{"id":"https://openalex.org/W7165735884","doi":"https://doi.org/10.48550/arxiv.2606.24051","title":"DriveStack-VLA: Render-Teacher Alignment for BEV-Based DeepStack Vision-Language-Action Model","display_name":"DriveStack-VLA: Render-Teacher Alignment for BEV-Based DeepStack Vision-Language-Action Model","publication_year":2026,"publication_date":"2026-06-23","ids":{"openalex":"https://openalex.org/W7165735884","doi":"https://doi.org/10.48550/arxiv.2606.24051"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.24051","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.24051","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.2606.24051","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052973548","display_name":"Jingke Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Jingke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107849883","display_name":"Z. Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Zhenru","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139281070","display_name":"Shuangming Lei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lei, Shuangming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139256194","display_name":"Hao Su","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Su, Hao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126420301","display_name":"Y Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Yuehao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130376473","display_name":"Yijia Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Yijia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139263915","display_name":"Kai Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Kai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003023334","display_name":"Guanglin Xu","orcid":"https://orcid.org/0009-0007-7743-9088"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Guanglin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139228178","display_name":"AiXue Ye","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ye, AiXue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139231409","display_name":"Yukai Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Yukai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139291246","display_name":"Yong Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yong","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":0.970300018787384,"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":0.970300018787384,"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":0.006500000134110451,"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":0.0038999998942017555,"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/focus","display_name":"Focus (optics)","score":0.5256999731063843},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5058000087738037},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.49790000915527344},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.48100000619888306},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4779999852180481},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.44429999589920044},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.44029998779296875},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.4189999997615814}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7293000221252441},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.603600025177002},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5419999957084656},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5256999731063843},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5058000087738037},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.49790000915527344},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.48100000619888306},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4779999852180481},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.44429999589920044},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.44029998779296875},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.4189999997615814},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4083999991416931},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.39010000228881836},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.3424000144004822},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.30329999327659607},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.29980000853538513},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2978000044822693},{"id":"https://openalex.org/C2780878386","wikidata":"https://www.wikidata.org/wiki/Q1659648","display_name":"Visual language","level":2,"score":0.29120001196861267},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2802000045776367},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.2581000030040741}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.24051","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.24051","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.2606.24051","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.24051","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":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.5117143392562866}],"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],"driving":[1,10,25,180],"models":[2,26,64],"convert":[3],"a":[4,9,83,87,107,117,148,179,185],"pretrained":[5],"Vision-Language":[6],"Model":[7,114],"into":[8,110],"policy,":[11],"allowing":[12],"them":[13],"to":[14,56,66,124,138],"use":[15],"world":[16],"knowledge":[17],"and":[18,41,54,71,120,156,178],"follow":[19],"language":[20,42],"guidances.":[21],"However,":[22],"existing":[23],"VLA":[24,97],"still":[27],"lack":[28],"driving-oriented":[29],"spatial":[30,94],"intelligence:":[31],"their":[32],"policies":[33],"are":[34,196],"mainly":[35],"grounded":[36],"on":[37,166,170,190,198],"perspective":[38],"image":[39],"tokens":[40],"priors,":[43],"while":[44],"precise":[45],"motion":[46],"planning":[47],"requires":[48],"metric":[49],"geometry,":[50],"top-down":[51],"scene":[52],"structure,":[53],"attention":[55],"safety-critical":[57],"perceptual":[58,72,127],"cues.":[59],"This":[60],"limitation":[61],"makes":[62],"current":[63],"vulnerable":[65],"weak":[67],"visual":[68,102],"geometry":[69],"modeling":[70,103],"coverage":[73],"in":[74,142],"expert":[75],"demonstrations.":[76],"In":[77],"this":[78],"paper,":[79],"we":[80,99,146],"present":[81],"DriveStack-VLA,":[82],"framework":[84],"built":[85],"upon":[86],"large":[88],"VLM":[89],"backbone.":[90],"To":[91],"strengthen":[92],"the":[93,111,126,140,159,173,191],"grounding":[95],"of":[96,129,134,182,188],"driving,":[98],"develop":[100],"dual":[101],"components.":[104],"We":[105],"inject":[106],"Bird-Eye-View":[108],"representation":[109],"Large":[112],"Language":[113],"decoder":[115],"through":[116],"DeepStack-style":[118],"connection,":[119],"propose":[121],"Render-Teacher":[122],"Alignment":[123],"align":[125],"focus":[128],"real":[130],"images":[131],"with":[132,184],"that":[133,152],"rasterized":[135],"images.":[136],"Furthermore,":[137],"bridge":[139],"gap":[141],"multimodal":[143],"trajectory":[144],"selection,":[145],"introduce":[147],"head-based":[149],"self-critique":[150],"module":[151],"ranks":[153],"sampled":[154],"trajectories":[155],"conditionally":[157],"refines":[158],"best":[160],"one.":[161],"DriveStack-VLA":[162],"achieves":[163],"91.6":[164],"PDMS":[165],"NAVSIMv1,":[167],"91.0":[168],"EPDMS":[169],"NAVSIMv2":[171],"(with":[172],"human":[174],"penalty":[175],"filter":[176],"enabled),":[177],"score":[181],"79.49":[183],"success":[186],"rate":[187],"56.36\\%":[189],"closed-loop":[192],"Bench2Drive.":[193],"More":[194],"visualizations":[195],"available":[197],"our":[199],"project":[200],"page:":[201],"https://anonymous.4open.science/w/drivestack-vla/.":[202]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-25T00:00:00"}