{"id":"https://openalex.org/W7138997467","doi":"https://doi.org/10.48550/arxiv.2603.17834","title":"Generative Control as Optimization: Time Unconditional Flow Matching for Adaptive and Robust Robotic Control","display_name":"Generative Control as Optimization: Time Unconditional Flow Matching for Adaptive and Robust Robotic Control","publication_year":2026,"publication_date":"2026-03-18","ids":{"openalex":"https://openalex.org/W7138997467","doi":"https://doi.org/10.48550/arxiv.2603.17834"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.17834","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17834","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.17834","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129919191","display_name":"Zunzhe Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhang, Zunzhe","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063823658","display_name":"Runhan Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Runhan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129903695","display_name":"Yicheng Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yicheng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040608113","display_name":"Shaoting Zhu","orcid":"https://orcid.org/0009-0000-9294-6212"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Shaoting","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031959594","display_name":"Linzhan Mou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mou, Linzhan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130179745","display_name":"Hang Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Hang","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5129919191"],"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/T10653","display_name":"Robot Manipulation and Learning","score":0.3659999966621399,"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"}},"topics":[{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.3659999966621399,"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"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.15109999477863312,"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":0.13230000436306,"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/inference","display_name":"Inference","score":0.4722999930381775},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.4715999960899353},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.45730000734329224},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4564000070095062},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.3894999921321869},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.3467000126838684},{"id":"https://openalex.org/keywords/adaptive-control","display_name":"Adaptive control","score":0.3440000116825104},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.34380000829696655},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.33970001339912415}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6657000184059143},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4722999930381775},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.4715999960899353},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.45730000734329224},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4564000070095062},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.41600000858306885},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3894999921321869},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.3467000126838684},{"id":"https://openalex.org/C107464732","wikidata":"https://www.wikidata.org/wiki/Q235781","display_name":"Adaptive control","level":3,"score":0.3440000116825104},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.34380000829696655},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3400999903678894},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.33970001339912415},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32109999656677246},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.31679999828338623},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.31459999084472656},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.310699999332428},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.30320000648498535},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.2978000044822693},{"id":"https://openalex.org/C131675550","wikidata":"https://www.wikidata.org/wiki/Q7646884","display_name":"Surrogate model","level":2,"score":0.2831999957561493},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C203479927","wikidata":"https://www.wikidata.org/wiki/Q5165939","display_name":"Controller (irrigation)","level":2,"score":0.26930001378059387},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.26339998841285706},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.262800008058548},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.26190000772476196},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C80884492","wikidata":"https://www.wikidata.org/wiki/Q3345678","display_name":"Reproducing kernel Hilbert space","level":3,"score":0.2531000077724457},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.25209999084472656},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.251800000667572}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.17834","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17834","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.17834","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17834","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":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Diffusion":[0],"models":[1],"and":[2,157,178,188],"flow":[3],"matching":[4],"have":[5],"become":[6],"a":[7,17,26,63,78,135,167],"cornerstone":[8],"of":[9],"robotic":[10],"imitation":[11],"learning,":[12],"yet":[13],"they":[14],"suffer":[15],"from":[16,70],"structural":[18],"inefficiency":[19],"where":[20,86],"inference":[21,94],"is":[22,31],"often":[23],"bound":[24],"to":[25,33,41,161],"fixed":[27],"integration":[28,72],"schedule":[29],"that":[30,66,99],"agnostic":[32],"state":[34],"complexity.":[35],"This":[36],"paradigm":[37],"forces":[38],"the":[39,43,83,126,130],"policy":[40],"expend":[42],"same":[44],"computational":[45],"budget":[46],"on":[47,53,103,153],"trivial":[48],"motions":[49],"as":[50,60,125,134],"it":[51],"does":[52],"complex":[54],"tasks.":[55],"We":[56,150],"introduce":[57],"Generative":[58],"Control":[59],"Optimization":[61],"(GeCO),":[62],"time-unconditional":[64],"framework":[65],"transforms":[67],"action":[68,132],"synthesis":[69],"trajectory":[71],"into":[73],"iterative":[74],"optimization.":[75],"GeCO":[76,152,174],"learns":[77],"stationary":[79,117],"velocity":[80],"field":[81,127],"in":[82],"action-sequence":[84],"space":[85],"expert":[87],"behaviors":[88],"form":[89],"stable":[90],"attractors.":[91],"Consequently,":[92],"test-time":[93],"becomes":[95],"an":[96,120,181],"adaptive":[97],"process":[98],"allocates":[100],"computation":[101],"based":[102],"convergence--exiting":[104],"early":[105],"for":[106,112,142,148,170,184],"simple":[107],"states":[108,144],"while":[109,145],"refining":[110],"longer":[111],"difficult":[113],"ones.":[114],"Furthermore,":[115],"this":[116],"geometry":[118],"yields":[119],"intrinsic,":[121],"training-free":[122],"safety":[123],"signal,":[124],"norm":[128],"at":[129,193],"optimized":[131],"serves":[133],"robust":[136],"out-of-distribution":[137],"(OOD)":[138],"detector,":[139],"remaining":[140],"low":[141],"in-distribution":[143],"significantly":[146],"increasing":[147],"anomalies.":[149],"validate":[151],"standard":[154,171],"simulation":[155],"benchmarks":[156],"demonstrate":[158],"seamless":[159],"scaling":[160],"pi0-series":[162],"Vision-Language-Action":[163],"(VLA)":[164],"models.":[165],"As":[166],"plug-and-play":[168],"replacement":[169],"flow-matching":[172],"heads,":[173],"improves":[175],"success":[176],"rates":[177],"efficiency":[179],"with":[180],"optimization-native":[182],"mechanism":[183],"safe":[185],"deployment.":[186],"Video":[187],"code":[189],"can":[190],"be":[191],"found":[192],"https://hrh6666.github.io/GeCO/":[194]},"counts_by_year":[],"updated_date":"2026-03-20T20:54:20.808490","created_date":"2026-03-20T00:00:00"}