{"id":"https://openalex.org/W7160553818","doi":"https://doi.org/10.48550/arxiv.2605.05126","title":"ConsisVLA-4D: Advancing Spatiotemporal Consistency in Efficient 3D-Perception and 4D-Reasoning for Robotic Manipulation","display_name":"ConsisVLA-4D: Advancing Spatiotemporal Consistency in Efficient 3D-Perception and 4D-Reasoning for Robotic Manipulation","publication_year":2026,"publication_date":"2026-05-06","ids":{"openalex":"https://openalex.org/W7160553818","doi":"https://doi.org/10.48550/arxiv.2605.05126"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.05126","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05126","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.2605.05126","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135591337","display_name":"Wei Chen. Chao Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135602919","display_name":"Jizhihui Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Jizhihui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114534303","display_name":"Li Yixing","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yixing, Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065243247","display_name":"Junwen Tong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tong, Junwen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135541969","display_name":"Rui Shao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shao, Rui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135573590","display_name":"Liqiang Nie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nie, Liqiang","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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.8233000040054321,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.8233000040054321,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.031599998474121094,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.028300000354647636,"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/consistency","display_name":"Consistency (knowledge bases)","score":0.8197000026702881},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6735000014305115},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6082000136375427},{"id":"https://openalex.org/keywords/local-consistency","display_name":"Local consistency","score":0.5480999946594238},{"id":"https://openalex.org/keywords/consistency-model","display_name":"Consistency model","score":0.5385000109672546},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5278000235557556},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.48980000615119934},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.4781999886035919},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.4357999861240387}],"concepts":[{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.8197000026702881},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.71670001745224},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6735000014305115},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6082000136375427},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.607699990272522},{"id":"https://openalex.org/C137105694","wikidata":"https://www.wikidata.org/wiki/Q3407510","display_name":"Local consistency","level":4,"score":0.5480999946594238},{"id":"https://openalex.org/C37279795","wikidata":"https://www.wikidata.org/wiki/Q2492305","display_name":"Consistency model","level":3,"score":0.5385000109672546},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5278000235557556},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.48980000615119934},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4781999886035919},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.4357999861240387},{"id":"https://openalex.org/C155911833","wikidata":"https://www.wikidata.org/wiki/Q3817354","display_name":"Spatial intelligence","level":2,"score":0.43230000138282776},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4124999940395355},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.39430001378059387},{"id":"https://openalex.org/C27511587","wikidata":"https://www.wikidata.org/wiki/Q2178623","display_name":"Spatial relation","level":2,"score":0.3752000033855438},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3319999873638153},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33149999380111694},{"id":"https://openalex.org/C122377713","wikidata":"https://www.wikidata.org/wiki/Q4422799","display_name":"Weak consistency","level":4,"score":0.32249999046325684},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3061999976634979},{"id":"https://openalex.org/C2776010242","wikidata":"https://www.wikidata.org/wiki/Q4677575","display_name":"Active perception","level":3,"score":0.30239999294281006},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.30160000920295715},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2955999970436096},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2953999936580658},{"id":"https://openalex.org/C82029504","wikidata":"https://www.wikidata.org/wiki/Q4373882","display_name":"Sequential consistency","level":4,"score":0.2906000018119812},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.2632000148296356},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26030001044273376},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.26019999384880066}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.05126","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05126","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.2605.05126","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05126","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Current":[0],"Vision-Language-Action":[1],"(VLA)":[2],"models":[3],"primarily":[4],"focus":[5],"on":[6,26,189],"mapping":[7],"2D":[8],"observations":[9],"to":[10,39,125,187],"actions,":[11],"but":[12],"exhibit":[13],"notable":[14],"limitations":[15],"in":[16,69],"spatiotemporal":[17,51,67,128,169],"perception":[18,71],"and":[19,48,62,72,90,145,175,182,193,199],"reasoning:":[20],"1)":[21,78],"spatial":[22,102,107],"representations":[23],"often":[24],"rely":[25],"additional":[27],"sensors,":[28],"introducing":[29],"substantial":[30],"computational":[31],"overhead;":[32],"2)":[33,97],"visual":[34,156],"reasoning":[35,157],"is":[36,197],"typically":[37],"limited":[38],"future-frame":[40],"prediction,":[41],"lacking":[42],"alignment":[43],"with":[44,180],"the":[45,190],"instruction-grounded":[46],"scene":[47,159],"thus":[49],"compromising":[50],"consistency.":[52],"To":[53],"address":[54],"these":[55],"challenges,":[56],"we":[57,76,121],"propose":[58],"ConsisVLA-4D,":[59],"a":[60],"unified":[61],"efficient":[63,155,168],"framework":[64],"that":[65],"enhances":[66],"consistency":[68,85,104,129,170],"3D":[70],"4D":[73],"reasoning.":[74],"Specifically,":[75],"design:":[77],"CV-Aligner,":[79],"which":[80,99],"ensures":[81],"cross-view":[82],"object":[83,92],"semantic":[84],"by":[86,105],"filtering":[87],"instruction-relevant":[88],"regions":[89],"aligning":[91],"identities":[93],"across":[94,112],"multiple":[95],"viewpoints;":[96],"CO-Fuser,":[98,152],"guarantees":[100],"cross-object":[101],"geometric":[103,149],"eliminating":[106],"relation":[108],"ambiguities":[109],"between":[110],"objects":[111],"views":[113],"using":[114],"compact":[115],"latent":[116],"representations.":[117],"Building":[118],"upon":[119],"these,":[120],"introduce":[122],"3)":[123],"CS-Thinker":[124],"achieve":[126],"cross-scene":[127],"as":[130],"actions":[131],"unfold.":[132],"It":[133],"learns":[134],"implicit":[135],"knowledge":[136],"of":[137,143,151],"local":[138],"dynamics":[139],"from":[140,148,166],"object-semantic":[141],"tokens":[142,150],"CV-Aligner":[144],"global":[146],"depth":[147],"thereby":[153],"enhancing":[154],"under":[158],"variations.":[160],"Extensive":[161],"experiments":[162],"demonstrate":[163],"that,":[164],"benefiting":[165],"its":[167],"design,":[171],"ConsisVLA-4D":[172],"achieves":[173],"21.6%":[174],"41.5%":[176],"performance":[177],"improvements,":[178],"along":[179],"2.3-fold":[181],"2.4-fold":[183],"inference":[184],"speedups":[185],"compared":[186],"OpenVLA":[188],"LIBERO":[191],"benchmark":[192],"real-world":[194],"platforms,":[195],"respectively.ConsisVLA-4D":[196],"open-sourced":[198],"publicly":[200],"available":[201],"at":[202]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-08T00:00:00"}