{"id":"https://openalex.org/W7153978741","doi":"https://doi.org/10.48550/arxiv.2604.09364","title":"Arbitration Failure, Not Perceptual Blindness: How Vision-Language Models Resolve Visual-Linguistic Conflicts","display_name":"Arbitration Failure, Not Perceptual Blindness: How Vision-Language Models Resolve Visual-Linguistic Conflicts","publication_year":2026,"publication_date":"2026-04-10","ids":{"openalex":"https://openalex.org/W7153978741","doi":"https://doi.org/10.48550/arxiv.2604.09364"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.09364","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09364","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.09364","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133485306","display_name":"Farhad Nooralahzadeh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nooralahzadeh, Farhad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059154016","display_name":"Omid Rohanian","orcid":"https://orcid.org/0000-0002-8771-8386"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rohanian, Omid","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100388128","display_name":"Yi Zhang","orcid":"https://orcid.org/0000-0002-2367-2497"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133474917","display_name":"Jonathan F\u00fcrst","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"F\u00fcrst, Jonathan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133508227","display_name":"Kurt Stockinger","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stockinger, Kurt","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"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":0.8974000215530396,"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":0.8974000215530396,"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/T10465","display_name":"Neurobiology of Language and Bilingualism","score":0.01080000028014183,"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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.009499999694526196,"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/interpretability","display_name":"Interpretability","score":0.7458000183105469},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5648000240325928},{"id":"https://openalex.org/keywords/causality","display_name":"Causality (physics)","score":0.46700000762939453},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4521999955177307},{"id":"https://openalex.org/keywords/tact","display_name":"Tact","score":0.43140000104904175},{"id":"https://openalex.org/keywords/logit","display_name":"Logit","score":0.41659998893737793},{"id":"https://openalex.org/keywords/causal-model","display_name":"Causal model","score":0.38659998774528503},{"id":"https://openalex.org/keywords/generality","display_name":"Generality","score":0.37450000643730164},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.36390000581741333}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7458000183105469},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.57669997215271},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5648000240325928},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.46700000762939453},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45840001106262207},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4521999955177307},{"id":"https://openalex.org/C2778833722","wikidata":"https://www.wikidata.org/wiki/Q28457372","display_name":"Tact","level":2,"score":0.43140000104904175},{"id":"https://openalex.org/C140331021","wikidata":"https://www.wikidata.org/wiki/Q1868104","display_name":"Logit","level":2,"score":0.41659998893737793},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.38659998774528503},{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.37450000643730164},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.36390000581741333},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.3619999885559082},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.35519999265670776},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.33399999141693115},{"id":"https://openalex.org/C610760","wikidata":"https://www.wikidata.org/wiki/Q1340706","display_name":"Endogeneity","level":2,"score":0.3174000084400177},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.30889999866485596},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.3061999976634979},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.2964000105857849},{"id":"https://openalex.org/C2776035688","wikidata":"https://www.wikidata.org/wiki/Q1606558","display_name":"Affect (linguistics)","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2930000126361847},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.2915000021457672},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2867000102996826},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.2842000126838684},{"id":"https://openalex.org/C29081049","wikidata":"https://www.wikidata.org/wiki/Q1364242","display_name":"Image stitching","level":2,"score":0.27720001339912415},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C189645446","wikidata":"https://www.wikidata.org/wiki/Q350865","display_name":"Mirroring","level":2,"score":0.267300009727478},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.26350000500679016},{"id":"https://openalex.org/C122507166","wikidata":"https://www.wikidata.org/wiki/Q628906","display_name":"Crossover","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C21308566","wikidata":"https://www.wikidata.org/wiki/Q7169365","display_name":"Permutation (music)","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.09364","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09364","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":"doi:10.48550/arxiv.2604.09364","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09364","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":"article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.6825698018074036}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"When":[0],"a":[1,6,45,133,264],"Vision-Language":[2],"Model":[3],"(VLM)":[4],"sees":[5],"blue":[7],"banana":[8],"and":[9,29,79,111,238],"answers":[10,145],"\"yellow\",":[11],"is":[12,274],"the":[13,21,50,59,75,115,118,123,157,181,206,216,272],"problem":[14],"of":[15,85,125,135,194,205],"perception":[16],"or":[17],"arbitration?":[18],"We":[19,88,160],"explore":[20],"question":[22],"in":[23,117,171,242,256],"ten":[24],"VLMs":[25,142,267],"with":[26,68,132,253],"various":[27],"sizes":[28],"reveal":[30],"an":[31],"Encoding-Grounding":[32],"Dissociation:":[33],"models":[34,56],"that":[35,57,90,199,231],"fail":[36],"to":[37,155,192,220,227,251,263,284],"report":[38],"what":[39,277],"they":[40,278],"see":[41,269],"(and":[42],"thus":[43],"provide":[44,58],"wrong":[46],"answer)":[47],"still":[48],"encode":[49],"visual":[51,78,91,247],"evidence":[52],"as":[53,55],"strongly":[54],"correct":[60],"answer.":[61],"Using":[62],"Multimodal":[63],"Arbitration":[64],"Crossover":[65],"(MAC)":[66],"analysis":[67],"layer-by-layer":[69],"Logit":[70],"Lens":[71],"probing,":[72],"we":[73,153,229],"track":[74],"competition":[76],"between":[77],"prior":[80,151],"signals":[81],"across":[82],"every":[83],"layer":[84],"each":[86],"model.":[87],"show":[89,230],"attributes":[92],"can":[93,245,282],"be":[94],"linearly":[95],"decodable":[96],"from":[97,225],"early":[98,243],"layers":[99,186,244],"(AUC":[100],">":[101],"0.86).":[102],"The":[103,167],"accuracy":[104],"remains":[105],"nearly":[106],"identical":[107],"for":[108],"both":[109,236],"successful":[110],"failed":[112],"samples.":[113],"However,":[114],"gap":[116],"final-layer":[119],"logit":[120],"-":[121,127,235,241],"not":[122,175],"strength":[124],"encoding":[126],"better":[128],"predicts":[129],"grounding":[130,248],"outcomes":[131],"correlation":[134],"$\u03c1=$":[136],"0.847.":[137],"After":[138],"having":[139],"studied":[140],"when":[141],"base":[143],"their":[144],"on":[146,276],"image":[147,200],"clues":[148],"rather":[149],"than":[150],"knowledge,":[152],"want":[154],"understand":[156],"causal":[158,207],"relationships.":[159],"establish":[161],"causality":[162],"through":[163],"full-sequence":[164],"activation":[165,233],"patching.":[166],"standard":[168],"last-token":[169],"interventions":[170,281],"LLM":[172],"interpretability":[173],"do":[174],"affect":[176],"VLMs.":[177],"In":[178],"contrast,":[179],"replacing":[180],"full":[182],"token":[183],"sequence":[184],"at":[185],"identified":[187],"by":[188,249],"MAC":[189],"alters":[190],"60":[191],"84%":[193],"outputs.":[195],"Partial-token":[196],"decomposition":[197],"shows":[198],"tokens":[201,211],"carry":[202],"almost":[203],"all":[204],"impact,":[208],"while":[209],"text":[210],"have":[212],"none.":[213],"Scaling":[214],"addresses":[215],"remaining":[217],"architectural":[218],"differences":[219],"achieve":[221],"perfect":[222],"retention.":[223],"Moving":[224],"diagnosis":[226],"intervention,":[228],"training-free":[232],"steering":[234],"linear":[237],"sparse":[239],"autoencoder-guided":[240],"improve":[246],"up":[250],"+3.8%":[252],"degrading":[254],"performance":[255],"some":[257],"setups.":[258],"Overall,":[259],"these":[260],"findings":[261],"lead":[262],"clear":[265],"conclusion:":[266],"already":[268],"well,":[270],"but":[271],"challenge":[273],"acting":[275],"see.":[279],"Targeted":[280],"help":[283],"bridge":[285],"this":[286],"gap.":[287]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-14T00:00:00"}