{"id":"https://openalex.org/W7138012611","doi":"https://doi.org/10.48550/arxiv.2603.14497","title":"WorldVLM: Combining World Model Forecasting and Vision-Language Reasoning","display_name":"WorldVLM: Combining World Model Forecasting and Vision-Language Reasoning","publication_year":2026,"publication_date":"2026-03-15","ids":{"openalex":"https://openalex.org/W7138012611","doi":"https://doi.org/10.48550/arxiv.2603.14497"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.14497","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.14497","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.14497","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129682604","display_name":"Stefan Englmeier","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Englmeier, Stefan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129655038","display_name":"Katharina Winter","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Winter, Katharina","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129678565","display_name":"Fabian B. Flohr","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Flohr, Fabian B.","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5129682604"],"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":0.8492000102996826,"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":0.8492000102996826,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.024399999529123306,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.009600000455975533,"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/leverage","display_name":"Leverage (statistics)","score":0.7885000109672546},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5152000188827515},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4959000051021576},{"id":"https://openalex.org/keywords/comprehension","display_name":"Comprehension","score":0.4041000008583069},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.36629998683929443},{"id":"https://openalex.org/keywords/system-dynamics","display_name":"System dynamics","score":0.32850000262260437},{"id":"https://openalex.org/keywords/dynamics","display_name":"Dynamics (music)","score":0.29829999804496765}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7885000109672546},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.682699978351593},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6255999803543091},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5152000188827515},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4984999895095825},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4959000051021576},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.4041000008583069},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.36629998683929443},{"id":"https://openalex.org/C77405623","wikidata":"https://www.wikidata.org/wiki/Q598451","display_name":"System dynamics","level":2,"score":0.32850000262260437},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.29829999804496765},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C13687954","wikidata":"https://www.wikidata.org/wiki/Q4826847","display_name":"Autonomous agent","level":2,"score":0.26660001277923584},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C202033279","wikidata":"https://www.wikidata.org/wiki/Q1931373","display_name":"Scenario planning","level":2,"score":0.2551000118255615}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.14497","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.14497","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.14497","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.14497","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":"article"},"sustainable_development_goals":[{"score":0.4252920150756836,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Autonomous":[0],"driving":[1,54,131],"systems":[2],"depend":[3],"on":[4,5],"models":[6,74],"that":[7,114],"can":[8],"reason":[9],"about":[10],"high-level":[11,123],"scene":[12,36,65],"contexts":[13],"and":[14,35,72,106,117,135,142],"accurately":[15],"predict":[16,63],"the":[17,88,99,122,130,146],"dynamics":[18,61],"of":[19,102],"their":[20,45,50],"surrounding":[21],"environment.":[22],"Vision-":[23],"Language":[24],"Models":[25,57],"(VLMs)":[26],"have":[27],"recently":[28],"emerged":[29],"as":[30,52,69],"promising":[31,81],"tools":[32],"for":[33,75,83],"decision-making":[34],"understanding,":[37],"offering":[38],"strong":[39],"capabilities":[40],"in":[41,87],"contextual":[42],"reasoning.":[43],"However,":[44],"limited":[46],"spatial":[47],"comprehension":[48],"constrains":[49],"effectiveness":[51],"end-to-end":[53],"models.":[55],"World":[56],"(WM)":[58],"internalize":[59],"environmental":[60],"to":[62,128],"future":[64],"evolution.":[66],"Recently":[67],"explored":[68],"ego-motion":[70],"predictors":[71],"foundation":[73],"autonomous":[76],"driving,":[77],"they":[78],"represent":[79],"a":[80],"direction":[82],"addressing":[84],"key":[85],"challenges":[86],"field,":[89],"particularly":[90],"enhancing":[91],"generalization":[92],"while":[93],"maintaining":[94],"dynamic":[95],"prediction.":[96],"To":[97],"leverage":[98],"complementary":[100],"strengths":[101],"context-based":[103],"decision":[104],"making":[105],"prediction,":[107],"we":[108],"propose":[109],"WorldVLM:":[110],"A":[111],"hybrid":[112,147],"architecture":[113],"unifies":[115],"VLMs":[116],"WMs.":[118],"In":[119],"our":[120],"design,":[121],"VLM":[124],"generates":[125],"behavior":[126],"commands":[127],"guide":[129],"WM,":[132],"enabling":[133],"interpretable":[134],"context-aware":[136],"actions.":[137],"We":[138],"evaluate":[139],"conditioning":[140],"strategies":[141],"provide":[143],"insights":[144],"into":[145],"design":[148],"challenges.":[149]},"counts_by_year":[],"updated_date":"2026-03-18T06:31:55.123368","created_date":"2026-03-18T00:00:00"}
