{"id":"https://openalex.org/W7131420888","doi":"https://doi.org/10.48550/arxiv.2602.20577","title":"Efficient and Explainable End-to-End Autonomous Driving via Masked Vision-Language-Action Diffusion","display_name":"Efficient and Explainable End-to-End Autonomous Driving via Masked Vision-Language-Action Diffusion","publication_year":2026,"publication_date":"2026-02-24","ids":{"openalex":"https://openalex.org/W7131420888","doi":"https://doi.org/10.48550/arxiv.2602.20577"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.20577","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059144000","display_name":"Jiaru Zhang","orcid":"https://orcid.org/0000-0001-5909-1005"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Jiaru","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107013288","display_name":"Manav Gagvani","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gagvani, Manav","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126788729","display_name":"Can Cui","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cui, Can","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126820980","display_name":"Juntong Peng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng, Juntong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126842230","display_name":"Ruqi Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Ruqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Wang, Ziran","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Ziran","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":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24017768,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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":0.3968999981880188,"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":0.3968999981880188,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.11699999868869781,"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"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.10639999806880951,"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/codebook","display_name":"Codebook","score":0.6388000249862671},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5990999937057495},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5609999895095825},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.5249999761581421},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.4810999929904938},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.4406000077724457},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4219000041484833},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.40310001373291016}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7572000026702881},{"id":"https://openalex.org/C127759330","wikidata":"https://www.wikidata.org/wiki/Q637416","display_name":"Codebook","level":2,"score":0.6388000249862671},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5990999937057495},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5609999895095825},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.5249999761581421},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49399998784065247},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.4810999929904938},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4406000077724457},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4219000041484833},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.40310001373291016},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.3653999865055084},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.35040000081062317},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.30410000681877136},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.303600013256073},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3018999993801117},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.28610000014305115},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2815999984741211},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.26910001039505005},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2685999870300293},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.2535000145435333},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.2533999979496002}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.20577","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.20577","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.20577","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":"pmh:doi:10.48550/arxiv.2602.20577","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.49412935972213745,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2,6],"(LLMs)":[3],"and":[4,28,77,148,157,161,170],"Vision-Language":[5],"(VLMs)":[7],"have":[8],"emerged":[9],"as":[10],"promising":[11],"candidates":[12],"for":[13,62],"end-to-end":[14],"autonomous":[15],"driving.":[16],"However,":[17],"these":[18],"models":[19],"typically":[20],"face":[21],"challenges":[22],"in":[23,125,164],"inference":[24],"latency,":[25],"action":[26,99],"precision,":[27,166],"explainability.":[29],"Existing":[30],"autoregressive":[31,160],"approaches":[32],"struggle":[33],"with":[34],"slow":[35],"token-by-token":[36],"generation,":[37],"while":[38,167],"prior":[39],"diffusion-based":[40],"planners":[41],"often":[42],"rely":[43],"on":[44,146],"verbose,":[45],"general-purpose":[46],"language":[47,93],"tokens":[48],"that":[49,88,102,123,152],"lack":[50],"explicit":[51],"geometric":[52,131],"structure.":[53],"In":[54],"this":[55],"work,":[56],"we":[57,95,116],"propose":[58,117],"Masked":[59],"Vision-Language-Action":[60],"Diffusion":[61],"Autonomous":[63],"Driving":[64],"(MVLAD-AD),":[65],"a":[66,81,97,104],"novel":[67],"framework":[68],"designed":[69],"to":[70,121,140],"bridge":[71],"the":[72,92,126],"gap":[73],"between":[74],"efficient":[75],"planning":[76,165],"semantic":[78],"explainability":[79],"via":[80],"masked":[82],"vision-language-action":[83],"diffusion":[84,162],"model.":[85],"Unlike":[86],"methods":[87],"force":[89],"actions":[90],"into":[91],"space,":[94],"introduce":[96],"discrete":[98],"tokenization":[100],"strategy":[101,137],"constructs":[103],"compact":[105],"codebook":[106],"of":[107],"kinematically":[108],"feasible":[109],"waypoints":[110],"from":[111],"real-world":[112],"driving":[113],"distributions.":[114],"Moreover,":[115],"geometry-aware":[118],"embedding":[119],"learning":[120],"ensure":[122],"embeddings":[124],"latent":[127],"space":[128],"approximate":[129],"physical":[130],"metrics.":[132],"Finally,":[133],"an":[134],"action-priority":[135],"decoding":[136],"is":[138],"introduced":[139],"prioritize":[141],"trajectory":[142],"generation.":[143],"Extensive":[144],"experiments":[145],"nuScenes":[147],"derived":[149],"benchmarks":[150],"demonstrate":[151],"MVLAD-AD":[153],"achieves":[154],"superior":[155],"efficiency":[156],"outperforms":[158],"state-of-the-art":[159],"baselines":[163],"providing":[168],"high-fidelity":[169],"explainable":[171],"reasoning.":[172]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2026-02-26T00:00:00"}
