{"id":"https://openalex.org/W7137932650","doi":"https://doi.org/10.48550/arxiv.2603.14992","title":"Exposing Cross-Modal Consistency for Fake News Detection in Short-Form Videos","display_name":"Exposing Cross-Modal Consistency for Fake News Detection in Short-Form Videos","publication_year":2026,"publication_date":"2026-03-16","ids":{"openalex":"https://openalex.org/W7137932650","doi":"https://doi.org/10.48550/arxiv.2603.14992"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.14992","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.14992","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.14992","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129673505","display_name":"Chong Tian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tian, Chong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129745157","display_name":"Yu Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129665689","display_name":"Chenxu Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Chenxu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044078463","display_name":"Junyi Guan","orcid":"https://orcid.org/0000-0002-6670-4030"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guan, Junyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129659429","display_name":"Zheng Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Zheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129711276","display_name":"Yuhan Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yuhan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129725643","display_name":"Xiuying Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Xiuying","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129645699","display_name":"Qirong Ho","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ho, Qirong","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/T11147","display_name":"Misinformation and Its Impacts","score":0.7979999780654907,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.7979999780654907,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.03290000185370445,"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"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.030500000342726707,"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/consistency","display_name":"Consistency (knowledge bases)","score":0.7368000149726868},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.701200008392334},{"id":"https://openalex.org/keywords/misinformation","display_name":"Misinformation","score":0.5698000192642212},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5242000222206116},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4715999960899353},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4659999907016754},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.3723999857902527},{"id":"https://openalex.org/keywords/consistency-model","display_name":"Consistency model","score":0.3659000098705292},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.3352999985218048}],"concepts":[{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.7368000149726868},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7088000178337097},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.701200008392334},{"id":"https://openalex.org/C2776990098","wikidata":"https://www.wikidata.org/wiki/Q13579947","display_name":"Misinformation","level":2,"score":0.5698000192642212},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5609999895095825},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5242000222206116},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4715999960899353},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4659999907016754},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.3723999857902527},{"id":"https://openalex.org/C37279795","wikidata":"https://www.wikidata.org/wiki/Q2492305","display_name":"Consistency model","level":3,"score":0.3659000098705292},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.3352999985218048},{"id":"https://openalex.org/C31388003","wikidata":"https://www.wikidata.org/wiki/Q7624548","display_name":"Strong consistency","level":3,"score":0.33239999413490295},{"id":"https://openalex.org/C93361087","wikidata":"https://www.wikidata.org/wiki/Q4426698","display_name":"Data consistency","level":2,"score":0.31150001287460327},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3025999963283539},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.3000999987125397},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.29580000042915344},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.29100000858306885},{"id":"https://openalex.org/C15569618","wikidata":"https://www.wikidata.org/wiki/Q3561421","display_name":"Liveness","level":2,"score":0.290800005197525},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28940001130104065},{"id":"https://openalex.org/C2777548347","wikidata":"https://www.wikidata.org/wiki/Q5456937","display_name":"Flagging","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2888000011444092},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.2825999855995178},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.2694000005722046},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.266400009393692},{"id":"https://openalex.org/C2988167200","wikidata":"https://www.wikidata.org/wiki/Q16885149","display_name":"Online video","level":2,"score":0.2655999958515167},{"id":"https://openalex.org/C2779756789","wikidata":"https://www.wikidata.org/wiki/Q28549308","display_name":"Fake news","level":2,"score":0.2612999975681305},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2551000118255615}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.14992","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.14992","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.14992","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.14992","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":"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":{"Short-form":[0],"video":[1],"platforms":[2],"are":[3,24],"major":[4],"channels":[5],"for":[6,12,139],"news":[7],"but":[8,51],"also":[9],"fertile":[10],"ground":[11],"multimodal":[13],"misinformation":[14],"where":[15],"each":[16],"modality":[17],"appears":[18],"plausible":[19],"alone":[20],"yet":[21],"cross-modal":[22,123],"relationships":[23],"subtly":[25],"inconsistent,":[26],"like":[27],"mismatched":[28],"visuals":[29],"and":[30,38,76,91,99,111,117,134,155,168],"captions.":[31],"On":[32],"two":[33],"benchmark":[34],"datasets,":[35],"FakeSV":[36,154],"(Chinese)":[37],"FakeTT":[39],"(English),":[40],"we":[41,85],"observe":[42],"a":[43,63,94,173],"clear":[44],"asymmetry:":[45],"real":[46],"videos":[47,57],"exhibit":[48],"high":[49],"text-visual":[50],"moderate":[52],"text-audio":[53],"consistency,":[54],"while":[55],"fake":[56,74],"show":[58],"the":[59,149,161],"opposite":[60],"pattern.":[61],"Moreover,":[62],"single":[64],"global":[65,112],"consistency":[66,102,113,119],"score":[67],"forms":[68],"an":[69,136],"interpretable":[70],"axis":[71],"along":[72],"which":[73],"probability":[75],"prediction":[77],"errors":[78],"vary":[79],"smoothly.":[80],"Motivated":[81],"by":[82],"these":[83],"observations,":[84],"present":[86],"MAGIC3":[87,107,146],"(Modal-Adversarial":[88],"Gated":[89],"Interaction":[90],"Consistency-Centric":[92],"Classifier),":[93],"detector":[95],"that":[96],"explicitly":[97],"models":[98],"exposes":[100],"cross-tri-modal":[101],"signals":[103,120],"at":[104],"multiple":[105],"granularities.":[106],"combines":[108],"explicit":[109],"pairwise":[110],"modeling":[114],"with":[115],"token-":[116],"frame-level":[118],"derived":[121],"from":[122],"attention,":[124],"incorporates":[125],"multi-style":[126],"LLM":[127],"rewrites":[128],"to":[129],"obtain":[130],"style-robust":[131],"text":[132],"representations,":[133],"employs":[135],"uncertainty-aware":[137],"classifier":[138],"selective":[140],"VLM":[141],"routing.":[142],"Using":[143],"pre-extracted":[144],"features,":[145],"consistently":[147],"outperforms":[148],"strongest":[150],"non-VLM":[151],"baselines":[152],"on":[153],"FakeTT.":[156],"While":[157],"matching":[158],"VLM-level":[159],"accuracy,":[160],"two-stage":[162],"system":[163],"achieves":[164],"18-27x":[165],"higher":[166],"throughput":[167],"93%":[169],"VRAM":[170],"savings,":[171],"offering":[172],"strong":[174],"cost-performance":[175],"tradeoff.":[176]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-18T00:00:00"}
