{"id":"https://openalex.org/W7162307213","doi":"https://doi.org/10.48550/arxiv.2605.23113","title":"Inconsistency-aware Multimodal Schr\u00f6dinger Bridge for Deepfake Localization","display_name":"Inconsistency-aware Multimodal Schr\u00f6dinger Bridge for Deepfake Localization","publication_year":2026,"publication_date":"2026-05-22","ids":{"openalex":"https://openalex.org/W7162307213","doi":"https://doi.org/10.48550/arxiv.2605.23113"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.23113","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.23113","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":null,"license_id":null,"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.2605.23113","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102123841","display_name":"Jiayu Xiong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiong, Jiayu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136990371","display_name":"Jing Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Jing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136922731","display_name":"Qi Zhang","orcid":"https://orcid.org/0000-0002-8657-3920"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Qi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136920206","display_name":"Wanlong Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Wanlong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136946126","display_name":"Jun Xue","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xue, Jun","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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.36399999260902405,"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"}},"topics":[{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.36399999260902405,"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/T10860","display_name":"Speech and Audio Processing","score":0.3116999864578247,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11309","display_name":"Music and Audio Processing","score":0.1264999955892563,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/bridge","display_name":"Bridge (graph theory)","score":0.7368000149726868},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.636900007724762},{"id":"https://openalex.org/keywords/asynchronous-communication","display_name":"Asynchronous communication","score":0.5687000155448914},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5577999949455261},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4390999972820282},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4101000130176544}],"concepts":[{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.7368000149726868},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6723999977111816},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.636900007724762},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.5687000155448914},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5577999949455261},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4390999972820282},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4101000130176544},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40799999237060547},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4009000062942505},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.39399999380111694},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.3837999999523163},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.37700000405311584},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37450000643730164},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.3637000024318695},{"id":"https://openalex.org/C43711488","wikidata":"https://www.wikidata.org/wiki/Q7534783","display_name":"Skew","level":2,"score":0.26910001039505005}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.23113","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.23113","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.23113","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.23113","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Audio-visual":[0],"deepfake":[1],"localization":[2],"demands":[3],"interval-level":[4,43],"outputs":[5,114],"that":[6,36],"serve":[7],"as":[8],"temporal":[9],"evidence.":[10],"Despite":[11],"recent":[12],"progress,":[13],"symmetric":[14],"fusion":[15,112],"under":[16],"single-sided":[17,120,156],"or":[18,60],"asynchronous":[19,122],"forgeries":[20,123],"propagates":[21],"cross-modal":[22,39,71,91,96,127],"noise,":[23],"degrading":[24],"high-precision":[25,152],"localization.":[26,44],"We":[27],"present":[28],"IaMSB,":[29],"an":[30],"inconsistency-aware":[31],"multimodal":[32],"Schr\u00f6dinger":[33,64],"Bridge":[34,65],"(SB)":[35],"jointly":[37],"estimates":[38,90],"consistency":[40,54,69],"and":[41,52,74,89,99,113,121,149],"performs":[42,110],"Unlike":[45],"diffusion":[46],"models,":[47],"SB":[48],"minimizes":[49],"path-distribution":[50],"discrepancy":[51],"yields":[53,150],"scores":[55],"without":[56],"explicit":[57],"noise":[58,133],"injection":[59],"denoising.":[61],"With":[62],"the":[63],"(SB),":[66],"IaMSB":[67,118,140],"unifies":[68],"estimation,":[70],"information":[72],"selection,":[73],"bridge-step":[75],"scheduling":[76],"in":[77],"one":[78],"framework.":[79],"Specifically,":[80],"a":[81],"lightweight":[82],"coarse":[83],"bridge":[84,101,108],"first":[85],"proposes":[86],"candidate":[87],"intervals":[88],"consistency;":[92],"these":[93],"statistics":[94],"select":[95],"witness":[97],"signals":[98],"allocate":[100],"steps":[102],"asymmetrically":[103],"across":[104],"modalities.":[105],"A":[106],"refinement":[107],"then":[109],"step-tuned":[111],"refined,":[115],"time-aligned":[116],"intervals.":[117],"anticipates":[119],"and,":[124],"using":[125],"bottlenecked":[126],"interaction":[128],"with":[129],"step":[130],"allocation,":[131],"suppresses":[132],"transfer,":[134],"avoids":[135],"unnecessary":[136],"iterations.":[137],"Across":[138],"benchmarks,":[139],"stabilizes":[141],"strict-IoU":[142],"boundary":[143],"precision,":[144],"raising":[145],"AP@0.95":[146],"by":[147],"3%~10%,":[148],"improved":[151],"localization,":[153],"particularly":[154],"for":[155],"forgeries.":[157]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-26T00:00:00"}