openalex.org/W3034435444","https://openalex.org/W3035524453","https://openalex.org/W3037948385","https://openalex.org/W3046554305","https://openalex.org/W3091787675","https://openalex.org/W3106217498","https://openalex.org/W3115894062","https://openalex.org/W3117854388","https://openalex.org/W3118608800","https://openalex.org/W3152635971","https://openalex.org/W3159890710","https://openalex.org/W3173329034","https://openalex.org/W3185674647","https://openalex.org/W3204232150","https://openalex.org/W4214687390","https://openalex.org/W4246193833","https://openalex.org/W4250621041","https://openalex.org/W6637373629","https://openalex.org/W6683161558","https://openalex.org/W6684191040","https://openalex.org/W6685380521","https://openalex.org/W6728550200","https://openalex.org/W6736334413","https://openalex.org/W6738602802","https://openalex.org/W6741217325","https://openalex.org/W6745901624","https://openalex.org/W6749396741","https://openalex.org/W6758241014","https://openalex.org/W6767370287","https://openalex.org/W6770196601","https://openalex.org/W6771518190","https://openalex.org/W6774314701","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4391375266","https://openalex.org/W1979597421","https://openalex.org/W2007980826","https://openalex.org/W2061531152","https://openalex.org/W3002753104","https://openalex.org/W2077600819","https://openalex.org/W2142036596","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Discovering":[0],"novel":[1],"visual":[2,127],"categories":[3],"from":[4,103,138],"a":[5,11,44,48,63,73,94,99,111],"set":[6,49],"of":[7,50,144,218],"unlabeled":[8,60,86,130,207],"images":[9,52,61,131,148],"is":[10,153,227],"crucial":[12],"and":[13,53,82,107,132,160,173,180,203,216],"essential":[14],"capability":[15],"for":[16,32,129],"intelligent":[17],"vision":[18],"systems":[19],"since":[20],"it":[21,109],"enables":[22],"them":[23],"to":[24,58,115,186],"automatically":[25],"learn":[26],"new":[27,100],"concepts":[28],"with":[29,47,110,141],"no":[30,142],"need":[31,143],"human-annotated":[33],"supervision":[34],"anymore.":[35],"To":[36,88],"tackle":[37],"this":[38,90],"problem,":[39],"existing":[40],"approaches":[41],"first":[42],"pretrain":[43],"neural":[45],"network":[46,57,106],"labeled":[51,80,139,147,201],"then":[54],"fine-tune":[55],"the":[56,104,117,146,183,187,210,214],"cluster":[59],"into":[62],"few":[64,158],"categorical":[65],"groups.":[66],"However,":[67],"their":[68],"unified":[69],"feature":[70,77,83,102,114],"representation":[71,123],"hits":[72],"tradeoff":[74],"bottleneck":[75],"between":[76],"preservation":[78],"on":[79,85,167],"data":[81],"adaptation":[84],"data.":[87],"circumvent":[89],"bottleneck,":[91],"we":[92,193],"propose":[93],"residual-tuning":[95,152,220],"approach,":[96],"which":[97],"estimates":[98],"residual":[101],"pretrained":[105],"adds":[108],"previous":[112,223],"basic":[113],"compute":[116],"clustering":[118],"objective":[119],"together.":[120],"Our":[121,165,225],"disentangled":[122],"approach":[124,221],"facilitates":[125],"adjusting":[126],"representations":[128],"overcoming":[133],"forgetting":[134],"old":[135],"knowledge":[136],"acquired":[137],"images,":[140],"replaying":[145],"again.":[149],"In":[150],"addition,":[151],"an":[154],"efficient":[155],"solution,":[156],"adding":[157],"parameters":[159],"consuming":[161],"modest":[162],"training":[163],"time.":[164],"results":[166,211],"three":[168],"common":[169],"benchmarks":[170],"show":[171],"consistent":[172],"considerable":[174],"gains":[175],"over":[176],"other":[177],"state-of-the-art":[178],"methods,":[179],"further":[181,212],"reduce":[182],"performance":[184],"gap":[185],"fully":[188],"supervised":[189],"learning":[190],"setup.":[191],"Moreover,":[192],"explore":[194],"two":[195],"extended":[196],"scenarios,":[197],"including":[198],"using":[199],"fewer":[200],"classes":[202],"continually":[204],"discovering":[205],"more":[206],"sets,":[208],"where":[209],"signify":[213],"advantages":[215],"effectiveness":[217],"our":[219],"against":[222],"approaches.":[224],"code":[226],"available":[228],"at":[229],"https://github.com/liuyudut/ResTune.":[230]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
