{"id":"https://openalex.org/W7216583427","doi":"https://doi.org/10.48550/arxiv.2610.00722","title":"JEPA-TTT: Persistent Test-Time Training of Latent World Models for Planning under Dynamics Shifts","display_name":"JEPA-TTT: Persistent Test-Time Training of Latent World Models for Planning under Dynamics Shifts","publication_year":2026,"publication_date":"2026-09-30","ids":{"openalex":"https://openalex.org/W7216583427","doi":"https://doi.org/10.48550/arxiv.2610.00722"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2610.00722","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.00722","pdf_url":"https://arxiv.org/pdf/2610.00722","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2610.00722","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5155097457","display_name":"Zheyuan Zhang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]},{"id":"https://openalex.org/I4210145184","display_name":"Honda (United States)","ror":"https://ror.org/04vdmc602","country_code":"US","type":"company","lineage":["https://openalex.org/I1283473643","https://openalex.org/I4210145184"]},{"id":"https://openalex.org/I4405271240","display_name":"Honda Research Institute, USA","ror":"https://ror.org/02441en43","country_code":"US","type":"facility","lineage":["https://openalex.org/I4405271240"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhang, Zheyuan","raw_affiliation_strings":["Honda Research Institute USA","Johns Hopkins University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Honda Research Institute USA","institution_ids":["https://openalex.org/I4210145184","https://openalex.org/I4405271240"]},{"raw_affiliation_string":"Johns Hopkins University","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126686187","display_name":"Suyu Ye","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]},{"id":"https://openalex.org/I4210145184","display_name":"Honda (United States)","ror":"https://ror.org/04vdmc602","country_code":"US","type":"company","lineage":["https://openalex.org/I1283473643","https://openalex.org/I4210145184"]},{"id":"https://openalex.org/I4405271240","display_name":"Honda Research Institute, USA","ror":"https://ror.org/02441en43","country_code":"US","type":"facility","lineage":["https://openalex.org/I4405271240"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ye, Suyu","raw_affiliation_strings":["Honda Research Institute USA","Johns Hopkins University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Honda Research Institute USA","institution_ids":["https://openalex.org/I4210145184","https://openalex.org/I4405271240"]},{"raw_affiliation_string":"Johns Hopkins University","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073021106","display_name":"Nakul Agarwal","orcid":"https://orcid.org/0000-0002-7684-6075","observed_orcids":["https://orcid.org/0000-0002-7684-6075"]},"institutions":[{"id":"https://openalex.org/I4210145184","display_name":"Honda (United States)","ror":"https://ror.org/04vdmc602","country_code":"US","type":"company","lineage":["https://openalex.org/I1283473643","https://openalex.org/I4210145184"]},{"id":"https://openalex.org/I4405271240","display_name":"Honda Research Institute, USA","ror":"https://ror.org/02441en43","country_code":"US","type":"facility","lineage":["https://openalex.org/I4405271240"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Agarwal, Nakul","raw_affiliation_strings":["Honda Research Institute USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Honda Research Institute USA","institution_ids":["https://openalex.org/I4210145184","https://openalex.org/I4405271240"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001543635","display_name":"Hossein Nourkhiz Mahjoub","orcid":"https://orcid.org/0000-0002-8380-3241","observed_orcids":["https://orcid.org/0000-0002-8380-3241"]},"institutions":[{"id":"https://openalex.org/I4210145184","display_name":"Honda (United States)","ror":"https://ror.org/04vdmc602","country_code":"US","type":"company","lineage":["https://openalex.org/I1283473643","https://openalex.org/I4210145184"]},{"id":"https://openalex.org/I4405271240","display_name":"Honda Research Institute, USA","ror":"https://ror.org/02441en43","country_code":"US","type":"facility","lineage":["https://openalex.org/I4405271240"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mahjoub, Hossein Nourkhiz","raw_affiliation_strings":["Honda Research Institute USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Honda Research Institute