{"id":"https://openalex.org/W7160906642","doi":"https://doi.org/10.48550/arxiv.2605.10817","title":"CLEF: EEG Foundation Model for Learning Clinical Semantics","display_name":"CLEF: EEG Foundation Model for Learning Clinical Semantics","publication_year":2026,"publication_date":"2026-05-11","ids":{"openalex":"https://openalex.org/W7160906642","doi":"https://doi.org/10.48550/arxiv.2605.10817"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.10817","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.10817","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.10817","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135945023","display_name":"Peng Cao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cao, Peng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135916721","display_name":"Ali Mirzazadeh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mirzazadeh, Ali","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135987003","display_name":"Jong Woo Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Jong Woo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041712925","display_name":"A Videnovi\u0107","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Videnovic, Aleksandar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135985382","display_name":"Dina Katabi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Katabi, Dina","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"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":0.8111000061035156,"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":0.8111000061035156,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.05480000004172325,"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/T10094","display_name":"Epilepsy research and treatment","score":0.021800000220537186,"subfield":{"id":"https://openalex.org/subfields/2738","display_name":"Psychiatry and Mental health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.742900013923645},{"id":"https://openalex.org/keywords/clef","display_name":"Clef","score":0.48089998960494995},{"id":"https://openalex.org/keywords/session","display_name":"Session (web analytics)","score":0.41200000047683716},{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.38019999861717224},{"id":"https://openalex.org/keywords/foundation","display_name":"Foundation (evidence)","score":0.3790999948978424},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.33640000224113464}],"concepts":[{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.742900013923645},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6453999876976013},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5490000247955322},{"id":"https://openalex.org/C107763842","wikidata":"https://www.wikidata.org/wiki/Q181040","display_name":"Clef","level":3,"score":0.48089998960494995},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4607999920845032},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4429999887943268},{"id":"https://openalex.org/C2779182362","wikidata":"https://www.wikidata.org/wiki/Q17126187","display_name":"Session (web analytics)","level":2,"score":0.41200000047683716},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.38019999861717224},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.3790999948978424},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.33640000224113464},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3287999927997589},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3271999955177307},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.31470000743865967},{"id":"https://openalex.org/C2777067715","wikidata":"https://www.wikidata.org/wiki/Q3327726","display_name":"Multitaper","level":2,"score":0.2978000044822693},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.28220000863075256},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.27649998664855957},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.10817","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.10817","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":"doi:10.48550/arxiv.2605.10817","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.10817","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":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Clinical":[0],"EEG":[1,7,17,39,44,85,91,100,119],"interpretation":[2],"requires":[3],"reasoning":[4],"over":[5,94],"full":[6],"sessions":[8,45,92],"and":[9,26,58,64,84,124,132],"integrating":[10],"signal":[11],"patterns":[12],"with":[13,61,87],"clinical":[14,30,158],"context.":[15,31],"Existing":[16],"foundation":[18,40,101,120],"models":[19,102],"are":[20],"largely":[21],"designed":[22],"for":[23,157],"short-window":[24],"decoding":[25],"do":[27],"not":[28],"incorporate":[29],"We":[32,71],"introduce":[33],"CLEF,":[34],"a":[35,75,153],"clinically":[36,148],"grounded":[37,149],"long-context":[38],"model.":[41],"CLEF":[42,73,97],"represents":[43],"as":[46,152],"3D":[47],"multitaper":[48],"spectrogram":[49],"tokens,":[50],"enabling":[51],"tractable":[52],"Transformer":[53],"modeling":[54],"at":[55],"session":[56],"scale,":[57],"aligns":[59],"embeddings":[60],"neurologist":[62],"reports":[63],"structured":[65],"EHR":[66,125],"data":[67],"through":[68],"contrastive":[69],"objectives.":[70],"evaluate":[72],"on":[74,103],"new":[76],"234-task":[77],"benchmark":[78],"spanning":[79],"disease":[80],"phenotypes,":[81],"medication":[82],"exposures,":[83],"findings,":[86],"more":[88],"than":[89],"260k":[90],"from":[93,111],"108k":[95],"patients.":[96],"outperforms":[98],"prior":[99,118],"229":[104],"of":[105],"234":[106],"tasks,":[107],"improving":[108],"mean":[109],"AUROC":[110],"0.65":[112],"to":[113],"0.74.":[114],"Reconstruction-only":[115],"pretraining":[116],"surpasses":[117],"models,":[121],"while":[122],"report":[123],"alignment":[126,142],"yields":[127],"further":[128],"gains.":[129],"Held-out":[130],"concept":[131],"external-cohort":[133],"experiments":[134],"suggest":[135],"that":[136],"these":[137],"representations":[138],"transfer":[139],"beyond":[140],"observed":[141],"targets.":[143],"These":[144],"results":[145],"support":[146],"session-scale,":[147],"representation":[150],"learning":[151],"promising":[154],"foundation-model":[155],"paradigm":[156],"EEG.":[159]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-13T00:00:00"}