{"id":"https://openalex.org/W7147432632","doi":"https://doi.org/10.1109/icaiic68212.2026.11454154","title":"TexTKAN: Parameter-Efficient Text-Based Depression Detection Using Temporal Kolmogorov-Arnold Networks","display_name":"TexTKAN: Parameter-Efficient Text-Based Depression Detection Using Temporal Kolmogorov-Arnold Networks","publication_year":2026,"publication_date":"2026-02-24","ids":{"openalex":"https://openalex.org/W7147432632","doi":"https://doi.org/10.1109/icaiic68212.2026.11454154"},"language":null,"primary_location":{"id":"doi:10.1109/icaiic68212.2026.11454154","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic68212.2026.11454154","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047371208","display_name":"Gede Aditra Pradnyana","orcid":"https://orcid.org/0000-0002-7821-8566"},"institutions":[{"id":"https://openalex.org/I4210090826","display_name":"Universitas Pendidikan Ganesha","ror":"https://ror.org/00bmjd793","country_code":"ID","type":"education","lineage":["https://openalex.org/I4210090826"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Gede Aditra Pradnyana","raw_affiliation_strings":["Universitas Pendidikan Ganesha,Department of Informatics,Bali,Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitas Pendidikan Ganesha,Department of Informatics,Bali,Indonesia","institution_ids":["https://openalex.org/I4210090826"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132581671","display_name":"Wiwik Anggraeni","orcid":null},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Sepuluh Nopember Institute of Technology","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Wiwik Anggraeni","raw_affiliation_strings":["Institut Teknologi Sepuluh Nopember,Department of Information Systems,Surabaya,Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut Teknologi Sepuluh Nopember,Department of Information Systems,Surabaya,Indonesia","institution_ids":["https://openalex.org/I166843116"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012595591","display_name":"Mauridhi Hery Purnomo","orcid":"https://orcid.org/0000-0002-6221-7382"},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Sepuluh Nopember Institute of Technology","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Mauridhi Hery Purnomo","raw_affiliation_strings":["Institut Teknologi Sepuluh Nopember,Department of Electrical Engineering,Surabaya,Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut Teknologi Sepuluh Nopember,Department of Electrical Engineering,Surabaya,Indonesia","institution_ids":["https://openalex.org/I166843116"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.29865269,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"974","last_page":"979"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12488","display_name":"Mental Health via Writing","score":0.944100022315979,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12488","display_name":"Mental Health via Writing","score":0.944100022315979,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11519","display_name":"Digital Mental Health Interventions","score":0.032099999487400055,"subfield":{"id":"https://openalex.org/subfields/3202","display_name":"Applied Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.003800000064074993,"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/depression","display_name":"Depression (economics)","score":0.5587000250816345},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49399998784065247},{"id":"https://openalex.org/keywords/mental-health","display_name":"Mental health","score":0.3458000123500824},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.3061999976634979},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2856999933719635}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6244999766349792},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6137999892234802},{"id":"https://openalex.org/C2776867660","wikidata":"https://www.wikidata.org/wiki/Q1814941","display_name":"Depression (economics)","level":2,"score":0.5587000250816345},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5478000044822693},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49399998784065247},{"id":"https://openalex.org/C134362201","wikidata":"https://www.wikidata.org/wiki/Q317309","display_name":"Mental health","level":2,"score":0.3458000123500824},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3327000141143799},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.3061999976634979},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C2982912361","wikidata":"https://www.wikidata.org/wiki/Q1851867","display_name":"Mental model","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2556999921798706}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icaiic68212.2026.11454154","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic68212.2026.11454154","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1614298861","https://openalex.org/W2064675550","https://openalex.org/W2250539671","https://openalex.org/W2493916176","https://openalex.org/W3162632106","https://openalex.org/W3206212789","https://openalex.org/W4285209895","https://openalex.org/W4295067194","https://openalex.org/W4306173662","https://openalex.org/W4312454886","https://openalex.org/W4312811953","https://openalex.org/W4353004436","https://openalex.org/W4392096521","https://openalex.org/W4394006485","https://openalex.org/W4396878152","https://openalex.org/W4408249562","https://openalex.org/W4413267802"],"related_works":[],"abstract_inverted_index":{"Depression":[0],"remains":[1],"a":[2,30,80,159],"significant":[3],"mental":[4],"health":[5],"issue":[6,57],"worldwide.":[7],"One":[8],"approach":[9],"being":[10],"explored":[11],"to":[12,19],"address":[13,73],"this":[14,34,76],"is":[15,37],"using":[16,108],"deep":[17,45],"learning":[18],"automate":[20],"depression":[21,148,167],"detection":[22,149],"from":[23],"social":[24],"media":[25],"texts.":[26],"Besides":[27],"accuracy":[28,100],"improvement,":[29],"primary":[31],"challenge":[32],"in":[33,48,62],"research":[35],"area":[36],"the":[38,56,87],"vast":[39],"number":[40],"of":[41,58,70,90,101,106],"parameters":[42],"required":[43],"for":[44,144,162],"learning,":[46],"particularly":[47],"text":[49,164],"classification":[50,165],"tasks":[51],"involving":[52],"multiple":[53],"sentences.":[54],"Moreover,":[55],"over-parameterization":[59],"arises,":[60],"resulting":[61],"prolonged":[63],"training":[64],"times":[65],"and":[66,103,119,138,146],"an":[67,99,104,132],"increased":[68],"risk":[69],"overfitting.":[71],"To":[72],"these":[74],"limitations,":[75],"study":[77],"proposes":[78],"TexTKAN,":[79],"modified":[81],"Temporal":[82],"Kolmogorov-Arnold":[83,91],"Network":[84],"inspired":[85],"by":[86],"parameter":[88],"efficiency":[89],"Networks.":[92],"Experimental":[93],"results":[94,127],"indicate":[95],"that":[96,129,155],"TexTKAN":[97,130],"achieves":[98],"0.816":[102],"F1-score":[105],"0.802":[107],"GloVe":[109],"embeddings,":[110],"outperforming":[111],"conventional":[112],"recurrent":[113],"architectures,":[114],"including":[115],"RNN,":[116],"LSTM,":[117],"GRU,":[118],"BiLSTM,":[120],"while":[121],"requiring":[122],"fewer":[123],"trainable":[124],"parameters.":[125],"These":[126],"highlight":[128],"provides":[131],"effective":[133],"trade-off":[134],"between":[135],"predictive":[136],"performance":[137],"model":[139],"efficiency,":[140],"making":[141],"it":[142],"well-suited":[143],"resource-constrained":[145],"real-world":[147],"applications.":[150],"The":[151],"findings":[152],"further":[153],"suggest":[154],"KAN-based":[156],"architectures":[157],"offer":[158],"promising":[160],"direction":[161],"efficient":[163],"beyond":[166],"detection.":[168]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-04-02T00:00:00"}