{"id":"https://openalex.org/W7154213246","doi":"https://doi.org/10.48550/arxiv.2604.10009","title":"Towards Multi-Source Domain Generalization for Sleep Staging with Noisy Labels","display_name":"Towards Multi-Source Domain Generalization for Sleep Staging with Noisy Labels","publication_year":2026,"publication_date":"2026-04-11","ids":{"openalex":"https://openalex.org/W7154213246","doi":"https://doi.org/10.48550/arxiv.2604.10009"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.10009","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10009","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":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.10009","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133579938","display_name":"Kening Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wang, Kening","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133611371","display_name":"Di Wen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wen, Di","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133617601","display_name":"Yufan Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yufan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133589683","display_name":"Ruiping Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Ruiping","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133588534","display_name":"Junwei Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Junwei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133580103","display_name":"Jiale Wei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Jiale","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133604277","display_name":"Kailun Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Kailun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133612554","display_name":"Rainer Stiefelhagen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stiefelhagen, Rainer","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133593270","display_name":"Kunyu Peng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng, Kunyu","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5133579938"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.6262000203132629,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.6262000203132629,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10985","display_name":"Sleep and Wakefulness Research","score":0.07699999958276749,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.051500000059604645,"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/robustness","display_name":"Robustness (evolution)","score":0.6327999830245972},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6033999919891357},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.534600019454956},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.47859999537467957},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4749000072479248},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4300000071525574},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4011000096797943},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.39590001106262207}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7311000227928162},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6614999771118164},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6327999830245972},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6033999919891357},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.534600019454956},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.47859999537467957},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4749000072479248},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46650001406669617},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4300000071525574},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4011000096797943},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.39590001106262207},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3718999922275543},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.351500004529953},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.30709999799728394},{"id":"https://openalex.org/C2910364982","wikidata":"https://www.wikidata.org/wiki/Q35831","display_name":"Sleep Stages","level":4,"score":0.2913999855518341},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.29019999504089355},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.28760001063346863},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.2858000099658966},{"id":"https://openalex.org/C2775841894","wikidata":"https://www.wikidata.org/wiki/Q4683692","display_name":"Sleep (system call)","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.26840001344680786},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.2540000081062317}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.10009","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10009","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.10009","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10009","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":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Automatic":[0],"sleep":[1,85],"staging":[2,86],"is":[3],"a":[4,82],"multimodal":[5,84],"learning":[6,64],"problem":[7],"involving":[8],"heterogeneous":[9],"physiological":[10],"signals":[11],"such":[12],"as":[13],"EEG":[14],"and":[15,26,59,71,99,124,130],"EOG,":[16],"which":[17],"often":[18],"suffer":[19],"from":[20],"domain":[21,41,69],"shifts":[22,70],"across":[23],"institutions,":[24],"devices,":[25],"populations.":[27],"In":[28],"practice,":[29],"these":[30],"data":[31],"are":[32],"also":[33],"affected":[34],"by":[35],"noisy":[36,110],"annotations,":[37],"yet":[38],"label-noise-robust":[39],"multi-source":[40],"generalization":[42],"remains":[43],"underexplored.":[44],"We":[45],"present":[46],"the":[47],"first":[48],"benchmark":[49,129],"for":[50],"Noisy":[51],"Labels":[52],"in":[53],"Multi-Source":[54],"Domain-Generalized":[55],"Sleep":[56],"Staging":[57],"(NL-DGSS)":[58],"show":[60],"that":[61],"existing":[62],"noisy-label":[63],"methods":[65],"degrade":[66],"substantially":[67],"when":[68],"label":[72],"noise":[73,126],"coexist.":[74],"To":[75],"address":[76],"this":[77],"challenge,":[78],"we":[79],"propose":[80],"FF-TRUST,":[81],"domain-invariant":[83],"framework":[87],"with":[88,103],"Joint":[89],"Time-Frequency":[90],"Early":[91],"Learning":[92],"Regularization":[93],"(JTF-ELR).":[94],"By":[95],"jointly":[96],"exploiting":[97],"temporal":[98],"spectral":[100],"consistency":[101],"together":[102],"confidence-diversity":[104],"regularization,":[105],"FF-TRUST":[106],"improves":[107],"robustness":[108],"under":[109,121],"supervision.":[111],"Experiments":[112],"on":[113],"five":[114],"public":[115],"datasets":[116],"demonstrate":[117],"consistent":[118],"state-of-the-art":[119],"performance":[120],"diverse":[122],"symmetric":[123],"asymmetric":[125],"settings.":[127],"The":[128],"code":[131],"will":[132],"be":[133],"made":[134],"publicly":[135],"available":[136],"at":[137],"https://github.com/KNWang970918/FF-TRUST.git.":[138]},"counts_by_year":[],"updated_date":"2026-04-15T06:04:33.058270","created_date":"2026-04-15T00:00:00"}