{"id":"https://openalex.org/W7161740898","doi":"https://doi.org/10.48550/arxiv.2605.17488","title":"Omni-Customizer: End-to-End MultiModal Customization for Joint Audio-Video Generation","display_name":"Omni-Customizer: End-to-End MultiModal Customization for Joint Audio-Video Generation","publication_year":2026,"publication_date":"2026-05-17","ids":{"openalex":"https://openalex.org/W7161740898","doi":"https://doi.org/10.48550/arxiv.2605.17488"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.17488","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17488","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.2605.17488","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108058575","display_name":"Yuheng Chen","orcid":"https://orcid.org/0009-0008-2896-6831"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yuheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136459611","display_name":"Qingdong He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Qingdong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136481067","display_name":"Teng Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Teng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136459390","display_name":"Yuji Wang","orcid":"https://orcid.org/0000-0003-1385-7217"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yuji","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136468402","display_name":"Yabiao Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yabiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136468928","display_name":"Lizhuang Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Lizhuang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136469979","display_name":"Jiangning Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Jiangning","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":0.4392000138759613,"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":0.4392000138759613,"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":0.16990000009536743,"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":0.13600000739097595,"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/personalization","display_name":"Personalization","score":0.6391000151634216},{"id":"https://openalex.org/keywords/multimodal-interaction","display_name":"Multimodal interaction","score":0.583299994468689},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.4830000102519989},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.41040000319480896},{"id":"https://openalex.org/keywords/timbre","display_name":"Timbre","score":0.38420000672340393},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.34290000796318054}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7623000144958496},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.6391000151634216},{"id":"https://openalex.org/C135641252","wikidata":"https://www.wikidata.org/wiki/Q738567","display_name":"Multimodal interaction","level":2,"score":0.583299994468689},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.5582000017166138},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.4830000102519989},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.41040000319480896},{"id":"https://openalex.org/C2776539107","wikidata":"https://www.wikidata.org/wiki/Q176501","display_name":"Timbre","level":3,"score":0.38420000672340393},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.350600004196167},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.3449000120162964},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.34290000796318054},{"id":"https://openalex.org/C2780910867","wikidata":"https://www.wikidata.org/wiki/Q1952416","display_name":"Multimodality","level":2,"score":0.3393999934196472},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.31150001287460327},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C162269090","wikidata":"https://www.wikidata.org/wiki/Q1156047","display_name":"Rope","level":2,"score":0.27869999408721924},{"id":"https://openalex.org/C173414695","wikidata":"https://www.wikidata.org/wiki/Q5510276","display_name":"Fusion mechanism","level":4,"score":0.26260000467300415}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.17488","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17488","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.2605.17488","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17488","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"landscape":[1],"of":[2,15,30,61,171],"joint":[3],"audio":[4,115,151],"and":[5,33,58,114,131,160,173,199],"video":[6],"generation":[7],"has":[8],"been":[9],"fundamentally":[10],"transformed":[11],"by":[12],"the":[13,27,55,76,97,150,169],"advent":[14],"powerful":[16],"foundation":[17],"models.":[18],"Despite":[19],"these":[20],"strides,":[21],"achieving":[22],"cohesive":[23],"multimodal":[24,62,82,129],"customization":[25],"for":[26],"simultaneous":[28],"preservation":[29],"visual":[31,113,191],"identities":[32],"vocal":[34],"timbres":[35],"across":[36,190],"multiple":[37],"interacting":[38],"subjects":[39],"remains":[40],"largely":[41],"underexplored.":[42],"To":[43],"bridge":[44],"this":[45,103],"gap,":[46],"we":[47,66,105,136],"present":[48],"Omni-Customizer,":[49],"an":[50,68],"end-to-end":[51],"framework":[52],"targeted":[53],"at":[54],"precise":[56,196],"binding":[57],"seamless":[59],"fusion":[60,130],"identity":[63,83,133,175,192],"information.":[64],"Specifically,":[65],"introduce":[67],"Omni-Context":[69],"Fusion":[70],"(OCF)":[71],"module":[72],"that":[73,142,180],"effectively":[74],"enriches":[75],"base":[77],"textual":[78],"prompt":[79],"with":[80,86,119],"dense,":[81],"cues,":[84],"along":[85,118],"a":[87,138,161],"Masked":[88],"TTS":[89,120],"Cross-Attention":[90],"(MTP-CA)":[91],"mechanism":[92],"explicitly":[93],"designed":[94],"to":[95,111,122,147,153,164,167],"prevent":[96],"severe":[98],"\"speech":[99],"leakage\"":[100],"problem.":[101],"Within":[102],"architecture,":[104],"propose":[106],"Semantic-Anchored":[107],"Multimodal":[108],"RoPE":[109],"(SA-MRoPE)":[110],"anchor":[112],"reference":[116],"tokens,":[117],"embeddings,":[121],"their":[123],"corresponding":[124],"semantic":[125],"descriptions,":[126],"enabling":[127],"structured":[128],"robust":[132,174],"binding.":[134],"Furthermore,":[135],"devise":[137],"comprehensive":[139],"training":[140],"strategy":[141],"incorporates":[143],"interleaved":[144],"audio-video":[145,197],"scheduling":[146],"rapidly":[148],"adapt":[149],"branch":[152],"multilingual":[154],"scenarios":[155],"without":[156],"degrading":[157],"foundational":[158],"priors,":[159],"progressive":[162],"in-pair":[163],"cross-pair":[165],"curriculum":[166],"facilitate":[168],"learning":[170],"high-level":[172],"features.":[176],"Extensive":[177],"experiments":[178],"demonstrate":[179],"Omni-Customizer":[181],"achieves":[182],"state-of-the-art":[183],"performance":[184],"in":[185],"dual-modal":[186],"customized":[187],"generation,":[188],"excelling":[189],"similarity,":[193],"timbre":[194],"consistency,":[195],"synchronization,":[198],"overall":[200],"video-audio":[201],"fidelity.":[202]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-20T00:00:00"}
