{"id":"https://openalex.org/W7140588253","doi":"https://doi.org/10.48550/arxiv.2603.23523","title":"Do 3D Large Language Models Really Understand 3D Spatial Relationships?","display_name":"Do 3D Large Language Models Really Understand 3D Spatial Relationships?","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W7140588253","doi":"https://doi.org/10.48550/arxiv.2603.23523"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.23523","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23523","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":"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.2603.23523","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5003807275","display_name":"Xianzheng Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Xianzheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130685322","display_name":"Tao Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Tao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130689802","display_name":"Shuai Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Shuai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058048083","display_name":"Yash Bhalgat","orcid":"https://orcid.org/0000-0001-7775-6250"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bhalgat, Yash","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130639747","display_name":"Jindong Gu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Jindong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103619575","display_name":"Angel Xuan Chang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chang, Angel X","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014426007","display_name":"Iro Armeni","orcid":"https://orcid.org/0000-0002-4230-5916"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Armeni, Iro","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062808708","display_name":"Iro Laina","orcid":"https://orcid.org/0000-0001-8857-7709"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Laina, Iro","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104001613","display_name":"Songyou Peng","orcid":"https://orcid.org/0009-0007-6085-8059"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng, Songyou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5067395390","display_name":"Victor Adrian Prisacariu","orcid":"https://orcid.org/0000-0002-0630-6129"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Prisacariu, Victor Adrian","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":0.9156000018119812,"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":0.9156000018119812,"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/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.016300000250339508,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11904","display_name":"Spatial Cognition and Navigation","score":0.009399999864399433,"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/benchmark","display_name":"Benchmark (surveying)","score":0.7936999797821045},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6516000032424927},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4756999909877777},{"id":"https://openalex.org/keywords/visual-reasoning","display_name":"Visual reasoning","score":0.4341999888420105},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.3978999853134155},{"id":"https://openalex.org/keywords/taxonomy","display_name":"Taxonomy (biology)","score":0.37959998846054077}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7936999797821045},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.758400022983551},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6516000032424927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5849999785423279},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4855000078678131},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4756999909877777},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.4341999888420105},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.3978999853134155},{"id":"https://openalex.org/C58642233","wikidata":"https://www.wikidata.org/wiki/Q8269924","display_name":"Taxonomy (biology)","level":2,"score":0.37959998846054077},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3456000089645386},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3377000093460083},{"id":"https://openalex.org/C2983448237","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Language understanding","level":2,"score":0.2937000095844269},{"id":"https://openalex.org/C155911833","wikidata":"https://www.wikidata.org/wiki/Q3817354","display_name":"Spatial intelligence","level":2,"score":0.2904999852180481},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C3019007443","wikidata":"https://www.wikidata.org/wiki/Q568742","display_name":"3d model","level":2,"score":0.2703999876976013}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.23523","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23523","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":"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.2603.23523","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23523","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":"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":[{"id":"https://metadata.un.org/sdg/4","score":0.8040966391563416,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recent":[0],"3D":[1,8,43,96,128,154],"Large-Language":[2],"Models":[3],"(3D-LLMs)":[4],"claim":[5],"to":[6,55,91,124,151],"understand":[7],"worlds,":[9],"especially":[10],"spatial":[11,107,136],"relationships":[12,108],"among":[13],"objects.":[14],"Yet,":[15],"we":[16,73],"find":[17],"that":[18,47,81,102,121],"simply":[19],"fine-tuning":[20],"a":[21,76,88,117],"language":[22],"model":[23,59,123],"on":[24,36,99,127],"text-only":[25],"question-answer":[26],"pairs":[27],"can":[28],"perform":[29],"comparably":[30],"or":[31],"even":[32],"surpass":[33],"these":[34],"methods":[35],"the":[37,48,58,142],"SQA3D":[38,49],"benchmark":[39,50,80],"without":[40],"using":[41],"any":[42],"input.":[44],"This":[45],"indicates":[46],"may":[51],"not":[52],"be":[53],"able":[54],"detect":[56],"if":[57],"exploits":[60],"textual":[61],"shortcuts":[62],"rather":[63],"than":[64],"engages":[65],"in":[66,135],"3D-aware":[67],"reasoning.":[68,97],"To":[69],"address":[70],"this":[71],"issue,":[72],"introduce":[74],"Real-3DQA,":[75],"more":[77,126],"rigorous":[78],"evaluation":[79],"filters":[82],"out":[83],"easy-to-guess":[84],"questions":[85],"and":[86,147],"introduces":[87],"structured":[89],"taxonomy":[90],"assess":[92],"various":[93],"aspects":[94],"of":[95],"Experiments":[98],"Real-3DQA":[100],"confirm":[101],"existing":[103],"3D-LLMs":[104,133],"struggle":[105],"with":[106],"once":[109],"simple":[110],"cues":[111],"are":[112],"removed.":[113],"We":[114],"further":[115],"propose":[116],"3D-reweighted":[118],"training":[119,149],"objective":[120],"guides":[122],"rely":[125],"visual":[129],"clues,":[130],"substantially":[131],"enhancing":[132],"performance":[134],"reasoning":[137],"tasks.":[138],"Our":[139],"findings":[140],"underscore":[141],"need":[143],"for":[144],"robust":[145],"benchmarks":[146],"tailored":[148],"strategies":[150],"advance":[152],"genuine":[153],"vision-language":[155],"understanding.":[156],"Project":[157],"page:":[158],"https://real-3dqa.github.io/.":[159]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-27T00:00:00"}