{"id":"https://openalex.org/W7134283400","doi":"https://doi.org/10.48550/arxiv.2603.06576","title":"BEVLM: Distilling Semantic Knowledge from LLMs into Bird's-Eye View Representations","display_name":"BEVLM: Distilling Semantic Knowledge from LLMs into Bird's-Eye View Representations","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W7134283400","doi":"https://doi.org/10.48550/arxiv.2603.06576"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.06576","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","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":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068538358","display_name":"Thomas Monninger","orcid":"https://orcid.org/0000-0002-8318-5594"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Monninger, Thomas","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012852633","display_name":"Shaoyuan Xie","orcid":"https://orcid.org/0009-0008-1358-3010"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Shaoyuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063270515","display_name":"Qi Alfred Chen","orcid":"https://orcid.org/0000-0003-0316-9285"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Qi Alfred","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5042823691","display_name":"Sihao Ding","orcid":"https://orcid.org/0000-0003-1796-8504"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, Sihao","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5068538358"],"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":0.8823000192642212,"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":0.8823000192642212,"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":0.03519999980926514,"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":0.01679999940097332,"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/visual-reasoning","display_name":"Visual reasoning","score":0.5924000144004822},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.527400016784668},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.4948999881744385},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4684000015258789},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.453000009059906},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.4472000002861023},{"id":"https://openalex.org/keywords/knowledge-representation-and-reasoning","display_name":"Knowledge representation and reasoning","score":0.44670000672340393}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7307999730110168},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.5924000144004822},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5568000078201294},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.527400016784668},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.4948999881744385},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4684000015258789},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.45890000462532043},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.453000009059906},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.4472000002861023},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.44670000672340393},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.32499998807907104},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.29750001430511475},{"id":"https://openalex.org/C85407183","wikidata":"https://www.wikidata.org/wiki/Q1045785","display_name":"Semantic network","level":2,"score":0.29589998722076416},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.295199990272522},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.2750000059604645},{"id":"https://openalex.org/C197914299","wikidata":"https://www.wikidata.org/wiki/Q18650","display_name":"Semantic memory","level":3,"score":0.26750001311302185},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.26739999651908875},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.26570001244544983}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.06576","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.06576","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.06576","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":"pmh:doi:10.48550/arxiv.2603.06576","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7633901238441467,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"integration":[1],"of":[2,96],"Large":[3],"Language":[4],"Models":[5],"(LLMs)":[6],"into":[7,156],"autonomous":[8],"driving":[9,136,164],"has":[10],"attracted":[11],"growing":[12],"interest":[13],"for":[14,25],"their":[15],"strong":[16],"reasoning":[17,63],"and":[18,29,42,50,64,114],"semantic":[19,94,152],"understanding":[20],"abilities,":[21],"which":[22],"are":[23],"essential":[24],"handling":[26],"complex":[27],"decision-making":[28],"long-tail":[30],"scenarios.":[31,170],"However,":[32],"existing":[33],"methods":[34],"typically":[35],"feed":[36],"LLMs":[37,129,155],"with":[38,119],"tokens":[39],"from":[40,81,154],"multi-view":[41],"multi-frame":[43],"images":[44],"independently,":[45],"leading":[46],"to":[47,66,130],"redundant":[48],"computation":[49],"limited":[51],"spatial":[52,62,89],"consistency.":[53],"This":[54],"separation":[55],"in":[56,134,168],"visual":[57],"processing":[58],"hinders":[59],"accurate":[60],"3D":[61],"fails":[65],"maintain":[67],"geometric":[68],"coherence":[69],"across":[70],"views.":[71],"On":[72],"the":[73,93],"other":[74],"hand,":[75],"Bird's-Eye":[76],"View":[77],"(BEV)":[78],"representations":[79],"learned":[80],"geometrically":[82],"annotated":[83],"tasks":[84],"(e.g.,":[85],"object":[86],"detection)":[87],"provide":[88],"structure":[90],"but":[91],"lack":[92],"richness":[95],"foundation":[97],"vision":[98],"encoders.":[99],"To":[100],"bridge":[101],"this":[102],"gap,":[103],"we":[104,124],"propose":[105],"BEVLM,":[106],"a":[107,111],"framework":[108],"that":[109,126],"connects":[110],"spatially":[112],"consistent":[113],"semantically":[115],"distilled":[116],"BEV":[117,144,157],"representation":[118],"LLMs.":[120],"Through":[121],"extensive":[122],"experiments,":[123],"show":[125],"BEVLM":[127,159],"enables":[128],"reason":[131],"more":[132],"effectively":[133],"cross-view":[135],"scenes,":[137],"improving":[138],"accuracy":[139],"by":[140,142,150,166],"46%,":[141],"leveraging":[143],"features":[145],"as":[146],"unified":[147],"inputs.":[148],"Furthermore,":[149],"distilling":[151],"knowledge":[153],"representations,":[158],"significantly":[160],"improves":[161],"closed-loop":[162],"end-to-end":[163],"performance":[165],"29%":[167],"safety-critical":[169]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-03-10T00:00:00"}
