{"id":"https://openalex.org/W7166817726","doi":"https://doi.org/10.18653/v1/2026.findings-acl.1979","title":"Beyond Polarity: Continuous Affect-Enhanced Multimodal Aspect-Based Sentiment Classification","display_name":"Beyond Polarity: Continuous Affect-Enhanced Multimodal Aspect-Based Sentiment Classification","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7166817726","doi":"https://doi.org/10.18653/v1/2026.findings-acl.1979"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2026.findings-acl.1979","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.1979","pdf_url":"https://aclanthology.org/2026.findings-acl.1979.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2026.findings-acl.1979.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5132621416","display_name":"Ling-ang Meng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ling-Ang Meng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139725788","display_name":"Tianyu Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tianyu Zhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139807254","display_name":"Dawei Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dawei Song","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135072781","display_name":"Jingxu Cao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jingxu Cao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5032413813","display_name":"Youhui Zuo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Youhui Zuo","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":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.86580341,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"39717","last_page":"39727"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.5468000173568726,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive 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/T10667","display_name":"Emotion and Mood Recognition","score":0.5468000173568726,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive 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":0.3140000104904175,"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/T12488","display_name":"Mental Health via Writing","score":0.017000000923871994,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.29910001158714294},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.25999999046325684},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.23569999635219574},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.2280000001192093},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.2257000058889389}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5769000053405762},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49230000376701355},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3125},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.29910001158714294},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.23569999635219574},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.2280000001192093},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.2257000058889389},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.21789999306201935},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.21080000698566437}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2026.findings-acl.1979","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.1979","pdf_url":"https://aclanthology.org/2026.findings-acl.1979.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2026.findings-acl.1979","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.1979","pdf_url":"https://aclanthology.org/2026.findings-acl.1979.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4853011787","display_name":null,"funder_award_id":"62376027","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7166817726.pdf","grobid_xml":"https://content.openalex.org/works/W7166817726.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multimodal":[0],"aspect-based":[1],"sentiment":[2,7,59,80,101],"classification":[3],"(MABSC)":[4],"requires":[5],"aspect-level":[6,79],"inference":[8],"from":[9,76],"textual-image":[10],"data":[11],"that":[12,52,96,141],"jointly":[13],"convey":[14],"opinions.Yet":[15],"most":[16],"existing":[17],"approaches":[18],"primarily":[19],"exploit":[20],"discrete":[21],"polarity":[22],"patterns":[23],"and":[24,61,138],"generic":[25],"visual":[26,94],"embeddings,":[27],"making":[28],"them":[29],"less":[30],"effective":[31],"when":[32],"the":[33,104,147],"affect":[34,74],"is":[35],"subtle,":[36],"implicit,":[37],"or":[38],"expressed":[39],"through":[40],"imagery.In":[41],"this":[42],"work,":[43],"we":[44,66,82,107],"propose":[45],"VADE,":[46],"a":[47,68,84,119],"Valence-Arousal-Dominance":[48],"(VAD)-Enhanced":[49],"MABSC":[50],"framework":[51],"brings":[53],"continuous":[54,73],"VAD":[55,69,151],"signals":[56,152],"into":[57],"multimodal":[58,120],"reasoning":[60],"learns":[62],"emotion-sensitive":[63],"image":[64,86],"representations.Specifically,":[65],"design":[67],"encoder":[70,87],"to":[71,92,100],"extract":[72],"cues":[75],"text":[77],"for":[78,153],"reasoning.Furthermore,":[81],"fine-tune":[83],"CLIP-based":[85],"on":[88,133],"affect-enriched":[89],"image-text":[90,111,127],"pairs":[91,128],"obtain":[93],"representations":[95],"are":[97],"more":[98],"sensitive":[99],"cues.To":[102],"support":[103],"fine-tuning":[105],"process,":[106],"construct":[108],"an":[109],"affectenriched":[110],"dataset":[112],"Senti-COCO":[113],"by":[114],"rewriting":[115],"MSCOCO":[116],"captions":[117],"with":[118,129],"large":[121],"language":[122],"model,":[123],"which":[124],"yields":[125],"large-scale":[126],"richer":[130],"affective":[131],"expressions.Experiments":[132],"two":[134],"mainstream":[135],"datasets,":[136],"Twitter-15":[137],"Twitter-17,":[139],"show":[140],"VADE":[142],"achieves":[143],"state-of-the-art":[144],"results,":[145],"demonstrating":[146],"effectiveness":[148],"of":[149],"incorporating":[150],"MABSC.":[154]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-07-02T00:00:00"}
