{"id":"https://openalex.org/W4414747863","doi":"https://doi.org/10.18653/v1/2026.acl-long.1691","title":"Multi-View Attention Multiple-Instance Learning Enhanced by LLM Reasoning for Cognitive Distortion Detection","display_name":"Multi-View Attention Multiple-Instance Learning Enhanced by LLM Reasoning for Cognitive Distortion Detection","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W4414747863","doi":"https://doi.org/10.18653/v1/2026.acl-long.1691"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2026.acl-long.1691","doi":"https://doi.org/10.18653/v1/2026.acl-long.1691","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-long.1691","pdf_url":"https://aclanthology.org/2026.acl-long.1691.pdf","source":{"id":"https://openalex.org/S4393915740","display_name":"Proceedings of the conference - Association for Computational Linguistics. Meeting","issn_l":"0736-587X","issn":["0736-587X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://aclanthology.org/2026.acl-long.1691.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103424713","display_name":"J.S. Kim","orcid":"https://orcid.org/0009-0005-7581-9357","observed_orcids":["https://orcid.org/0009-0005-7581-9357"]},"institutions":[{"id":"https://openalex.org/I12832649","display_name":"Gachon University","ror":"https://ror.org/03ryywt80","country_code":"KR","type":"education","lineage":["https://openalex.org/I12832649"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jun Seo Kim","raw_affiliation_strings":["Gachon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Gachon University","institution_ids":["https://openalex.org/I12832649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076443181","display_name":"Hyemi Kim","orcid":"https://orcid.org/0000-0003-4713-4658","observed_orcids":["https://orcid.org/0000-0003-4713-4658"]},"institutions":[{"id":"https://openalex.org/I101155339","display_name":"Korea Telecom (South Korea)","ror":"https://ror.org/043n4tt17","country_code":"KR","type":"company","lineage":["https://openalex.org/I101155339"]},{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyemi Kim","raw_affiliation_strings":["Korea Telecom Research","Yonsei University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea Telecom Research","institution_ids":["https://openalex.org/I101155339"]},{"raw_affiliation_string":"Yonsei University","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Woo Joo OH","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I101155339","display_name":"Korea Telecom (South Korea)","ror":"https://ror.org/043n4tt17","country_code":"KR","type":"company","lineage":["https://openalex.org/I101155339"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Woo Joo OH","raw_affiliation_strings":["Korea Telecom Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea Telecom Research","institution_ids":["https://openalex.org/I101155339"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hongjin Cho","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I101155339","display_name":"Korea Telecom (South Korea)","ror":"https://ror.org/043n4tt17","country_code":"KR","type":"company","lineage":["https://openalex.org/I101155339"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hongjin Cho","raw_affiliation_strings":["Korea Telecom Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea Telecom Research","institution_ids":["https://openalex.org/I101155339"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063582567","display_name":"Hochul Lee","orcid":"https://orcid.org/0000-0002-7740-9424","observed_orcids":["https://orcid.org/0000-0002-7740-9424"]},"institutions":[{"id":"https://openalex.org/I101155339","display_name":"Korea Telecom (South Korea)","ror":"https://ror.org/043n4tt17","country_code":"KR","type":"company","lineage":["https://openalex.org/I101155339"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hochul Lee","raw_affiliation_strings":["Korea Telecom Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea Telecom Research","institution_ids":["https://openalex.org/I101155339"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085143832","display_name":"Hye Hyeon Kim","orcid":"https://orcid.org/0000-0002-1928-4168","observed_orcids":["https://orcid.org/0000-0002-1928-4168"]},"institutions":[{"id":"https://openalex.org/I101155339","display_name":"Korea Telecom (South Korea)","ror":"https://ror.org/043n4tt17","country_code":"KR","type":"company","lineage":["https://openalex.org/I101155339"]},{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hye Hyeon Kim","raw_affiliation_strings":["Korea Telecom Research","Yonsei University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea Telecom Research","institution_ids":["https://openalex.org/I101155339"]},{"raw_affiliation_string":"Yonsei University","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00552251,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"36505","last_page":"36525"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12488","display_name":"Mental Health via Writing","score":0.9945999979972839,"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":0.9945999979972839,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.00279999990016222,"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":0.00039999998989515007,"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/multiple-instance-learning","display_name":"multiple instance learning","score":0.7770000100135803},{"id":"https://openalex.org/keywords/large-language-models","display_name":"large language models","score":0.9580000042915344},{"id":"https://openalex.org/keywords/cognitive-behavioral-therapy","display_name":"cognitive behavioral therapy","score":0.47200000286102295},{"id":"https://openalex.org/keywords/interpretability","display_name":"interpretability","score":0.550000011920929}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9153000116348267},{"id":"https://openalex.org/C108154423","wikidata":"https://www.wikidata.org/wiki/Q1469792","display_name":"Salience (neuroscience)","level":2,"score":0.7484999895095825},{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.6460999846458435},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6053000092506409},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.5845000147819519},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5842000246047974},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.4717000126838684},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.4074000120162964},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.398499995470047},{"id":"https://openalex.org/C20854674","wikidata":"https://www.wikidata.org/wiki/Q4386060","display_name":"Cognitive architecture","level":3,"score":0.39800000190734863},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36079999804496765},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.35420000553131104},{"id":"https://openalex.org/C115086926","wikidata":"https://www.wikidata.org/wiki/Q17004651","display_name":"Causal reasoning","level":3,"score":0.31790000200271606},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.3151000142097473},{"id":"https://openalex.org/C134362201","wikidata":"https://www.wikidata.org/wiki/Q317309","display_name":"Mental health","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C2982912361","wikidata":"https://www.wikidata.org/wiki/Q1851867","display_name":"Mental model","level":2,"score":0.2921999990940094},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.28139999508857727},{"id":"https://openalex.org/C161407221","wikidata":"https://www.wikidata.org/wiki/Q4382939","display_name":"Cognitive model","level":3,"score":0.2799000144004822},{"id":"https://openalex.org/C2988148770","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion detection","level":3,"score":0.2628999948501587},{"id":"https://openalex.org/C2983448237","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Language understanding","level":2,"score":0.26170000433921814},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.25060001015663147}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.18653/v1/2026.acl-long.1691","doi":"https://doi.org/10.18653/v1/2026.acl-long.1691","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-long.1691","pdf_url":"https://aclanthology.org/2026.acl-long.1691.pdf","source":{"id":"https://openalex.org/S4393915740","display_name":"Proceedings of the conference - Association for Computational Linguistics. Meeting","issn_l":"0736-587X","issn":["0736-587X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2509.17292","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2509.17292","pdf_url":"https://arxiv.org/pdf/2509.17292","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2509.17292","doi":"https://doi.org/10.48550/arxiv.2509.17292","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2509.17292","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"}],"best_oa_location":{"id":"doi:10.18653/v1/2026.acl-long.1691","doi":"https://doi.org/10.18653/v1/2026.acl-long.1691","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-long.1691","pdf_url":"https://aclanthology.org/2026.acl-long.1691.pdf","source":{"id":"https://openalex.org/S4393915740","display_name":"Proceedings of the conference - Association for Computational Linguistics. Meeting","issn_l":"0736-587X","issn":["0736-587X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.46810001134872437,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4414747863.pdf","grobid_xml":"https://content.openalex.org/works/W4414747863.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4404781657","https://openalex.org/W4401042554","https://openalex.org/W7202118306","https://openalex.org/W7196931993","https://openalex.org/W4327644073","https://openalex.org/W7155092417","https://openalex.org/W4297255516","https://openalex.org/W7135222002","https://openalex.org/W7167585422","https://openalex.org/W7171959196"],"abstract_inverted_index":{"Cognitive":[0],"distortions":[1,109],"have":[2],"been":[3],"closely":[4],"linked":[5],"to":[6,17,40,61],"mental":[7,126],"health":[8,127],"disorders,":[9],"yet":[10],"their":[11],"automatic":[12],"detection":[13],"remains":[14],"challenging":[15],"due":[16],"contextual":[18],"ambiguity,":[19],"co-occurrence,":[20],"and":[21,43,52,72,91,100,119,130],"semantic":[22],"overlap.We":[23],"propose":[24],"a":[25,35,68,80,116],"novel":[26],"framework":[27],"that":[28,97],"combines":[29],"Large":[30],"Language":[31],"Models":[32],"(LLMs)":[33],"with":[34,67,110],"Multiple-Instance":[36],"Learning":[37],"(MIL)":[38],"architecture":[39],"enhance":[41],"interpretability":[42],"expression-level":[44],"reasoning.Each":[45],"utterance":[46],"is":[47],"decomposed":[48],"into":[49],"Emotion,":[50],"Logic,":[51],"Behavior":[53],"(ELB)":[54],"components,":[55],"which":[56],"are":[57,77,133],"processed":[58],"by":[59],"LLMs":[60],"infer":[62],"multiple":[63],"distortion":[64],"instances,":[65],"each":[66],"predicted":[69],"type,":[70],"expression,":[71],"model-assigned":[73],"salience":[74,102],"score.These":[75],"instances":[76],"integrated":[78],"via":[79],"Multi-View":[81],"Gated":[82],"Attention":[83],"mechanism":[84],"for":[85,108,122],"final":[86],"classification.Experiments":[87],"on":[88],"Korean":[89],"(KoACD)":[90],"English":[92],"(Therapist":[93],"QA)":[94],"datasets":[95],"demonstrate":[96],"incorporating":[98],"ELB":[99],"LLMinferred":[101],"scores":[103],"improves":[104],"classification":[105],"performance,":[106],"especially":[107],"high":[111],"interpretive":[112],"ambiguity.Our":[113],"results":[114],"suggest":[115],"psychologically":[117],"grounded":[118],"generalizable":[120],"approach":[121],"fine-grained":[123],"reasoning":[124],"in":[125],"NLP.The":[128],"dataset":[129],"implementation":[131],"details":[132],"publicly":[134],"accessible":[135],"1":[136],".":[137]},"counts_by_year":[],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2025-10-10T00:00:00"}
