{"id":"https://openalex.org/W7169016802","doi":"https://doi.org/10.48550/arxiv.2607.13681","title":"Towards Spatial Supersensing in the Wild","display_name":"Towards Spatial Supersensing in the Wild","publication_year":2026,"publication_date":"2026-07-15","ids":{"openalex":"https://openalex.org/W7169016802","doi":"https://doi.org/10.48550/arxiv.2607.13681"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.13681","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.13681","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2607.13681","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113222156","display_name":"Tianjun Gu","orcid":"https://orcid.org/0009-0001-4757-2685"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Tianjun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135982055","display_name":"Tianyu Xin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xin, Tianyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065782115","display_name":"K Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Kuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122931632","display_name":"B Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Bowen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140977994","display_name":"Kok-Chung Chua","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chua, Kok-Chung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140987627","display_name":"Peize Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Peize","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140977607","display_name":"Xinran Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xinran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5141045271","display_name":"Yupeng Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yupeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140988498","display_name":"Qiyue Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Qiyue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5141010758","display_name":"Qinlei Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Qinlei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089167445","display_name":"J. Y. Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Jianhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085698173","display_name":"Ye Lu","orcid":"https://orcid.org/0000-0002-2376-4519"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Yucheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101188116","display_name":"Yinan Han","orcid":"https://orcid.org/0000-0002-8400-5057"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Yinan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140968632","display_name":"Marco Pavone","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pavone, Marco","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5141017568","display_name":"Yiming Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yiming","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":0.913100004196167,"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":0.913100004196167,"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/T10709","display_name":"Social Robot Interaction and HRI","score":0.023000000044703484,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.006800000090152025,"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/benchmark","display_name":"Benchmark (surveying)","score":0.5151000022888184},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.47760000824928284},{"id":"https://openalex.org/keywords/spatial-cognition","display_name":"Spatial cognition","score":0.3903000056743622},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.3709000051021576},{"id":"https://openalex.org/keywords/unified-model","display_name":"Unified Model","score":0.3377000093460083},{"id":"https://openalex.org/keywords/computational-model","display_name":"Computational model","score":0.33169999718666077}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6685000061988831},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5655999779701233},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5151000022888184},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.47760000824928284},{"id":"https://openalex.org/C2777371692","wikidata":"https://www.wikidata.org/wiki/Q2178611","display_name":"Spatial cognition","level":3,"score":0.3903000056743622},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.3709000051021576},{"id":"https://openalex.org/C45493050","wikidata":"https://www.wikidata.org/wiki/Q7884934","display_name":"Unified Model","level":2,"score":0.3377000093460083},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.33169999718666077},{"id":"https://openalex.org/C155911833","wikidata":"https://www.wikidata.org/wiki/Q3817354","display_name":"Spatial intelligence","level":2,"score":0.31859999895095825},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30730000138282776},{"id":"https://openalex.org/C58642233","wikidata":"https://www.wikidata.org/wiki/Q8269924","display_name":"Taxonomy (biology)","level":2,"score":0.2946000099182129},{"id":"https://openalex.org/C96522737","wikidata":"https://www.wikidata.org/wiki/Q17148345","display_name":"Path integration","level":2,"score":0.2944999933242798},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2547999918460846},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.2535000145435333}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.13681","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.13681","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2607.13681","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.13681","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Humans":[0],"can":[1],"efficiently":[2],"parse":[3],"continuous":[4],"sensory":[5],"streams,":[6],"from":[7,130],"hours":[8],"to":[9,31,58,201],"years,":[10],"scaffolding":[11],"an":[12],"internal":[13],"world":[14,38,106,211],"model":[15],"that":[16,162,197,216],"grounds":[17],"spatial":[18,26,79,185,210,222],"reasoning":[19],"and":[20,54,64,114,118,177,180,191,205],"prediction.":[21],"To":[22,67],"mimic":[23],"this":[24],"capacity,":[25],"supersensing":[27,80],"challenges":[28],"multimodal":[29],"models":[30,157,198],"move":[32],"beyond":[33],"linguistic":[34],"understanding":[35],"toward":[36],"true":[37],"modeling.":[39],"However,":[40],"their":[41],"benchmark":[42,76],"relies":[43],"on":[44,94,145],"synthetic":[45],"long":[46,82],"videos,":[47],"formed":[48],"by":[49,91],"concatenating":[50],"random":[51],"short":[52],"clips,":[53],"is":[55],"mostly":[56],"limited":[57],"household":[59],"scenes,":[60],"leaving":[61],"real-world":[62,132],"continuity":[63],"diversity":[65],"underexplored.":[66],"address":[68],"the":[69,102,108,115,218],"gap,":[70],"we":[71,99],"introduce":[72],"$\\textbf{VSI-Super-Wild}$,":[73],"a":[74,148,208,213],"large-scale":[75],"for":[77,221],"evaluating":[78],"over":[81,167],"temporal":[83,178],"horizons":[84],"in":[85,153],"diverse":[86],"in-the-wild":[87],"scenes.":[88],"Notably,":[89],"inspired":[90],"cognitive":[92],"studies":[93],"how":[95,171],"humans":[96],"structure":[97],"experience,":[98],"systematically":[100],"probe":[101],"full":[103],"triad":[104],"of":[105],"state:":[107],"agent":[109],"(observer),":[110],"objects":[111],"(scene":[112],"items),":[113],"environment":[116],"(places":[117],"global":[119],"layout).":[120],"In":[121],"total,":[122],"VSI-Super-Wild":[123,146],"contains":[124],"$\\textbf{6,980}$":[125],"human-verified":[126],"question-answer":[127],"pairs":[128],"derived":[129],"$\\textbf{442}$":[131],"videos":[133],"spanning":[134],"8":[135],"scene":[136],"categories,":[137],"including":[138],"long-form":[139],"recordings":[140],"exceeding":[141],"4":[142],"hours.":[143],"Results":[144],"expose":[147],"fundamental":[149,214],"disconnect:":[150],"despite":[151],"advances":[152],"static":[154],"image":[155],"understanding,":[156],"consistently":[158],"fail":[159],"at":[160],"tasks":[161],"require":[163],"coherent":[164],"world-state":[165,175],"tracking":[166],"time.":[168],"We":[169],"characterize":[170],"performance":[172],"degrades":[173],"with":[174],"complexity":[176],"horizon,":[179],"diagnose":[181],"four":[182],"failure":[183],"modes:":[184],"collapse,":[186],"semantic":[187],"shortcuts,":[188],"insufficient":[189],"update,":[190],"instance":[192],"confusion.":[193],"This":[194],"taxonomy":[195],"reveals":[196],"lack":[199],"mechanisms":[200],"bind":[202],"objects,":[203],"agents,":[204],"environments":[206],"into":[207],"unified":[209],"model,":[212],"gap":[215],"defines":[217],"path":[219],"forward":[220],"supersensing.":[223]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-17T00:00:00"}
