{"id":"https://openalex.org/W7130730707","doi":"https://doi.org/10.48550/arxiv.2602.17659","title":"When Vision Overrides Language: Evaluating and Mitigating Counterfactual Failures in VLAs","display_name":"When Vision Overrides Language: Evaluating and Mitigating Counterfactual Failures in VLAs","publication_year":2026,"publication_date":"2026-02-19","ids":{"openalex":"https://openalex.org/W7130730707","doi":"https://doi.org/10.48550/arxiv.2602.17659"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.17659","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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/A5126470175","display_name":"Yu Fang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Fang, Yu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126487801","display_name":"Yuchun Feng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feng, Yuchun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Jing, Dong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jing, Dong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126508432","display_name":"Jiaqi Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Jiaqi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126446418","display_name":"Yue Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Yue","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028701570","display_name":"Zhenyu Wei","orcid":"https://orcid.org/0000-0001-5072-1883"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Zhenyu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Szafir, Daniel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Szafir, Daniel","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Ding, Mingyu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, Mingyu","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5126470175"],"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":0.8324999809265137,"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":0.8324999809265137,"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":0.02539999969303608,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.023800000548362732,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.9641000032424927},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7046999931335449},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5702000260353088},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5612000226974487},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5425000190734863},{"id":"https://openalex.org/keywords/defeasible-estate","display_name":"Defeasible estate","score":0.3822999894618988}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.9641000032424927},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7046999931335449},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6757000088691711},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5702000260353088},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5612000226974487},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5425000190734863},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.529699981212616},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5268999934196472},{"id":"https://openalex.org/C193856179","wikidata":"https://www.wikidata.org/wiki/Q5251100","display_name":"Defeasible estate","level":2,"score":0.3822999894618988},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.35659998655319214},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.3434999883174896},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.31040000915527344},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.30329999327659607},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.26919999718666077}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.17659","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.17659","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.17659","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":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.17659","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Vision-Language-Action":[0],"models":[1],"(VLAs)":[2],"promise":[3],"to":[4,16,156],"ground":[5],"language":[6,57,74,115,184],"instructions":[7,23,80],"in":[8,12,117,183,189],"robot":[9],"control,":[10],"yet":[11,94,107],"practice":[13],"often":[14],"fail":[15],"faithfully":[17],"follow":[18],"language.":[19],"When":[20],"presented":[21],"with":[22,125,199,209],"that":[24,72,89,112],"lack":[25],"strong":[26],"scene-specific":[27],"supervision,":[28],"VLAs":[29,71,170],"suffer":[30],"from":[31],"counterfactual":[32,68,90,132,218],"failures:":[33],"they":[34],"act":[35],"based":[36],"on":[37,141,146,176,192,228],"vision":[38],"shortcuts":[39],"induced":[40],"by":[41,77,181,226],"dataset":[42],"biases,":[43],"repeatedly":[44],"executing":[45],"well-learned":[46],"behaviors":[47],"and":[48,149,171,187,204,222],"selecting":[49],"objects":[50],"frequently":[51],"seen":[52],"during":[53,134],"training":[54],"regardless":[55],"of":[56,202,220],"intent.":[58],"To":[59],"systematically":[60],"study":[61],"it,":[62],"we":[63],"introduce":[64],"LIBERO-CF,":[65,177],"the":[66],"first":[67],"benchmark":[69],"for":[70],"evaluates":[73],"following":[75,185],"capability":[76],"assigning":[78],"alternative":[79],"under":[81],"visually":[82],"plausible":[83],"LIBERO":[84],"layouts.":[85],"Our":[86],"evaluation":[87],"reveals":[88],"failures":[91,219],"are":[92],"prevalent":[93],"underexplored":[95],"across":[96,168],"state-of-the-art":[97],"VLAs.":[98,118],"We":[99],"propose":[100],"Counterfactual":[101],"Action":[102],"Guidance":[103],"(CAG),":[104],"a":[105,121,126,196,210],"simple":[106],"effective":[108],"dual-branch":[109],"inference":[110],"scheme":[111],"explicitly":[113],"regularizes":[114],"conditioning":[116],"CAG":[119,178,216],"combines":[120],"standard":[122],"VLA":[123],"policy":[124],"language-unconditioned":[127],"Vision-Action":[128],"(VA)":[129],"module,":[130],"enabling":[131],"comparison":[133],"action":[135],"selection.":[136],"This":[137],"design":[138],"reduces":[139,217],"reliance":[140],"visual":[142],"shortcuts,":[143],"improves":[144,179,223],"robustness":[145],"under-observed":[147,193],"tasks,":[148],"requires":[150],"neither":[151],"additional":[152],"demonstrations":[153],"nor":[154],"modifications":[155],"existing":[157],"architectures":[158],"or":[159],"pretrained":[160],"models.":[161],"Extensive":[162],"experiments":[163],"demonstrate":[164],"its":[165],"plug-and-play":[166],"integration":[167],"diverse":[169],"consistent":[172],"improvements.":[173],"For":[174],"example,":[175],"$\u03c0_{0.5}$":[180],"9.7%":[182],"accuracy":[186],"3.6%":[188],"task":[190,224],"success":[191,225],"tasks":[194],"using":[195],"training-free":[197],"strategy,":[198],"further":[200],"gains":[201],"15.5%":[203],"8.5%,":[205],"respectively,":[206],"when":[207],"paired":[208],"VA":[211],"model.":[212],"In":[213],"real-world":[214],"evaluations,":[215],"9.4%":[221],"17.2%":[227],"average.":[229]},"counts_by_year":[],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2026-02-21T00:00:00"}
