{"id":"https://openalex.org/W7161556097","doi":"https://doi.org/10.48550/arxiv.2605.15964","title":"WorldVLN: Autoregressive World Action Model for Aerial Vision-Language Navigation","display_name":"WorldVLN: Autoregressive World Action Model for Aerial Vision-Language Navigation","publication_year":2026,"publication_date":"2026-05-15","ids":{"openalex":"https://openalex.org/W7161556097","doi":"https://doi.org/10.48550/arxiv.2605.15964"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.15964","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.15964","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.2605.15964","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043924969","display_name":"Baining Zhao","orcid":"https://orcid.org/0000-0002-9653-3316"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Baining","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136376153","display_name":"Jiacheng Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Jiacheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136374067","display_name":"Weicheng Feng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feng, Weicheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136442739","display_name":"Xin Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136419237","display_name":"Zhaolu Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Zhaolu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136405364","display_name":"Haoyang Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Haoyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136369698","display_name":"Shilong Ji","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ji, Shilong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136449126","display_name":"Ziyou Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Ziyou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136373211","display_name":"Jianjie Fang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fang, Jianjie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136378721","display_name":"Zhiheng Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Zhiheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136358433","display_name":"Weichen Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Weichen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133568517","display_name":"Yu Shang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shang, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136405656","display_name":"Wei Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136404617","display_name":"Chen Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136421357","display_name":"Xinlei Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Xinlei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136355935","display_name":"Yong Li","orcid":"https://orcid.org/0009-0002-1699-0769"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, 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":0.9797000288963318,"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":0.9797000288963318,"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":0.003800000064074993,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.002099999925121665,"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/waypoint","display_name":"Waypoint","score":0.8398000001907349},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.7412999868392944},{"id":"https://openalex.org/keywords/nonlinear-autoregressive-exogenous-model","display_name":"Nonlinear autoregressive exogenous model","score":0.614799976348877},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.6116999983787537},{"id":"https://openalex.org/keywords/executable","display_name":"Executable","score":0.5999000072479248},{"id":"https://openalex.org/keywords/drone","display_name":"Drone","score":0.5078999996185303},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.37459999322891235},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.30550000071525574}],"concepts":[{"id":"https://openalex.org/C2781271823","wikidata":"https://www.wikidata.org/wiki/Q138081","display_name":"Waypoint","level":2,"score":0.8398000001907349},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.7412999868392944},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6556000113487244},{"id":"https://openalex.org/C42536954","wikidata":"https://www.wikidata.org/wiki/Q7049462","display_name":"Nonlinear autoregressive exogenous model","level":3,"score":0.614799976348877},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.6116999983787537},{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.5999000072479248},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5309000015258789},{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.5078999996185303},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.40119999647140503},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38260000944137573},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.37459999322891235},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3384999930858612},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C107284991","wikidata":"https://www.wikidata.org/wiki/Q79757","display_name":"Barometer","level":2,"score":0.296099990606308},{"id":"https://openalex.org/C194657046","wikidata":"https://www.wikidata.org/wiki/Q7394685","display_name":"STAR model","level":4,"score":0.2955000102519989},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.27630001306533813},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.2703000009059906},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.2653000056743622},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.26350000500679016},{"id":"https://openalex.org/C2987819851","wikidata":"https://www.wikidata.org/wiki/Q191839","display_name":"Aerial imagery","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.15964","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.15964","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.2605.15964","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.15964","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Aerial":[0],"vision-language":[1],"navigation":[2,126],"(VLN)":[3],"requires":[4],"agents":[5],"to":[6,41,78,139,142,177],"follow":[7],"natural-language":[8],"instructions":[9],"through":[10,146],"closed-loop":[11,108],"perception":[12],"and":[13,38,83,128,154,167,195],"action":[14,55,93,192],"in":[15,124],"3D":[16],"environments.":[17],"We":[18,111],"argue":[19],"that":[20,65,118,182],"aerial":[21,58],"VLN":[22],"can":[23],"be":[24],"formulated":[25],"as":[26],"a":[27,73,114,187],"prediction-driven":[28],"world-action":[29,109],"problem:":[30],"the":[31,42,51,104,121,133,183],"agent":[32],"should":[33],"anticipate":[34],"latent":[35,74],"world":[36,54,63],"evolution":[37],"act":[39],"according":[40],"predicted":[43],"consequences.":[44,150],"To":[45],"this":[46],"end,":[47],"we":[48],"propose":[49],"WorldVLN,":[50],"first":[52,119,134],"autoregressive":[53,75,105,140],"model":[56],"for":[57,190],"VLN.":[59],"Unlike":[60],"full-sequence":[61],"video-generation":[62],"models":[64],"generate":[66],"an":[67],"entire":[68],"visual":[69],"clip,":[70],"WorldVLN":[71,157,185],"adapts":[72],"video":[76,122],"backbone":[77],"predict":[79],"short-horizon":[80],"world-state":[81],"transitions":[82],"directly":[84],"decodes":[85],"them":[86],"into":[87,103],"executable":[88],"waypoint":[89,144],"actions.":[90],"After":[91],"each":[92],"segment":[94],"is":[95],"executed,":[96],"newly":[97],"received":[98],"observations":[99],"are":[100,197],"encoded":[101],"back":[102],"context,":[106],"enabling":[107],"prediction.":[110],"further":[112,174],"introduce":[113],"two-stage":[115],"training":[116],"framework":[117],"grounds":[120],"prior":[123],"instruction-conditioned":[125],"dynamics":[127],"then":[129],"develops":[130],"Action-aware":[131],"GRPO,":[132],"reinforcement":[135],"learning":[136],"method":[137],"tailored":[138],"WAMs,":[141],"optimize":[143],"decisions":[145],"their":[147],"downstream":[148],"rollout":[149],"On":[151],"public":[152],"outdoor":[153],"indoor":[155],"benchmarks,":[156],"consistently":[158],"outperforms":[159],"existing":[160],"Vision-Language-Action":[161],"baselines":[162],"with":[163],"12\\%+":[164],"success-rate":[165],"gains":[166],"larger":[168],"advantages":[169],"on":[170],"challenging":[171],"cases.":[172],"It":[173],"transfers":[175],"zero-shot":[176],"real":[178],"drone":[179],"deployment,":[180],"suggesting":[181],"proposed":[184],"offers":[186],"promising":[188],"route":[189],"spatial":[191],"tasks.":[193],"Demos":[194],"code":[196],"available":[198],"at":[199],"https://embodiedcity.github.io/WorldVLN/.":[200]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-19T00:00:00"}