{"id":"https://openalex.org/W7165205165","doi":"https://doi.org/10.48550/arxiv.2606.19184","title":"When AUC Misleads: Polarization-Aware Evaluation of Deepfake Detectors under Domain Shift","display_name":"When AUC Misleads: Polarization-Aware Evaluation of Deepfake Detectors under Domain Shift","publication_year":2026,"publication_date":"2026-06-17","ids":{"openalex":"https://openalex.org/W7165205165","doi":"https://doi.org/10.48550/arxiv.2606.19184"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.19184","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.19184","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2606.19184","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138880036","display_name":"Dat Nguyen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nguyen, Dat","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058284960","display_name":"Cosmin Radoi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Radoi, Cosmin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085180472","display_name":"Romain Hermary","orcid":"https://orcid.org/0000-0001-9351-2862"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hermary, Romain","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042350375","display_name":"Marcella Astrid","orcid":"https://orcid.org/0000-0003-1432-6661"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Astrid, Marcella","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076577348","display_name":"Nesryne Mejri","orcid":"https://orcid.org/0000-0002-0541-1234"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mejri, Nesryne","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080787031","display_name":"Enjie Ghorbel","orcid":"https://orcid.org/0000-0002-6878-0141"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ghorbel, Enjie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5083368272","display_name":"Djamila Aouada","orcid":"https://orcid.org/0000-0002-7576-2064"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aouada, Djamila","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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.7839000225067139,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.7839000225067139,"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/T11448","display_name":"Face recognition and analysis","score":0.05290000140666962,"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":0.025200000032782555,"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/robustness","display_name":"Robustness (evolution)","score":0.6703000068664551},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4900999963283539},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.4722000062465668},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.39469999074935913},{"id":"https://openalex.org/keywords/artifact","display_name":"Artifact (error)","score":0.38920000195503235},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.38760000467300415},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.36910000443458557},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.31380000710487366}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6703000068664551},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6122999787330627},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4984000027179718},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4900999963283539},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.4722000062465668},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42309999465942383},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.39469999074935913},{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.38920000195503235},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.38760000467300415},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3772999942302704},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.36910000443458557},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34549999237060547},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.31380000710487366},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.3061999976634979},{"id":"https://openalex.org/C205049153","wikidata":"https://www.wikidata.org/wiki/Q2698605","display_name":"Polarization (electrochemistry)","level":2,"score":0.2985999882221222},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.29170000553131104},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28929999470710754},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.2827000021934509},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.26460000872612},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.2644999921321869},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.26339998841285706},{"id":"https://openalex.org/C184389593","wikidata":"https://www.wikidata.org/wiki/Q603159","display_name":"Curve fitting","level":2,"score":0.2572999894618988}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.19184","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.19184","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2606.19184","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.19184","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":0.8318313956260681,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"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],"advances":[1],"in":[2,163],"generative":[3],"AI,":[4],"such":[5,70],"as":[6,154],"diffusion":[7],"models":[8],"and":[9,27,86],"face-swapping":[10],"tools,":[11],"have":[12],"enabled":[13],"the":[14,57,60,116,127,138,158],"creation":[15],"of":[16,83,109,141],"highly":[17],"realistic":[18],"deepfakes,":[19],"leading":[20],"to":[21,49,74,118],"real-world":[22,76],"harms":[23],"including":[24],"financial":[25],"fraud":[26],"non-consensual":[28],"explicit":[29],"content.":[30],"In":[31],"response,":[32],"deepfake":[33,142],"detection":[34],"has":[35],"become":[36],"an":[37,71],"active":[38],"research":[39],"area,":[40],"with":[41,106],"recent":[42],"methods":[43],"increasingly":[44],"focusing":[45],"on":[46,167],"improving":[47],"generalization":[48,139],"unseen":[50],"manipulations.":[51],"This":[52],"is":[53,124,151],"typically":[54],"evaluated":[55],"using":[56],"Area":[58],"Under":[59],"ROC":[61],"Curve":[62],"(AUC)":[63],"measured":[64],"separately":[65],"across":[66],"multiple":[67],"datasets.":[68],"However,":[69],"evaluation":[72],"fails":[73],"reflect":[75],"scenarios":[77],"where":[78],"detectors":[79,143],"face":[80],"a":[81,96,107,161],"mixture":[82],"data":[84],"sources":[85],"varying":[87],"artifact":[88],"types.":[89],"To":[90],"address":[91],"this":[92],"limitation,":[93],"we":[94],"introduce":[95],"novel":[97],"metric,":[98],"Cross-dataset":[99],"AUC":[100],"(Cross-AUC)":[101],"that":[102],"averages":[103],"per-domain":[104],"AUCs":[105],"measure":[108],"prediction":[110],"polarization":[111,122],"for":[112],"taking":[113],"into":[114],"account":[115],"robustness":[117],"domain":[119,145],"shift.":[120],"The":[121],"extent":[123],"quantified":[125],"by":[126],"Wasserstein":[128],"Distance":[129],"between":[130],"class":[131],"score":[132],"distributions.":[133],"Cross-AUC":[134],"not":[135],"only":[136],"assesses":[137],"capabilities":[140],"under":[144],"shifts":[146],"more":[147],"realistically,":[148],"but":[149],"it":[150,155],"also":[152],"interpretable":[153],"better":[156],"explains":[157],"reason":[159],"behind":[160],"drop":[162],"performance.":[164],"Experiments":[165],"performed":[166],"seven":[168],"benchmark":[169],"datasets":[170],"demonstrate":[171],"its":[172],"practical":[173],"relevance.":[174]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-19T00:00:00"}