{"id":"https://openalex.org/W7141138295","doi":"https://doi.org/10.48550/arxiv.2603.25716","title":"Out of Sight but Not Out of Mind: Hybrid Memory for Dynamic Video World Models","display_name":"Out of Sight but Not Out of Mind: Hybrid Memory for Dynamic Video World Models","publication_year":2026,"publication_date":"2026-03-26","ids":{"openalex":"https://openalex.org/W7141138295","doi":"https://doi.org/10.48550/arxiv.2603.25716"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.25716","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25716","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.2603.25716","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056134988","display_name":"Kaijin Chen","orcid":"https://orcid.org/0000-0002-1588-5361"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Kaijin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130765748","display_name":"Dingkang Liang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Dingkang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130728023","display_name":"Xin Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Xin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130779648","display_name":"Yikang Ding","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, Yikang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130783293","display_name":"Xiaoqiang Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Xiaoqiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130783984","display_name":"Pengfei Wan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wan, Pengfei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130729461","display_name":"Xiang Bai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bai, Xiang","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":0.3628999888896942,"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":0.3628999888896942,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.23199999332427979,"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/T12290","display_name":"Human Motion and Animation","score":0.11599999666213989,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bittorrent-tracker","display_name":"BitTorrent tracker","score":0.6534000039100647},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5835999846458435},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5584999918937683},{"id":"https://openalex.org/keywords/sight","display_name":"Sight","score":0.5067999958992004},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.49900001287460327},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.46239998936653137},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.4255000054836273},{"id":"https://openalex.org/keywords/hybrid-system","display_name":"Hybrid system","score":0.42289999127388},{"id":"https://openalex.org/keywords/subject","display_name":"Subject (documents)","score":0.385699987411499}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8273000121116638},{"id":"https://openalex.org/C57501372","wikidata":"https://www.wikidata.org/wiki/Q2021268","display_name":"BitTorrent tracker","level":3,"score":0.6534000039100647},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5835999846458435},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5806999802589417},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5584999918937683},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5195000171661377},{"id":"https://openalex.org/C1517167","wikidata":"https://www.wikidata.org/wiki/Q1134322","display_name":"Sight","level":2,"score":0.5067999958992004},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.49900001287460327},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.46239998936653137},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.4255000054836273},{"id":"https://openalex.org/C50897621","wikidata":"https://www.wikidata.org/wiki/Q2665508","display_name":"Hybrid system","level":2,"score":0.42289999127388},{"id":"https://openalex.org/C2777855551","wikidata":"https://www.wikidata.org/wiki/Q12310021","display_name":"Subject (documents)","level":2,"score":0.385699987411499},{"id":"https://openalex.org/C12186640","wikidata":"https://www.wikidata.org/wiki/Q6815743","display_name":"Memory model","level":3,"score":0.3799999952316284},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.35910001397132874},{"id":"https://openalex.org/C136085584","wikidata":"https://www.wikidata.org/wiki/Q910289","display_name":"Overlay","level":2,"score":0.3386000096797943},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3292999863624573},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.326200008392334},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.29840001463890076},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.2924000024795532},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.27900001406669617},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.2671000063419342},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C95020103","wikidata":"https://www.wikidata.org/wiki/Q1813492","display_name":"Match moving","level":3,"score":0.2551000118255615},{"id":"https://openalex.org/C118702147","wikidata":"https://www.wikidata.org/wiki/Q189396","display_name":"Dynamic random-access memory","level":3,"score":0.2547000050544739},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.2540999948978424}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.25716","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25716","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.2603.25716","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25716","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Video":[0],"world":[1],"models":[2,54],"have":[3],"shown":[4],"immense":[5],"potential":[6],"in":[7,79,171],"simulating":[8],"the":[9,85,152],"physical":[10],"world,":[11],"yet":[12],"existing":[13],"memory":[14,128,132],"mechanisms":[15],"primarily":[16],"treat":[17],"environments":[18],"as":[19,58],"static":[20,62],"canvases.":[21],"When":[22],"dynamic":[23,68,173],"subjects":[24],"hide":[25],"out":[26],"of":[27,156],"sight":[28],"and":[29,64,102,112,135,154,176],"later":[30],"re-emerge,":[31],"current":[32],"methods":[33],"often":[34],"struggle,":[35],"leading":[36],"to":[37,55,91,117,145],"frozen,":[38],"distorted,":[39],"or":[40],"vanishing":[41],"subjects.":[42,158],"To":[43,76],"address":[44],"this,":[45],"we":[46,82,123],"introduce":[47],"Hybrid":[48],"Memory,":[49],"a":[50,126,137],"novel":[51],"paradigm":[52],"requiring":[53],"simultaneously":[56],"act":[57],"precise":[59],"archivists":[60],"for":[61,67],"backgrounds":[63],"vigilant":[65],"trackers":[66],"subjects,":[69,111],"ensuring":[70],"motion":[71,147,155],"continuity":[72],"during":[73],"out-of-view":[74],"intervals.":[75],"facilitate":[77],"research":[78],"this":[80],"direction,":[81],"construct":[83],"HM-World,":[84],"first":[86],"large-scale":[87],"video":[88],"dataset":[89],"dedicated":[90],"hybrid":[92,120],"memory.":[93],"It":[94],"features":[95],"59K":[96],"high-fidelity":[97],"clips":[98],"with":[99],"decoupled":[100],"camera":[101],"subject":[103,174],"trajectories,":[104],"encompassing":[105],"17":[106],"diverse":[107],"scenes,":[108],"49":[109],"distinct":[110],"meticulously":[113],"designed":[114],"exit-entry":[115],"events":[116],"rigorously":[118],"evaluate":[119],"coherence.":[121],"Furthermore,":[122],"propose":[124],"HyDRA,":[125],"specialized":[127],"architecture":[129],"that":[130,164],"compresses":[131],"into":[133],"tokens":[134],"utilizes":[136],"spatiotemporal":[138],"relevance-driven":[139],"retrieval":[140],"mechanism.":[141],"By":[142],"selectively":[143],"attending":[144],"relevant":[146],"cues,":[148],"HyDRA":[149],"effectively":[150],"preserves":[151],"identity":[153],"hidden":[157],"Extensive":[159],"experiments":[160],"on":[161],"HM-World":[162],"demonstrate":[163],"our":[165],"method":[166],"significantly":[167],"outperforms":[168],"state-of-the-art":[169],"approaches":[170],"both":[172],"consistency":[175],"overall":[177],"generation":[178],"quality.":[179],"Code":[180],"is":[181],"publicly":[182],"available":[183],"at":[184],"https://github.com/H-EmbodVis/HyDRA.":[185]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-28T00:00:00"}