{"id":"https://openalex.org/W7154610248","doi":"https://doi.org/10.48550/arxiv.2604.13366","title":"Diffusion Sequence Models for Generative In-Context Meta-Learning of Robot Dynamics","display_name":"Diffusion Sequence Models for Generative In-Context Meta-Learning of Robot Dynamics","publication_year":2026,"publication_date":"2026-04-15","ids":{"openalex":"https://openalex.org/W7154610248","doi":"https://doi.org/10.48550/arxiv.2604.13366"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.13366","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.13366","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":"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"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.13366","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5107202253","display_name":"Angelo Moroncelli","orcid":"https://orcid.org/0009-0002-2100-5225"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Moroncelli, Angelo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5094123715","display_name":"Matteo Rufolo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rufolo, Matteo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133739636","display_name":"Gunes Cagin Aydin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aydin, Gunes Cagin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003810719","display_name":"Asad Ali Shahid","orcid":"https://orcid.org/0009-0001-0312-9657"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shahid, Asad Ali","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5086291668","display_name":"Loris Roveda","orcid":"https://orcid.org/0000-0002-4427-536X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Roveda, Loris","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/T11206","display_name":"Model Reduction and Neural Networks","score":0.21570000052452087,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.21570000052452087,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"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":0.17980000376701355,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.12520000338554382,"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/robustness","display_name":"Robustness (evolution)","score":0.7549999952316284},{"id":"https://openalex.org/keywords/inpainting","display_name":"Inpainting","score":0.5486999750137329},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5349000096321106},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5314000248908997},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5149999856948853},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.45179998874664307},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.39559999108314514},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.3882000148296356}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7549999952316284},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6330000162124634},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5699999928474426},{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.5486999750137329},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5349000096321106},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5314000248908997},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5149999856948853},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.45179998874664307},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.39559999108314514},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.3882000148296356},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3833000063896179},{"id":"https://openalex.org/C55128770","wikidata":"https://www.wikidata.org/wiki/Q5275440","display_name":"Diffusion map","level":4,"score":0.373199999332428},{"id":"https://openalex.org/C119247159","wikidata":"https://www.wikidata.org/wiki/Q1366192","display_name":"System identification","level":3,"score":0.3273000121116638},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.29660001397132874},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.29499998688697815},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.2890999913215637},{"id":"https://openalex.org/C142259097","wikidata":"https://www.wikidata.org/wiki/Q5891314","display_name":"Homogeneity (statistics)","level":2,"score":0.28619998693466187},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2849000096321106},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28119999170303345},{"id":"https://openalex.org/C77405623","wikidata":"https://www.wikidata.org/wiki/Q598451","display_name":"System dynamics","level":2,"score":0.2766000032424927},{"id":"https://openalex.org/C79610928","wikidata":"https://www.wikidata.org/wiki/Q1656743","display_name":"Parameter identification problem","level":3,"score":0.2660999894142151},{"id":"https://openalex.org/C31531917","wikidata":"https://www.wikidata.org/wiki/Q915157","display_name":"Robust control","level":3,"score":0.2581000030040741}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.13366","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.13366","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.13366","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.13366","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":"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"},"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":{"Accurate":[0],"modeling":[1],"of":[2],"robot":[3],"dynamics":[4,40],"is":[5],"essential":[6],"for":[7,38,105,145,157],"model-based":[8],"control,":[9],"yet":[10],"remains":[11],"challenging":[12],"under":[13,115],"distributional":[14],"shifts":[15],"and":[16,31,34,52,71,77,96],"real-time":[17,140],"constraints.":[18],"In":[19],"this":[20,55],"work,":[21],"we":[22,91,129],"formulate":[23],"system":[24,159],"identification":[25,160],"as":[26,47,99,101,153],"an":[27],"in-context":[28],"meta-learning":[29],"problem":[30],"compare":[32],"deterministic":[33,50],"generative":[35,151],"sequence":[36],"models":[37,75,111,136],"forward":[39],"prediction.":[41],"We":[42,107],"take":[43],"a":[44,48,154],"Transformer-based":[45],"meta-model,":[46],"strong":[49],"baseline,":[51],"introduce":[53],"to":[54,137],"setting":[56],"two":[57],"complementary":[58],"diffusion-based":[59],"approaches:":[60],"(i)":[61],"inpainting":[62,119],"diffusion":[63,74,110,120,135],"(Diffuser),":[64],"which":[65,79],"learns":[66],"the":[67,122],"joint":[68],"input-observation":[69],"distribution,":[70],"(ii)":[72],"conditioned":[73,83],"(CNN":[76],"Transformer),":[78],"generate":[80],"future":[81],"observations":[82],"on":[84],"control":[85,146],"inputs.":[86],"Through":[87],"large-scale":[88],"randomized":[89],"simulations,":[90],"analyze":[92],"performance":[93,124],"across":[94],"in-distribution":[95],"out-of-distribution":[97],"regimes,":[98],"well":[100],"computational":[102],"trade-offs":[103],"relevant":[104],"control.":[106],"show":[108],"that":[109,131],"significantly":[112],"improve":[113],"robustness":[114],"distribution":[116],"shift,":[117],"with":[118],"achieving":[121],"best":[123],"in":[125,161],"our":[126],"experiments.":[127],"Finally,":[128],"demonstrate":[130],"warm-started":[132],"sampling":[133],"enables":[134],"operate":[138],"within":[139],"constraints,":[141],"making":[142],"them":[143],"viable":[144],"applications.":[147],"These":[148],"results":[149],"highlight":[150],"meta-models":[152],"promising":[155],"direction":[156],"robust":[158],"robotics.":[162]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-17T00:00:00"}
