{"id":"https://openalex.org/W7143413153","doi":"https://doi.org/10.48550/arxiv.2603.26320","title":"DFM-VLA: Iterative Action Refinement for Robot Manipulation via Discrete Flow Matching","display_name":"DFM-VLA: Iterative Action Refinement for Robot Manipulation via Discrete Flow Matching","publication_year":2026,"publication_date":"2026-03-27","ids":{"openalex":"https://openalex.org/W7143413153","doi":"https://doi.org/10.48550/arxiv.2603.26320"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.26320","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.26320","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.2603.26320","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130991683","display_name":"Jiayi Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Jiayi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130944031","display_name":"Wenxuan Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Wenxuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130970634","display_name":"Shuai Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Shuai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130981685","display_name":"Jingbo Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Jingbo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130962305","display_name":"Zhijun Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Zhijun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130931190","display_name":"Haoang Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Haoang","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/T10653","display_name":"Robot Manipulation and Learning","score":0.6779000163078308,"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":0.6779000163078308,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.061500001698732376,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.05829999968409538,"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/decoding-methods","display_name":"Decoding methods","score":0.6200000047683716},{"id":"https://openalex.org/keywords/iterative-refinement","display_name":"Iterative refinement","score":0.5447999835014343},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.5351999998092651},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.49630001187324524},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.48010000586509705},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4771000146865845},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.44339999556541443},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.4318999946117401},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.37369999289512634}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7095000147819519},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.6200000047683716},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5557000041007996},{"id":"https://openalex.org/C2779982483","wikidata":"https://www.wikidata.org/wiki/Q6094420","display_name":"Iterative refinement","level":2,"score":0.5447999835014343},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.5351999998092651},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.49630001187324524},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.48010000586509705},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4771000146865845},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.44339999556541443},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.4318999946117401},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.37369999289512634},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.36629998683929443},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.35499998927116394},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3440999984741211},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.3352999985218048},{"id":"https://openalex.org/C2778858076","wikidata":"https://www.wikidata.org/wiki/Q5249539","display_name":"Decodes","level":3,"score":0.3336000144481659},{"id":"https://openalex.org/C55689738","wikidata":"https://www.wikidata.org/wiki/Q15963867","display_name":"Discrete time and continuous time","level":2,"score":0.3294999897480011},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.32760000228881836},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3127000033855438},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.30140000581741333},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.2849999964237213},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.28299999237060547},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.2815000116825104},{"id":"https://openalex.org/C2778584072","wikidata":"https://www.wikidata.org/wiki/Q7353545","display_name":"Robustification","level":3,"score":0.27399998903274536},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.2662999927997589},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2637999951839447},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.258899986743927},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.2581000030040741}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.26320","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.26320","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.2603.26320","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.26320","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":{"Vision--Language--Action":[0],"(VLA)":[1],"models":[2],"that":[3,84,141],"encode":[4],"actions":[5,25],"using":[6],"a":[7,40,67,79,115],"discrete":[8,36,68,147,189],"tokenization":[9],"scheme":[10],"are":[11,26],"increasingly":[12],"adopted":[13],"for":[14,72,128,192],"robotic":[15,193],"manipulation,":[16],"but":[17],"existing":[18],"decoding":[19,117],"paradigms":[20],"remain":[21],"fundamentally":[22],"limited.":[23],"Whether":[24],"decoded":[27],"sequentially":[28],"by":[29,35,125],"autoregressive":[30],"VLAs":[31],"or":[32],"in":[33,52,153],"parallel":[34],"diffusion":[37,151],"VLAs,":[38],"once":[39],"token":[41,57],"is":[42,45,197],"generated,":[43],"it":[44],"typically":[46],"fixed":[47],"and":[48,107,136,149,173],"cannot":[49,59],"be":[50,60],"revised":[51],"subsequent":[53],"iterations,":[54],"so":[55],"early":[56],"errors":[58],"effectively":[61],"corrected":[62],"later.":[63],"We":[64,94],"propose":[65],"DFM-VLA,":[66],"flow":[69,190],"matching":[70,191],"VLA":[71],"iterative":[73,121],"refinement":[74,92,122,187],"of":[75,169,178,185],"action":[76,89,186],"tokens.":[77],"DFM-VLA~models":[78],"token-level":[80],"probability":[81],"velocity":[82,101],"field":[83],"dynamically":[85],"updates":[86],"the":[87,100,183],"full":[88],"sequence":[90],"across":[91],"iterations.":[93],"investigate":[95],"two":[96],"ways":[97],"to":[98],"construct":[99],"field:":[102],"an":[103,108,120,165,174],"auxiliary":[104],"velocity-head":[105],"formulation":[106],"action-embedding-guided":[109],"formulation.":[110],"Our":[111,195],"framework":[112],"further":[113],"adopts":[114],"two-stage":[116],"strategy":[118],"with":[119],"stage":[123],"followed":[124],"deterministic":[126],"validation":[127],"stable":[129],"convergence.":[130],"Extensive":[131],"experiments":[132],"on":[133,171,180],"CALVIN,":[134],"LIBERO,":[135,181],"real-world":[137],"manipulation":[138,154],"tasks":[139],"show":[140],"DFM-VLA":[142,163],"consistently":[143],"outperforms":[144],"strong":[145],"autoregressive,":[146],"diffusion,":[148],"continuous":[150],"baselines":[152],"performance":[155],"while":[156],"retaining":[157],"high":[158],"inference":[159],"efficiency.":[160],"In":[161],"particular,":[162],"achieves":[164],"average":[166,175],"success":[167,176],"length":[168],"4.44":[170],"CALVIN":[172],"rate":[177],"95.7\\%":[179],"highlighting":[182],"value":[184],"via":[188],"manipulation.":[194],"project":[196],"available":[198],"https://chris1220313648.github.io/DFM-VLA/":[199]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-31T00:00:00"}
