{"id":"https://openalex.org/W7128798855","doi":"https://doi.org/10.1109/access.2026.3664693","title":"Stabilizing Multi-Task Latent Spaces: Recursive Refinement With Coordinators in Partially Labeled Learning","display_name":"Stabilizing Multi-Task Latent Spaces: Recursive Refinement With Coordinators in Partially Labeled Learning","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7128798855","doi":"https://doi.org/10.1109/access.2026.3664693"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3664693","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3664693","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3664693","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125896202","display_name":"Wooseong Jeong","orcid":null},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Wooseong Jeong","raw_affiliation_strings":["Department of Mechanical Engineering, KAIST, Daejeon, South Korea"],"raw_orcid":"https://orcid.org/0009-0006-3669-7411","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, KAIST, Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078580884","display_name":"Jegyeong Cho","orcid":"https://orcid.org/0000-0002-2330-4029"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jegyeong Cho","raw_affiliation_strings":["Department of Mechanical Engineering, KAIST, Daejeon, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-2330-4029","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, KAIST, Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125929853","display_name":"Youngho Yoon","orcid":null},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Youngho Yoon","raw_affiliation_strings":["Department of Mechanical Engineering, KAIST, Daejeon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, KAIST, Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100334542","display_name":"Jaeyoung Lee","orcid":"https://orcid.org/0000-0003-4390-7676"},"institutions":[{"id":"https://openalex.org/I4210143937","display_name":"Hanwha Solutions (South Korea)","ror":"https://ror.org/05dmq6f22","country_code":"KR","type":"company","lineage":["https://openalex.org/I4210143937","https://openalex.org/I4403386467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaeyoung Lee","raw_affiliation_strings":["Hanwha Aerospace, Seongnam-si, Gyeonggi-do, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hanwha Aerospace, Seongnam-si, Gyeonggi-do, South Korea","institution_ids":["https://openalex.org/I4210143937"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5125930758","display_name":"Kuk-Jin Yoon","orcid":null},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kuk-Jin Yoon","raw_affiliation_strings":["Department of Mechanical Engineering, KAIST, Daejeon, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-1634-2756","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, KAIST, Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19821831,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"27956","last_page":"27971"},"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":0.9345999956130981,"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":0.9345999956130981,"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/T10028","display_name":"Topic Modeling","score":0.010200000368058681,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.007899999618530273,"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/generalization","display_name":"Generalization","score":0.7759000062942505},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7078999876976013},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.5394999980926514},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4837000072002411},{"id":"https://openalex.org/keywords/sample-complexity","display_name":"Sample complexity","score":0.48240000009536743},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.4490000009536743},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4325999915599823},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.397599995136261}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7915999889373779},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7759000062942505},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7078999876976013},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.60589998960495},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5608999729156494},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.5394999980926514},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4837000072002411},{"id":"https://openalex.org/C2778445095","wikidata":"https://www.wikidata.org/wiki/Q18354077","display_name":"Sample complexity","level":2,"score":0.48240000009536743},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.4490000009536743},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4325999915599823},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.397599995136261},{"id":"https://openalex.org/C117765406","wikidata":"https://www.wikidata.org/wiki/Q5362437","display_name":"Generalization error","level":3,"score":0.3495999872684479},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.3391999900341034},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.3327000141143799},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.3203999996185303},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3084999918937683},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.30649998784065247},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C100279318","wikidata":"https://www.wikidata.org/wiki/Q467440","display_name":"Sample space","level":2,"score":0.2583000063896179},{"id":"https://openalex.org/C40506919","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Sequence learning","level":2,"score":0.2547999918460846}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3664693","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3664693","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:koasas.kaist.ac.kr:10203/339661","is_oa":false,"landing_page_url":"http://hdl.handle.net/10203/339661","pdf_url":null,"source":{"id":"https://openalex.org/S4306402435","display_name":"KAIST Institutional Repository (KAIST)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I157485424","host_organization_name":"Korea Advanced Institute of Science and Technology","host_organization_lineage":["https://openalex.org/I157485424"],"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":"Article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3664693","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3664693","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.5536633729934692,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multi-Task":[0,84],"Learning":[1],"(MTL)":[2],"is":[3,58],"a":[4,90],"widely":[5],"used":[6],"paradigm":[7],"that":[8,107],"enhances":[9,135],"generalization":[10],"by":[11,41,114],"training":[12],"multiple":[13],"tasks":[14],"simultaneously.":[15],"However,":[16],"it":[17,31],"requires":[18],"large":[19],"datasets":[20],"where":[21],"each":[22],"sample":[23],"must":[24],"have":[25],"labels":[26],"for":[27],"all":[28],"tasks,":[29],"making":[30],"costly":[32],"and":[33,68,138],"impractical.":[34],"Partially":[35],"labeled":[36,98,144],"MTL":[37],"alleviates":[38],"this":[39,56],"issue":[40],"enabling":[42],"models":[43],"to":[44,93,119],"learn":[45],"from":[46,61],"data":[47],"with":[48,87],"sparse":[49],"task":[50,66,117],"labels.":[51],"A":[52],"key":[53],"challenge":[54],"in":[55,75,96,142],"setting":[57],"the":[59,109,121,128],"instability":[60,95],"partial":[62,124],"supervision,":[63],"which":[64],"misaligns":[65],"representations":[67,118],"degrades":[69],"learning,":[70],"yet":[71],"remains":[72],"largely":[73],"overlooked":[74],"existing":[76],"works.":[77],"To":[78],"address":[79],"this,":[80],"we":[81],"propose":[82],"Recursive":[83],"Latent":[85],"Refinement":[86],"Coordinators":[88],"(RLRC),":[89],"framework":[91],"designed":[92],"mitigate":[94],"partially":[97,143],"MTL.":[99],"RLRC":[100,134],"introduces":[101],"<italic":[102],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[103],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">coordinators</i>,":[104],"learnable":[105],"projections":[106],"refine":[108],"shared":[110],"multi-task":[111],"latent":[112,129],"space":[113,130],"dynamically":[115],"adjusting":[116],"reduce":[120],"impact":[122],"of":[123],"supervision.":[125],"By":[126],"stabilizing":[127],"through":[131],"recursive":[132],"refinement,":[133],"learning":[136],"efficiency":[137],"achieves":[139],"strong":[140],"performance":[141],"settings.":[145]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-14T00:00:00"}
