{"id":"https://openalex.org/W7163145468","doi":"https://doi.org/10.48550/arxiv.2606.01710","title":"Density-Aware Translation of Spurious Correlations in Zero-Shot VLMs","display_name":"Density-Aware Translation of Spurious Correlations in Zero-Shot VLMs","publication_year":2026,"publication_date":"2026-06-01","ids":{"openalex":"https://openalex.org/W7163145468","doi":"https://doi.org/10.48550/arxiv.2606.01710"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.01710","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.01710","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.2606.01710","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5093346020","display_name":"Afsaneh Hasanebrahimi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hasanebrahimi, Afsaneh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049209023","display_name":"Hanxun Huang","orcid":"https://orcid.org/0000-0002-2793-6680"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Hanxun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133566538","display_name":"Christopher Leckie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Leckie, Christopher","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134297192","display_name":"Sarah Erfani","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Erfani, Sarah","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":0.5867999792098999,"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":0.5867999792098999,"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":0.11010000109672546,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.043800000101327896,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/spurious-relationship","display_name":"Spurious relationship","score":0.8845999836921692},{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.6632999777793884},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5968000292778015},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.579200029373169},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5515999794006348},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4970000088214874},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4943999946117401},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4772999882698059},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.36399999260902405},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.3580000102519989}],"concepts":[{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.8845999836921692},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.6632999777793884},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5968000292778015},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.579200029373169},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5515999794006348},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5472999811172485},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5450999736785889},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4970000088214874},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4943999946117401},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4772999882698059},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4016999900341034},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37220001220703125},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.36399999260902405},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.3580000102519989},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.3537999987602234},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.3450999855995178},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.3400999903678894},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.3395000100135803},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.3379000127315521},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.3237000107765198},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.31709998846054077},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.3075000047683716},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.29159998893737793},{"id":"https://openalex.org/C132459708","wikidata":"https://www.wikidata.org/wiki/Q744069","display_name":"Extrapolation","level":2,"score":0.2906999886035919},{"id":"https://openalex.org/C126691448","wikidata":"https://www.wikidata.org/wiki/Q2028919","display_name":"Magnitude (astronomy)","level":2,"score":0.2766000032424927},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.27140000462532043},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.2558000087738037},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.25459998846054077}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.01710","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.01710","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.2606.01710","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.01710","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":[{"score":0.6910956501960754,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"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":[0],"models":[1,41],"(VLMs),":[2],"such":[3],"as":[4,168],"CLIP,":[5],"achieve":[6],"powerful":[7],"zero-shot":[8,177],"classification.":[9],"However,":[10],"their":[11],"predictions":[12],"remain":[13],"sensitive":[14],"to":[15,45,133],"spurious":[16,113],"correlations,":[17],"where":[18,112],"contextual":[19],"cues":[20,122],"dominate":[21],"over":[22],"semantic":[23],"content.":[24],"Earlier":[25],"solutions":[26],"typically":[27],"rely":[28],"on":[29,87,137,154],"fine-tuning":[30],"or":[31,42],"prompt":[32],"engineering,":[33],"which":[34],"either":[35],"undermine":[36],"the":[37,76,92,99],"advantages":[38],"of":[39],"pre-trained":[40],"are":[43,104,115,123],"prone":[44],"hallucination.":[46],"In":[47],"this":[48],"work,":[49],"we":[50,128],"propose":[51],"Density-Aware":[52],"Translation":[53],"(DAT)":[54],"that":[55,78],"refines":[56],"image-text":[57],"similarity":[58],"scores":[59,142],"using":[60,179],"a":[61,82,130,169],"local":[62],"geometric":[63],"density":[64],"term":[65],"derived":[66],"from":[67],"group":[68],"reference":[69],"sets.":[70],"Our":[71],"approach":[72],"is":[73],"motivated":[74],"by":[75],"phenomenon":[77],"CLIP":[79],"embeddings":[80],"exhibit":[81],"modality":[83],"gap":[84],"and":[85,162,171],"lie":[86],"an":[88],"anisotropic":[89],"shell":[90],"in":[91,143,160],"feature":[93],"space:":[94],"common":[95],"patterns":[96,103],"cluster":[97],"near":[98],"mean,":[100],"while":[101,117,146],"rare":[102,121],"pushed":[105],"outward.":[106],"This":[107],"geometry":[108],"creates":[109],"uneven":[110],"alignment,":[111],"correlations":[114],"amplified":[116],"semantically":[118,149],"meaningful":[119],"but":[120],"marginalised.":[124],"To":[125],"address":[126],"this,":[127],"employ":[129],"relative":[131],"measure":[132],"rescale":[134],"similarities":[135],"based":[136],"embedding":[138],"density,":[139],"suppressing":[140],"overconfident":[141],"diffuse":[144],"regions":[145],"preserving":[147],"dense,":[148],"consistent":[150,158],"matches.":[151],"Experimental":[152],"results":[153],"benchmark":[155],"datasets":[156],"demonstrate":[157],"improvements":[159],"worst-group":[161],"average":[163],"accuracy,":[164],"highlighting":[165],"density-aware":[166],"translation":[167],"simple":[170],"effective":[172],"calibration":[173],"mechanism":[174],"for":[175],"reliable":[176],"classification":[178],"multimodal":[180],"models.":[181]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-03T00:00:00"}