USA","institution_ids":["https://openalex.org/I4210145184","https://openalex.org/I4405271240"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032101438","display_name":"Ehsan Moradi\u2010Pari","orcid":"https://orcid.org/0000-0002-4822-3196","observed_orcids":["https://orcid.org/0000-0002-4822-3196"]},"institutions":[{"id":"https://openalex.org/I4210145184","display_name":"Honda (United States)","ror":"https://ror.org/04vdmc602","country_code":"US","type":"company","lineage":["https://openalex.org/I1283473643","https://openalex.org/I4210145184"]},{"id":"https://openalex.org/I4405271240","display_name":"Honda Research Institute, USA","ror":"https://ror.org/02441en43","country_code":"US","type":"facility","lineage":["https://openalex.org/I4405271240"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pari, Ehsan Moradi","raw_affiliation_strings":["Honda Research Institute USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Honda Research Institute USA","institution_ids":["https://openalex.org/I4210145184","https://openalex.org/I4405271240"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043628255","display_name":"Daniel Khashabi","orcid":"https://orcid.org/0009-0009-7664-2230","observed_orcids":["https://orcid.org/0009-0009-7664-2230"]},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Khashabi, Daniel","raw_affiliation_strings":["Johns Hopkins University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Johns Hopkins University","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005908625","display_name":"Tianmin Shu","orcid":"https://orcid.org/0000-0001-5734-0653","observed_orcids":["https://orcid.org/0000-0001-5734-0653"]},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shu, Tianmin","raw_affiliation_strings":["Johns Hopkins University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Johns Hopkins University","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024302009","display_name":"Vaishnav Tadiparthi","orcid":"https://orcid.org/0000-0001-9897-0600","observed_orcids":["https://orcid.org/0000-0001-9897-0600"]},"institutions":[{"id":"https://openalex.org/I4210145184","display_name":"Honda (United States)","ror":"https://ror.org/04vdmc602","country_code":"US","type":"company","lineage":["https://openalex.org/I1283473643","https://openalex.org/I4210145184"]},{"id":"https://openalex.org/I4405271240","display_name":"Honda Research Institute, USA","ror":"https://ror.org/02441en43","country_code":"US","type":"facility","lineage":["https://openalex.org/I4405271240"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tadiparthi, Vaishnav","raw_affiliation_strings":["Honda Research Institute USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Honda Research Institute USA","institution_ids":["https://openalex.org/I4210145184","https://openalex.org/I4405271240"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9980000257492065,"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"}},"topics":[{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9980000257492065,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.0008999999845400453,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.0003000000142492354,"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/world-models","display_name":"world models","score":0.7940000295639038},{"id":"https://openalex.org/keywords/test-time-training","display_name":"test-time training","score":0.640999972820282},{"id":"https://openalex.org/keywords/jepa","display_name":"JEPA","score":0.7260000109672546},{"id":"https://openalex.org/keywords/self-supervised-learning","display_name":"self-supervised learning","score":0.7820000052452087},{"id":"https://openalex.org/keywords/planning","display_name":"planning","score":0.5569999814033508},{"id":"https://openalex.org/keywords/continuous-control","display_name":"continuous control","score":0.7210000157356262}],"concepts":[{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6534000039100647},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.632099986076355},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.618399977684021},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6144999861717224},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.5952000021934509},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.5512999892234802},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5368000268936157},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4731000065803528},{"id":"https://openalex.org/C2776505523","wikidata":"https://www.wikidata.org/wiki/Q4785468","display_name":"Plan (archaeology)","level":2,"score":0.37880000472068787},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.3747999966144562},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3610999882221222},{"id":"https://openalex.org/C167085575","wikidata":"https://www.wikidata.org/wiki/Q6803654","display_name":"Mean squared prediction error","level":2,"score":0.319599986076355},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.2883000075817108},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.2533999979496002}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2610.00722","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.00722","pdf_url":"https://arxiv.org/pdf/2610.00722","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2610.00722","doi":"https://doi.org/10.48550/arxiv.2610.00722","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2610.00722","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,"listed_in":[],"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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2610.00722","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.00722","pdf_url":"https://arxiv.org/pdf/2610.00722","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7216583427.pdf","grobid_xml":"https://content.openalex.org/works/W7216583427.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W2736601468","https://openalex.org/W2781585732","https://openalex.org/W2787613197","https://openalex.org/W2795843265","https://openalex.org/W2903630557","https://openalex.org/W2992977009","https://openalex.org/W3037655992","https://openalex.org/W3041404693","https://openalex.org/W3119543788","https://openalex.org/W3178351738","https://openalex.org/W4387947644","https://openalex.org/W4394861491","https://openalex.org/W4400435102","https://openalex.org/W4415336982","https://openalex.org/W4416338927","https://openalex.org/W4417261359","https://openalex.org/W7135201772","https://openalex.org/W7140141371","https://openalex.org/W7160981724","https://openalex.org/W7166853236","https://openalex.org/W7167797435"],"related_works":["https://openalex.org/W7166853236","https://openalex.org/W7161045822","https://openalex.org/W7222131363","https://openalex.org/W7213911053","https://openalex.org/W7214783055","https://openalex.org/W7171663849","https://openalex.org/W7223126082","https://openalex.org/W7201875857","https://openalex.org/W7203783470","https://openalex.org/W7165671954"],"abstract_inverted_index":{"World":[0],"models":[1],"enable":[2],"agents":[3],"to":[4],"plan":[5],"by":[6,131,139],"predicting":[7],"future":[8],"states":[9],"of":[10,37],"the":[11,33,55,64,142],"environment,":[12],"but":[13],"their":[14],"predictions":[15],"can":[16,155],"become":[17],"unreliable":[18],"when":[19],"test-time":[20,123,153],"dynamics":[21,35,109],"differ":[22],"from":[23,101],"those":[24],"seen":[25],"during":[26],"training.":[27],"We":[28],"present":[29],"JEPA-TTT,":[30],"which":[31,84],"adapts":[32],"latent":[34,128,159],"predictor":[36,105],"a":[38,73,95,157],"pretrained":[39,65,158],"action-conditioned":[40],"Joint-Embedding":[41],"Predictive":[42],"Architecture":[43],"world":[44,145,160],"model":[45,161],"throughout":[46],"test":[47],"time.":[48],"Self-supervised":[49],"updates":[50],"accumulate":[51],"across":[52],"episodes,":[53,124],"while":[54],"visual":[56],"encoder":[57],"and":[58,67,98,135],"reward":[59],"head":[60],"remain":[61],"fixed,":[62],"preserving":[63],"representation":[66],"task":[68],"objective.":[69],"Planning":[70],"requires":[71],"neither":[72],"goal":[74],"image":[75],"nor":[76],"online":[77],"environment":[78],"reward.":[79],"JEPA-TTT":[80,115],"uses":[81],"dense":[82],"replay,":[83],"forms":[85],"prediction":[86,129],"windows":[87],"at":[88],"every":[89,119],"temporal":[90],"offset,":[91],"retains":[92],"them":[93],"in":[94,111],"growing":[96],"buffer,":[97],"samples":[99],"minibatches":[100],"that":[102,150],"buffer":[103],"for":[104],"updates.":[106],"Across":[107],"eight":[108],"shifts":[110],"four":[112],"continuous-control":[113],"environments,":[114],"improves":[116,136],"planning":[117,137],"on":[118,133],"shift.":[120],"After":[121],"500":[122],"it":[125],"reduces":[126],"autoregressive":[127],"error":[130],"83%":[132],"average":[134],"performance":[138],"153%":[140],"over":[141],"frozen":[143],"JEPA":[144],"model.":[146],"These":[147],"results":[148],"show":[149],"persistent":[151],"self-supervised":[152],"training":[154],"adapt":[156],"under":[162],"changed":[163],"dynamics.":[164]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-10-03T00:00:00"}