{"id":"https://openalex.org/W7155090053","doi":"https://doi.org/10.48550/arxiv.2604.16993","title":"Rule-VLN: Bridging Perception and Compliance via Semantic Reasoning and Geometric Rectification","display_name":"Rule-VLN: Bridging Perception and Compliance via Semantic Reasoning and Geometric Rectification","publication_year":2026,"publication_date":"2026-04-18","ids":{"openalex":"https://openalex.org/W7155090053","doi":"https://doi.org/10.48550/arxiv.2604.16993"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.16993","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16993","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.16993","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134206174","display_name":"Jiawen Wen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wen, Jiawen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114594168","display_name":"Penglei Sun","orcid":"https://orcid.org/0009-0005-2290-0944"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Penglei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134211354","display_name":"Wenjie Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Wenjie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022201556","display_name":"Suixuan Qiu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiu, Suixuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134136446","display_name":"Weisheng Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Weisheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134171439","display_name":"Xiaofei Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Xiaofei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134101384","display_name":"Xiaowen Chu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chu, Xiaowen","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":0.89410001039505,"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":0.89410001039505,"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":0.022600000724196434,"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/T10914","display_name":"Tactile and Sensory Interactions","score":0.013500000350177288,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.7414000034332275},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.6144000291824341},{"id":"https://openalex.org/keywords/embodied-cognition","display_name":"Embodied cognition","score":0.5807999968528748},{"id":"https://openalex.org/keywords/rectification","display_name":"Rectification","score":0.5462999939918518},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.5170999765396118},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5112000107765198},{"id":"https://openalex.org/keywords/visual-reasoning","display_name":"Visual reasoning","score":0.4887000024318695},{"id":"https://openalex.org/keywords/active-perception","display_name":"Active perception","score":0.45179998874664307},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.44839999079704285}],"concepts":[{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.7414000034332275},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.6144000291824341},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.613099992275238},{"id":"https://openalex.org/C100609095","wikidata":"https://www.wikidata.org/wiki/Q1335050","display_name":"Embodied cognition","level":2,"score":0.5807999968528748},{"id":"https://openalex.org/C50942859","wikidata":"https://www.wikidata.org/wiki/Q4967193","display_name":"Rectification","level":3,"score":0.5462999939918518},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.5170999765396118},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5112000107765198},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5067999958992004},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.4887000024318695},{"id":"https://openalex.org/C2776010242","wikidata":"https://www.wikidata.org/wiki/Q4677575","display_name":"Active perception","level":3,"score":0.45179998874664307},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.44839999079704285},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4422999918460846},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.38449999690055847},{"id":"https://openalex.org/C198942812","wikidata":"https://www.wikidata.org/wiki/Q496618","display_name":"Semantic property","level":2,"score":0.37630000710487366},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3695000112056732},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.35850000381469727},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.3580000102519989},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3546999990940094},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.32580000162124634},{"id":"https://openalex.org/C136643341","wikidata":"https://www.wikidata.org/wiki/Q1361526","display_name":"Reachability","level":2,"score":0.32260000705718994},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.3127000033855438},{"id":"https://openalex.org/C115086926","wikidata":"https://www.wikidata.org/wiki/Q17004651","display_name":"Causal reasoning","level":3,"score":0.2883000075817108},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C2778493491","wikidata":"https://www.wikidata.org/wiki/Q7449072","display_name":"Semantic matching","level":3,"score":0.27059999108314514},{"id":"https://openalex.org/C2781460075","wikidata":"https://www.wikidata.org/wiki/Q1399332","display_name":"Compliance (psychology)","level":2,"score":0.26989999413490295},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2628999948501587},{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C86034646","wikidata":"https://www.wikidata.org/wiki/Q474311","display_name":"Semantic gap","level":4,"score":0.2572000026702881},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.2533000111579895}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.16993","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16993","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":"doi:10.48550/arxiv.2604.16993","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16993","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":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.7158979177474976}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"As":[0],"embodied":[1],"AI":[2],"transitions":[3],"to":[4,16,21,105],"real-world":[5],"deployment,":[6],"the":[7,10,56,94],"success":[8],"of":[9],"Vision-and-Language":[11],"Navigation":[12,96],"(VLN)":[13],"task":[14],"tends":[15],"evolve":[17],"from":[18,28],"mere":[19],"reachability":[20],"social":[22],"compliance.":[23],"However,":[24],"current":[25],"agents":[26,84,108],"suffer":[27],"a":[29,65,100,114],"\"goal-driven":[30],"trap\",":[31],"prioritizing":[32],"physical":[33],"geometry":[34],"(\"can":[35],"I":[36,42],"go?\")":[37],"over":[38],"semantic":[39],"rules":[40],"(\"may":[41],"go?\"),":[43],"frequently":[44],"overlooking":[45],"subtle":[46],"regulatory":[47,73],"constraints.":[48,90],"To":[49],"bridge":[50],"this":[51],"gap,":[52],"we":[53],"establish":[54],"Rule-VLN,":[55],"first":[57],"large-scale":[58],"urban":[59],"benchmark":[60],"for":[61,125],"rule-compliant":[62],"navigation.":[63],"Spanning":[64],"massive":[66],"29k-node":[67],"environment,":[68],"it":[69],"injects":[70],"177":[71],"diverse":[72],"categories":[74],"into":[75],"8k":[76],"constrained":[77],"nodes":[78],"across":[79],"four":[80],"curriculum":[81],"levels,":[82],"challenging":[83],"with":[85,109,120],"fine-grained":[86],"visual":[87,116],"and":[88,146],"behavioral":[89],"We":[91],"further":[92],"propose":[93],"Semantic":[95],"Rectification":[97],"Module":[98],"(SNRM),":[99],"universal,":[101],"zero-shot":[102],"module":[103],"designed":[104],"equip":[106],"pre-trained":[107],"safety":[110],"awareness.":[111],"SNRM":[112,137],"integrates":[113],"coarse-to-fine":[115],"perception":[117],"VLM":[118],"framework":[119],"an":[121],"epistemic":[122],"mental":[123],"map":[124],"dynamic":[126],"detour":[127],"planning.":[128],"Experiments":[129],"demonstrate":[130],"that":[131],"while":[132],"Rule-VLN":[133],"challenges":[134],"state-of-the-art":[135],"models,":[136],"significantly":[138],"restores":[139],"navigation":[140],"capabilities,":[141],"reducing":[142],"CVR":[143],"by":[144,149],"19.26%":[145],"boosting":[147],"TC":[148],"5.97%.":[150]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-22T00:00:00"}