{"id":"https://openalex.org/W7163211552","doi":"https://doi.org/10.48550/arxiv.2606.00318","title":"Belief Consistency Between Foundation-Model Evidence and Geometric Perception in Persistent Robotic Maps","display_name":"Belief Consistency Between Foundation-Model Evidence and Geometric Perception in Persistent Robotic Maps","publication_year":2026,"publication_date":"2026-05-29","ids":{"openalex":"https://openalex.org/W7163211552","doi":"https://doi.org/10.48550/arxiv.2606.00318"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.00318","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.00318","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":null,"license_id":null,"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.2606.00318","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135337339","display_name":"Christoffer Heckman","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Heckman, Christoffer","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031951235","display_name":"Harel Biggie","orcid":"https://orcid.org/0000-0002-6281-1218"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Biggie, Harel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5094196383","display_name":"Brendan Crowe","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Crowe, Brendan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137658871","display_name":"Nicholas Roy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Roy, Nicholas","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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.38989999890327454,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.38989999890327454,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T12536","display_name":"Topological and Geometric Data Analysis","score":0.07190000265836716,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.05530000105500221,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/commit","display_name":"Commit","score":0.7408000230789185},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.47780001163482666},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.45899999141693115},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.37700000405311584},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.36000001430511475},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.35830000042915344},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.3504999876022339},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.3271999955177307}],"concepts":[{"id":"https://openalex.org/C153180980","wikidata":"https://www.wikidata.org/wiki/Q19776675","display_name":"Commit","level":2,"score":0.7408000230789185},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5353000164031982},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5058000087738037},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.47780001163482666},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.45899999141693115},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4512999951839447},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.37700000405311584},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.36000001430511475},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.35830000042915344},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.3504999876022339},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.3271999955177307},{"id":"https://openalex.org/C104065381","wikidata":"https://www.wikidata.org/wiki/Q1002535","display_name":"Geometric modeling","level":2,"score":0.3107999861240387},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30300000309944153},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2948000133037567},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.2946000099182129},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.28040000796318054},{"id":"https://openalex.org/C39947850","wikidata":"https://www.wikidata.org/wiki/Q729523","display_name":"Geometric distribution","level":3,"score":0.2775999903678894},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.27570000290870667},{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.2556999921798706},{"id":"https://openalex.org/C201729545","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability theory","level":3,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.00318","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.00318","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.00318","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.00318","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.5366708040237427,"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":{"Persistent":[0],"maps":[1,141],"used":[2],"by":[3,38,99],"autonomous":[4],"robots":[5],"increasingly":[6],"fuse":[7],"a":[8,17,48,70,82,88,169],"geometric":[9,101,118,185],"perception":[10],"stack":[11],"whose":[12],"assertions":[13],"are":[14],"well-characterized":[15],"with":[16,78,115],"foundation-model":[18,41,96,191],"channel":[19,42,102,119],"that":[20,92],"produces":[21,136],"semantic":[22,127],"claims":[23,97],"without":[24,58],"calibrated":[25,84],"reliability":[26,56],"about":[27],"the":[28,35,40,63,100,104,107,151],"same":[29],"scene.":[30],"Contemporary":[31],"mapping":[32],"systems":[33],"integrate":[34],"two":[36,64,79],"channels":[37,65],"treating":[39],"as":[43],"an":[44,75,116,124],"additional":[45],"voter":[46],"into":[47],"per-element":[49],"posterior,":[50],"uncalibrated":[51],"for":[52,150],"its":[53],"own":[54],"per-class":[55,83,155],"and":[57,87,113,123,183,187],"machinery":[59],"to":[60,94,130],"flag":[61],"when":[62],"contradict":[66],"each":[67],"other":[68],"at":[69,103,165,177],"given":[71],"moment.":[72],"We":[73,109],"propose":[74],"update":[76],"operator":[77,135],"cooperating":[80],"mechanisms:":[81],"commit":[85,95,145],"gate,":[86],"per-event":[89],"conflict-drop":[90],"window":[91],"refuses":[93],"contradicted":[98],"moment":[105],"of":[106],"claim.":[108],"evaluate":[110],"on":[111],"KITTI-360":[112],"ScanNet,":[114],"oracle":[117,182],"(panoptic":[120],"ground":[121],"truth)":[122],"off-the-shelf":[125],"online":[126],"segmenter":[128],"(Mask2Former)":[129],"demonstrate":[131],"real-world":[132],"performance.":[133],"The":[134,174],"substantially":[137],"more":[138,161],"accurate":[139],"committed":[140],"(KITTI":[142],"is":[143,188],"car":[144],"precision":[146,167],"99.7%":[147],"vs.":[148,158],"43.9%":[149],"calibration-only":[152],"operator;":[153],"mean":[154],"IoU":[156],"0.522":[157],"0.180),":[159],"retains":[160],"compositional":[162,171],"true":[163],"positives":[164],"higher":[166],"than":[168],"monolithic":[170],"VLM":[172],"prompt.":[173],"framework":[175],"operates":[176],"deployment":[178],"quality":[179],"across":[180],"both":[181],"off-the-shelf-segmenter":[184],"channels,":[186],"invariant":[189],"under":[190],"substitution.":[192]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-03T00:00:00"}