{"id":"https://openalex.org/W7165171067","doi":"https://doi.org/10.48550/arxiv.2606.18610","title":"SC3-Eval: Evaluating Robot Foundation Models via Self-Consistent Video Generation","display_name":"SC3-Eval: Evaluating Robot Foundation Models via Self-Consistent Video Generation","publication_year":2026,"publication_date":"2026-06-17","ids":{"openalex":"https://openalex.org/W7165171067","doi":"https://doi.org/10.48550/arxiv.2606.18610"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.18610","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.18610","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.2606.18610","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138863039","display_name":"Wei-Cheng Tseng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tseng, Wei-Cheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138961249","display_name":"Gashon Hussein","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hussein, Gashon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136466952","display_name":"Y H Dong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong, Yuzhu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138844550","display_name":"Allen Z. Ren","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ren, Allen Z.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054418497","display_name":"Lu Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Lucy X.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138961512","display_name":"XuDong Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, XuDong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138904134","display_name":"Sergey Levine","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Levine, Sergey","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138883844","display_name":"Zhaoshuo Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Zhaoshuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138919318","display_name":"Jinwei Gu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Jinwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010648258","display_name":"Florian Shkurti","orcid":"https://orcid.org/0000-0002-5672-5831"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shkurti, Florian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035887801","display_name":"M Y Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Ming-Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138914526","display_name":"Quan Vuong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vuong, Quan","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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.26440000534057617,"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"}},"topics":[{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.26440000534057617,"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"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.149399995803833,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.1298000067472458,"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/consistency","display_name":"Consistency (knowledge bases)","score":0.5697000026702881},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.47380000352859497},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.4212999939918518},{"id":"https://openalex.org/keywords/train","display_name":"Train","score":0.40860000252723694},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.353300005197525},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.33399999141693115},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.31869998574256897},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.3093000054359436}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7851999998092651},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5697000026702881},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48089998960494995},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.47380000352859497},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4212999939918518},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.40860000252723694},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.353300005197525},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3425000011920929},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.33399999141693115},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.31869998574256897},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3140999972820282},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3093000054359436},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.3086000084877014},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.30649998784065247},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.30489999055862427},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.30480000376701355},{"id":"https://openalex.org/C2776449333","wikidata":"https://www.wikidata.org/wiki/Q7928781","display_name":"View synthesis","level":3,"score":0.3000999987125397},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27160000801086426},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C161759796","wikidata":"https://www.wikidata.org/wiki/Q3982902","display_name":"Teleoperation","level":3,"score":0.26350000500679016},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.2614000141620636},{"id":"https://openalex.org/C17305859","wikidata":"https://www.wikidata.org/wiki/Q382944","display_name":"Soar","level":2,"score":0.25760000944137573}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.18610","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.18610","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.2606.18610","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.18610","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":[{"score":0.7095483541488647,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Evaluating":[0],"generalist":[1],"robot":[2],"manipulation":[3],"policies":[4,48,187],"in":[5,189],"the":[6,43,53,92,116,127,135,138,154,174,183],"real":[7],"world":[8,18],"is":[9],"expensive,":[10],"slow,":[11],"and":[12,42,99,114,214,224],"difficult":[13],"to":[14,47,94,100,108,129,226],"scale.":[15],"Action-conditioned":[16],"video":[17,64,71],"models":[19],"offer":[20],"a":[21,62,69,109,118,161,208],"scalable":[22],"alternative":[23],"by":[24,79],"simulating":[25],"policy":[26,77],"rollouts.":[27],"Autoregressive":[28],"rollouts":[29,107,144,167,181],"accumulate":[30],"compounding":[31],"errors,":[32],"observations":[33],"across":[34],"multiple":[35],"camera":[36,132],"views":[37],"must":[38,45],"remain":[39],"mutually":[40],"consistent,":[41],"evaluator":[44,78],"generalize":[46],"whose":[49,168],"behaviors":[50],"lie":[51],"outside":[52],"training":[54],"distribution.":[55],"We":[56,177],"address":[57],"these":[58],"challenges":[59],"with":[60],"SC3-Eval,":[61],"self-consistent":[63],"generation":[65],"recipe":[66],"that":[67,165,186],"adapts":[68],"pre-trained":[70],"foundation":[72],"model":[73,93,120,128],"into":[74],"an":[75],"accurate":[76],"enforcing":[80],"three":[81,219],"complementary":[82],"forms":[83],"of":[84,212,216],"consistency.":[85],"First,":[86],"forward-inverse":[87],"dynamics":[88,156],"consistency":[89,125,152],"jointly":[90],"trains":[91,126],"predict":[95],"frames":[96,170],"from":[97,103,134,173],"actions":[98,102],"recover":[101],"frames,":[104],"anchoring":[105],"generated":[106,169],"physically":[110],"plausible":[111],"action":[112],"manifold":[113],"counteracting":[115],"drift":[117,171],"forward-only":[119],"cannot":[121],"penalize.":[122],"Second,":[123],"cross-view":[124],"inpaint":[130],"each":[131],"view":[133],"other,":[136],"keeping":[137],"multi-camera":[139],"observation":[140],"coherent":[141],"over":[142],"long":[143],"without":[145],"any":[146],"explicit":[147],"memory":[148],"mechanism.":[149],"Third,":[150],"test-time":[151],"reuses":[153],"inverse":[155],"mode":[157],"at":[158],"inference":[159],"as":[160],"per-action-chunk":[162],"uncertainty":[163],"signal":[164],"terminates":[166],"away":[172],"requested":[175],"actions.":[176],"also":[178],"demonstrate":[179],"SC3-Eval":[180,206],"reproduce":[182],"failure":[184],"modes":[185],"exhibit":[188],"real-world":[190,203],"rollouts,":[191],"supporting":[192],"fine-grained":[193],"diagnostic":[194],"comparison":[195],"rather":[196],"than":[197],"aggregate":[198],"ranking":[199],"alone.":[200],"Across":[201],"seven":[202],"vision-language-action":[204],"policies,":[205],"attains":[207],"closed-loop":[209],"Pearson":[210],"correlation":[211],"$0.929$":[213],"MMRV":[215],"$0.119$,":[217],"outperforming":[218],"strong":[220],"prior":[221],"video-model-based":[222],"baselines,":[223],"generalizes":[225],"new":[227],"tasks.":[228]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-19T00:00:00"}