{"id":"https://openalex.org/W7141310357","doi":"https://doi.org/10.48550/arxiv.2603.24793","title":"AVControl: Efficient Framework for Training Audio-Visual Controls","display_name":"AVControl: Efficient Framework for Training Audio-Visual Controls","publication_year":2026,"publication_date":"2026-03-25","ids":{"openalex":"https://openalex.org/W7141310357","doi":"https://doi.org/10.48550/arxiv.2603.24793"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.24793","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.24793","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.24793","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023427827","display_name":"Matan Ben-Yosef","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ben-Yosef, Matan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060032514","display_name":"Tavi Halperin","orcid":"https://orcid.org/0000-0001-9288-5392"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Halperin, Tavi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120522457","display_name":"Naomi ken korem","orcid":"https://orcid.org/0009-0006-8761-9675"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Korem, Naomi Ken","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066093107","display_name":"Mohammad Salama","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Salama, Mohammad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024733208","display_name":"Harel Cain","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cain, Harel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081607275","display_name":"A Joseph","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Joseph, Asaf","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130723584","display_name":"Anthony Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Anthony","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034668012","display_name":"Ur\u0161ka Jeler\u010di\u010d","orcid":"https://orcid.org/0000-0002-7131-8062"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jelercic, Urska","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5002960152","display_name":"Ofir Bibi","orcid":"https://orcid.org/0009-0004-1119-9550"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bibi, Ofir","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"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/T10860","display_name":"Speech and Audio Processing","score":0.35589998960494995,"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"}},"topics":[{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.35589998960494995,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.1606999933719635,"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/T11349","display_name":"Music Technology and Sound Studies","score":0.1273999959230423,"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/trajectory","display_name":"Trajectory","score":0.612500011920929},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5745000243186951},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.5740000009536743},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.48559999465942383},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.476500004529953},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.4383000135421753},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.4352000057697296},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.4090999960899353}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8256999850273132},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.612500011920929},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5745000243186951},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.5740000009536743},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5182999968528748},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.48559999465942383},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.476500004529953},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4571000039577484},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.4383000135421753},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.4352000057697296},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.4090999960899353},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.39730000495910645},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.33570000529289246},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.32670000195503235},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.2955999970436096},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.29280000925064087},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2863999903202057},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28029999136924744},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.2782999873161316},{"id":"https://openalex.org/C527821871","wikidata":"https://www.wikidata.org/wiki/Q228502","display_name":"Access control","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.2635999917984009},{"id":"https://openalex.org/C133162039","wikidata":"https://www.wikidata.org/wiki/Q1061077","display_name":"Code generation","level":3,"score":0.2556999921798706},{"id":"https://openalex.org/C149629883","wikidata":"https://www.wikidata.org/wiki/Q660926","display_name":"Fraction (chemistry)","level":2,"score":0.2549999952316284},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.24793","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.24793","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.24793","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.24793","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":"article"},"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":{"Controlling":[0],"video":[1,101,166],"and":[2,10,15,106,125,129,131,138,157,187,196,221],"audio":[3,16],"generation":[4,180],"requires":[5,191],"diverse":[6,145],"modalities,":[7],"from":[8],"depth":[9],"pose":[11],"to":[12,100,169,202],"camera":[13,136,159],"trajectories":[14],"transformations,":[17],"yet":[18],"existing":[19],"approaches":[20],"either":[21],"train":[22],"a":[23,28,45,52,64,68,144,178,193,199,203,208],"single":[24],"monolithic":[25,214],"model":[26],"for":[27,38,103,177],"fixed":[29],"set":[30,146],"of":[31,147,210,213],"controls":[32,152,176],"or":[33],"introduce":[34,43],"costly":[35],"architectural":[36,85],"changes":[37,86],"each":[39,58,189],"new":[40],"modality.":[41],"We":[42,92,216],"AVControl,":[44],"lightweight,":[46],"extendable":[47],"framework":[48,142],"built":[49],"on":[50,67,123,135],"LTX-2,":[51],"joint":[53,179],"audio-visual":[54,139,175],"foundation":[55],"model,":[56],"where":[57],"control":[59,137],"modality":[60,190],"is":[61,184],"trained":[62,149,222],"as":[63,76,154],"separate":[65],"LoRA":[66,89,223],"parallel":[69,109],"canvas":[70,110],"that":[71,94,107],"provides":[72],"the":[73,80,88,115,172,211],"reference":[74],"signal":[75],"additional":[77],"tokens":[78],"in":[79],"attention":[81],"layers,":[82],"requiring":[83],"no":[84],"beyond":[87],"adapters":[90],"themselves.":[91],"show":[93,132],"simply":[95],"extending":[96],"image-based":[97],"in-context":[98],"methods":[99],"fails":[102],"structural":[104],"control,":[105,165],"our":[108,170,219],"approach":[111],"resolves":[112],"this.":[113],"On":[114],"VACE":[116],"Benchmark,":[117],"we":[118],"outperform":[119],"all":[120],"evaluated":[121],"baselines":[122],"depth-":[124],"pose-guided":[126],"generation,":[127],"inpainting,":[128],"outpainting,":[130],"competitive":[133],"results":[134],"benchmarks.":[140],"Our":[141,182],"supports":[143],"independently":[148],"modalities:":[150],"spatially-aligned":[151],"such":[153],"depth,":[155],"pose,":[156],"edges,":[158],"trajectory":[160],"with":[161],"intrinsics,":[162],"sparse":[163],"motion":[164],"editing,":[167],"and,":[168],"knowledge,":[171],"first":[173],"modular":[174],"model.":[181],"method":[183],"both":[185],"compute-":[186],"data-efficient:":[188],"only":[192],"small":[194],"dataset":[195],"converges":[197],"within":[198],"few":[200,204],"hundred":[201],"thousand":[205],"training":[206],"steps,":[207],"fraction":[209],"budget":[212],"alternatives.":[215],"publicly":[217],"release":[218],"code":[220],"checkpoints.":[224]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-28T00:00:00"}
