{"id":"https://openalex.org/W7166875993","doi":"https://doi.org/10.48550/arxiv.2606.31326","title":"Bridging Video Understanding and Generation in a Unified Framework","display_name":"Bridging Video Understanding and Generation in a Unified Framework","publication_year":2026,"publication_date":"2026-06-30","ids":{"openalex":"https://openalex.org/W7166875993","doi":"https://doi.org/10.48550/arxiv.2606.31326"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.31326","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.31326","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2606.31326","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139739379","display_name":"Yuqi Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yuqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080246438","display_name":"Runyi Li","orcid":"https://orcid.org/0000-0002-5757-406X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Runyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139773266","display_name":"Ruoyu Feng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feng, Ruoyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139828095","display_name":"Renjie Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Renjie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101002828","display_name":"Wenfeng Lin","orcid":"https://orcid.org/0009-0006-7602-9442"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Wenfeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139781035","display_name":"Mingyu Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Mingyu","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":0.5652999877929688,"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":0.5652999877929688,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.37400001287460327,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.018799999728798866,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.5938000082969666},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.5450000166893005},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5435000061988831},{"id":"https://openalex.org/keywords/closed-captioning","display_name":"Closed captioning","score":0.49380001425743103},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.45100000500679016},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.4438000023365021},{"id":"https://openalex.org/keywords/unified-model","display_name":"Unified Model","score":0.38580000400543213}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8306000232696533},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.5938000082969666},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.5450000166893005},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5435000061988831},{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.49380001425743103},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4779999852180481},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.45100000500679016},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.4438000023365021},{"id":"https://openalex.org/C45493050","wikidata":"https://www.wikidata.org/wiki/Q7884934","display_name":"Unified Model","level":2,"score":0.38580000400543213},{"id":"https://openalex.org/C2780760462","wikidata":"https://www.wikidata.org/wiki/Q7927952","display_name":"Video modeling","level":4,"score":0.3508000075817108},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.34630000591278076},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.31679999828338623},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.30959999561309814},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.29190000891685486},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2881999909877777},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.2606000006198883},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.26030001044273376},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.31326","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.31326","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2606.31326","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.31326","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":[{"score":0.7548760771751404,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recently,":[0],"unified":[1,13,64,78],"image":[2],"generation":[3,37,148],"and":[4,45,54,84,95,98,153],"understanding":[5,29,83,155],"have":[6],"been":[7],"extensively":[8],"explored.":[9],"However,":[10],"extending":[11],"such":[12,150],"modeling":[14,66],"paradigms":[15],"to":[16,68,91],"the":[17,111,129],"video":[18,28,36,82,136,147,154],"domain":[19],"remains":[20],"largely":[21],"underexplored.":[22],"A":[23],"central":[24],"challenge":[25],"is":[26],"that":[27,41,80,127,141],"favors":[30],"compact,":[31],"discriminative":[32],"semantic":[33],"representations,":[34],"whereas":[35],"requires":[38],"dense":[39],"signals":[40],"preserve":[42],"visual":[43,96,119],"details":[44],"temporal":[46,55],"coherence.":[47],"Videos":[48],"naturally":[49],"capture":[50],"both":[51],"spatial":[52],"semantics":[53],"dynamics,":[56],"making":[57],"them":[58],"a":[59,77,88,100,124],"more":[60],"suitable":[61],"modality":[62],"for":[63,121],"multimodal":[65],"compared":[67],"static":[69],"images.":[70],"In":[71],"this":[72],"paper,":[73],"we":[74],"propose":[75],"Vega,":[76],"framework":[79],"bridges":[81],"generation.":[85],"Vega":[86,142],"leverages":[87],"shared":[89],"vocabulary":[90],"jointly":[92],"model":[93,113],"text":[94],"representations":[97],"employs":[99],"hybrid":[101],"architecture":[102],"combining":[103],"autoregressive":[104],"(AR)":[105],"prediction":[106],"with":[107],"diffusion-based":[108],"rendering.":[109],"Specifically,":[110],"AR":[112],"focuses":[114],"on":[115,146],"predicting":[116],"semantically":[117],"meaningful":[118],"tokens":[120],"keyframes,":[122],"providing":[123],"structured":[125],"representation":[126],"guides":[128],"diffusion":[130],"module":[131],"in":[132],"rendering":[133],"dense,":[134],"high-resolution":[135],"frames.":[137],"Extensive":[138],"experiments":[139],"demonstrate":[140],"achieves":[143],"strong":[144],"performance":[145],"benchmarks":[149,156],"as":[151],"VBench":[152],"like":[157],"VideoMME.":[158]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-02T00:00:00"}