{"id":"https://openalex.org/W7163070812","doi":"https://doi.org/10.48550/arxiv.2605.30994","title":"Dynamic Interaction-Aware and Causality-Disentangled Framework for Multimodal Sentiment Analysis","display_name":"Dynamic Interaction-Aware and Causality-Disentangled Framework for Multimodal Sentiment Analysis","publication_year":2026,"publication_date":"2026-05-29","ids":{"openalex":"https://openalex.org/W7163070812","doi":"https://doi.org/10.48550/arxiv.2605.30994"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.30994","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30994","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2605.30994","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136114558","display_name":"Guangyuan Dong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong, Guangyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137542593","display_name":"Ziwei Hong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hong, Ziwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137551060","display_name":"Shenghao Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Shenghao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137578028","display_name":"Chenyu Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Chenyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058241856","display_name":"Yuanyuan Fang","orcid":"https://orcid.org/0000-0002-4562-0727"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fang, Yuanyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137611645","display_name":"Zihao Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Zihao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137580644","display_name":"Xudong Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xudong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137580148","display_name":"Bingchen Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Bingchen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137516340","display_name":"Yuchen Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yuchen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137556152","display_name":"Haitao Ding","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, Haitao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122871520","display_name":"Zhenzhou Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Zhenzhou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137595288","display_name":"Ziyu Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Ziyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":12,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.7179999947547913,"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":0.7179999947547913,"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":0.13770000636577606,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.05169999971985817,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/representation","display_name":"Representation (politics)","score":0.5378000140190125},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.413100004196167},{"id":"https://openalex.org/keywords/information-flow","display_name":"Information flow","score":0.4090999960899353},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.40639999508857727},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.4027999937534332},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.38089999556541443},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.3774999976158142},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.3587000072002411}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7989000082015991},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5703999996185303},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5378000140190125},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44769999384880066},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.413100004196167},{"id":"https://openalex.org/C2779136372","wikidata":"https://www.wikidata.org/wiki/Q10283002","display_name":"Information flow","level":2,"score":0.4090999960899353},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.40639999508857727},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.4027999937534332},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.38089999556541443},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.3774999976158142},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.3587000072002411},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3504999876022339},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.32269999384880066},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.32100000977516174},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.3061000108718872},{"id":"https://openalex.org/C60008888","wikidata":"https://www.wikidata.org/wiki/Q6031013","display_name":"Information bottleneck method","level":3,"score":0.303600013256073},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C171018156","wikidata":"https://www.wikidata.org/wiki/Q7370306","display_name":"Rotation formalisms in three dimensions","level":2,"score":0.27950000762939453},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2700999975204468},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.25290000438690186},{"id":"https://openalex.org/C44492722","wikidata":"https://www.wikidata.org/wiki/Q327069","display_name":"Conditional probability","level":2,"score":0.25060001015663147}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.30994","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30994","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.30994","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30994","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.5172291994094849}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Although":[0],"Multimodal":[1,61,124],"Sentiment":[2],"Analysis":[3],"(MSA)":[4],"effectively":[5],"leverages":[6],"rich":[7],"information":[8,93,157],"from":[9,49,106],"language,":[10],"visual,":[11,136],"and":[12,35,64,77,138,149,155,194,214,226,238],"acoustic":[13],"modalities,":[14,51],"existing":[15],"methods":[16],"still":[17],"face":[18],"two":[19],"core":[20],"challenges:":[21],"1)":[22],"static":[23],"conflict":[24],"suppression":[25],"mechanisms":[26],"fail":[27],"to":[28,30,102,177],"adapt":[29],"dynamic":[31],"variations":[32],"across":[33,144],"samples,":[34],"2)":[36],"the":[37,42,72,92,128,173,192],"inherent":[38],"sentimental":[39,104],"bias":[40,105],"within":[41],"language":[43,107,112,140],"modality,":[44,150],"which":[45,96],"can":[46],"misguide":[47],"learning":[48],"other":[50],"remains":[52],"entangled.":[53],"To":[54],"this":[55],"end,":[56],"we":[57,84,120],"propose":[58],"a":[59,78,86,98,110,115,122,163,185],"Dynamic":[60,75,123],"Causal":[62,74,100],"Disentanglement":[63],"Adaptive":[65],"Fusion":[66],"Framework":[67],"(MCAF).":[68],"Its":[69],"cornerstone":[70],"is":[71],"Multi-Granularity":[73],"Router":[76,125],"Conditional":[79,165],"Diffusion":[80,166],"Denoising":[81,167],"Module.":[82],"First,":[83],"introduce":[85],"causal":[87],"intervention":[88],"module":[89],"based":[90],"on":[91,172,191,203,212,216,222],"bottleneck":[94],"principle,":[95],"builds":[97],"Structural":[99],"Model":[101],"disentangle":[103],"features,":[108],"yielding":[109],"\"de-confounded\"":[111],"representation":[113,176],"as":[114],"pure":[116],"guiding":[117],"signal.":[118],"Second,":[119],"devise":[121],"that":[126,198],"evaluates":[127],"interaction":[129],"states":[130],"(complementary,":[131],"conflicting,":[132],"or":[133],"redundant)":[134],"among":[135],"acoustic,":[137],"de-confounded":[139],"signals":[141],"in":[142,232],"real-time":[143],"three":[145],"levels:":[146],"feature,":[147],"temporal,":[148],"then":[151],"adaptively":[152],"allocates":[153],"weights":[154],"routes":[156],"flow":[158],"for":[159],"fine-grained":[160],"regulation.":[161],"Finally,":[162],"lightweight":[164],"Module":[168],"performs":[169],"iterative":[170],"denoising":[171],"fused":[174],"joint":[175],"explicitly":[178],"filter":[179],"out":[180],"residual":[181],"irrelevant":[182],"information,":[183],"generating":[184],"robust":[186],"hyper-modality":[187],"representation.":[188],"Extensive":[189],"experiments":[190],"CMU-MOSI":[193],"CMU-MOSEI":[195],"benchmarks":[196],"show":[197],"MCAF":[199],"sets":[200],"new":[201],"state-of-the-art":[202],"key":[204],"classification":[205],"metrics,":[206],"achieving":[207],"an":[208],"Acc-2/F1":[209],"of":[210],"86.52%/86.51%":[211],"MOSI":[213],"86.72%/86.65%":[215],"MOSEI,":[217],"while":[218],"remaining":[219],"highly":[220],"competitive":[221],"others.":[223],"Comprehensive":[224],"analyses":[225],"visualizations":[227],"further":[228],"validate":[229],"its":[230],"efficacy":[231],"dynamically":[233],"perceiving":[234],"interactions,":[235],"disentangling":[236],"bias,":[237],"enhancing":[239],"interpretability.":[240]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-06-02T00:00:00"}
