{"id":"https://openalex.org/W7138224785","doi":"https://doi.org/10.1609/aaai.v40i5.37318","title":"Phased One-Step Adversarial Equilibrium for Video Diffusion Models","display_name":"Phased One-Step Adversarial Equilibrium for Video Diffusion Models","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138224785","doi":"https://doi.org/10.1609/aaai.v40i5.37318"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i5.37318","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i5.37318","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v40i5.37318","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008859889","display_name":"Jiaxiang Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiaxiang Cheng","raw_affiliation_strings":["Tencent Hunyuan"],"affiliations":[{"raw_affiliation_string":"Tencent Hunyuan","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129692140","display_name":"Bing Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bing Ma","raw_affiliation_strings":["Tencent Hunyuan"],"affiliations":[{"raw_affiliation_string":"Tencent Hunyuan","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028027237","display_name":"Xuhua Ren","orcid":"https://orcid.org/0000-0002-6722-6114"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuhua Ren","raw_affiliation_strings":["Tencent Hunyuan"],"affiliations":[{"raw_affiliation_string":"Tencent Hunyuan","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101264780","display_name":"Hongyi Jin","orcid":"https://orcid.org/0000-0001-6894-6554"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyi Henry Jin","raw_affiliation_strings":["Tencent Hunyuan\nComputer Science Department, UCLA"],"affiliations":[{"raw_affiliation_string":"Tencent Hunyuan\nComputer Science Department, UCLA","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129687103","display_name":"Kai Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Yu","raw_affiliation_strings":["Tencent Hunyuan"],"affiliations":[{"raw_affiliation_string":"Tencent Hunyuan","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129671804","display_name":"Peng Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Zhang","raw_affiliation_strings":["Tencent Hunyuan"],"affiliations":[{"raw_affiliation_string":"Tencent Hunyuan","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101684085","display_name":"Wenyue Li","orcid":"https://orcid.org/0000-0003-4748-982X"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenyue Li","raw_affiliation_strings":["Tencent Hunyuan"],"affiliations":[{"raw_affiliation_string":"Tencent Hunyuan","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129713448","display_name":"Yuan Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Zhou","raw_affiliation_strings":["Tencent Hunyuan"],"affiliations":[{"raw_affiliation_string":"Tencent Hunyuan","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129733909","display_name":"Tianxiang Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianxiang Zheng","raw_affiliation_strings":["Tencent Hunyuan"],"affiliations":[{"raw_affiliation_string":"Tencent Hunyuan","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129738016","display_name":"Qinglin Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinglin Lu","raw_affiliation_strings":["Tencent Hunyuan"],"affiliations":[{"raw_affiliation_string":"Tencent Hunyuan","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":10,"corresponding_author_ids":["https://openalex.org/A5008859889"],"corresponding_institution_ids":["https://openalex.org/I2250653659"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.55597015,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"5","first_page":"3237","last_page":"3245"},"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":0.8658000230789185,"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":0.8658000230789185,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.05869999900460243,"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"}},{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.02199999988079071,"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/adversarial-system","display_name":"Adversarial system","score":0.47769999504089355},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.421999990940094},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.41690000891685486},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.3993000090122223},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.3763999938964844},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.35100001096725464},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.33970001339912415},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.32760000228881836}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.722599983215332},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.47769999504089355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4645000100135803},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.421999990940094},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.41690000891685486},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3993000090122223},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.3763999938964844},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35510000586509705},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.35100001096725464},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.33970001339912415},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.32760000228881836},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.3271999955177307},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3230000138282776},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.3224000036716461},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.3084000051021576},{"id":"https://openalex.org/C39394851","wikidata":"https://www.wikidata.org/wiki/Q921594","display_name":"Inter frame","level":4,"score":0.3066999912261963},{"id":"https://openalex.org/C128840427","wikidata":"https://www.wikidata.org/wiki/Q1302174","display_name":"Motion compensation","level":2,"score":0.28049999475479126},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.2773999869823456},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.2720000147819519},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2653000056743622},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.257999986410141},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.257099986076355}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i5.37318","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i5.37318","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i5.37318","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i5.37318","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6738187670707703}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Video":[0,47],"diffusion":[1,190],"generation":[2,60],"suffers":[3],"from":[4,21,61],"critical":[5],"sampling":[6],"efficiency":[7],"bottlenecks,":[8],"particularly":[9],"for":[10,29,36,112],"large-scale":[11,30,62,194],"models":[12,32],"and":[13,33,84,143,181],"long":[14],"contexts.":[15],"Existing":[16],"video":[17,31,59,63,195],"acceleration":[18,164],"methods,":[19],"adapted":[20],"image-based":[22],"techniques,":[23],"lack":[24],"a":[25,52,68,75,104,118],"single-step":[26,58,92],"distillation":[27,53,94,149],"ability":[28],"task":[34],"generalization":[35],"conditional":[37,129,144],"downstream":[38],"tasks.":[39],"To":[40],"bridge":[41],"this":[42],"gap,":[43],"we":[44,131],"propose":[45],"the":[46,80,89,96,113,123,128,148,172,189,193],"Phased":[48],"Adversarial":[49],"Equilibrium":[50],"(V-PAE),":[51],"framework":[54],"that":[55,108,160],"enables":[56],"high-quality,":[57],"models.":[64],"Our":[65],"approach":[66,187],"employs":[67],"two-phase":[69],"process.":[70,98],"(i)":[71],"Stability":[72],"priming":[73],"is":[74,103,138],"warm-up":[76],"process":[77,107],"to":[78],"align":[79],"distributions":[81],"of":[82,91,169,192],"real":[83],"generated":[85],"videos.":[86],"It":[87,116],"improves":[88],"stability":[90],"adversarial":[93,101,120],"in":[95,122,151,171],"following":[97],"(ii)":[99],"Unified":[100],"equilibrium":[102,121],"flexible":[105],"self-adversarial":[106],"reuses":[109],"generator":[110],"parameters":[111],"discriminator":[114],"backbone.":[115],"achieves":[117],"co-evolutionary":[119],"Gaussian":[124],"noise":[125],"space.":[126],"For":[127],"tasks,":[130],"primarily":[132],"preserve":[133],"video-image":[134],"subject":[135],"consistency,":[136],"which":[137],"caused":[139],"by":[140,166,199],"semantic":[141,177],"degradation":[142],"frame":[145,182],"collapse":[146],"during":[147],"training":[150],"image-to-video":[152],"(I2V)":[153],"generation.":[154],"Comprehensive":[155],"experiments":[156],"on":[157],"VBench-I2V":[158],"demonstrate":[159],"V-PAE":[161],"outperforms":[162],"existing":[163],"methods":[165],"an":[167],"average":[168],"5.8%":[170],"overall":[173],"quality":[174],"score,":[175],"including":[176],"alignment,":[178],"temporal":[179],"coherence,":[180],"quality.":[183],"In":[184],"addition,":[185],"our":[186],"reduces":[188],"latency":[191],"model":[196],"(e.g.,":[197],"Wan2.1-I2V-14B)":[198],"100":[200],"times,":[201],"while":[202],"preserving":[203],"competitive":[204],"performance.":[205]},"counts_by_year":[],"updated_date":"2026-03-20T20:47:17.329874","created_date":"2026-03-18T00:00:00"}
