{"id":"https://openalex.org/W7083670130","doi":"https://doi.org/10.48550/arxiv.2509.22412","title":"FreqDebias: Towards Generalizable Deepfake Detection via Consistency-Driven Frequency Debiasing","display_name":"FreqDebias: Towards Generalizable Deepfake Detection via Consistency-Driven Frequency Debiasing","publication_year":2025,"publication_date":"2025-09-26","ids":{"openalex":"https://openalex.org/W7083670130","doi":"https://doi.org/10.48550/arxiv.2509.22412"},"language":"en","primary_location":{"id":"doi:10.48550/arxiv.2509.22412","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2509.22412","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.2509.22412","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Kashiani, Hossein","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kashiani, Hossein","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Talemi, Niloufar Alipour","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Talemi, Niloufar Alipour","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Afghah, Fatemeh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Afghah, Fatemeh","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":true,"primary_topic":{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.6834999918937683,"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/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.6834999918937683,"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/T13067","display_name":"Geological Modeling and Analysis","score":0.027400000020861626,"subfield":{"id":"https://openalex.org/subfields/1906","display_name":"Geochemistry and Petrology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14311","display_name":"Electrical and Electromagnetic Research","score":0.01759999990463257,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/debiasing","display_name":"Debiasing","score":0.8654999732971191},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.644599974155426},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6183000206947327},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5440000295639038},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5325999855995178},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.46860000491142273},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4142000079154968}],"concepts":[{"id":"https://openalex.org/C2779458634","wikidata":"https://www.wikidata.org/wiki/Q24963715","display_name":"Debiasing","level":2,"score":0.8654999732971191},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6858999729156494},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.644599974155426},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6183000206947327},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5440000295639038},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5333999991416931},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5325999855995178},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.46860000491142273},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4408000111579895},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4142000079154968},{"id":"https://openalex.org/C37279795","wikidata":"https://www.wikidata.org/wiki/Q2492305","display_name":"Consistency model","level":3,"score":0.39570000767707825},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.3847000002861023},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3160000145435333},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.31529998779296875},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.3027999997138977},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.2858000099658966},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2847000062465668}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2509.22412","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2509.22412","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.2509.22412","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2509.22412","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":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.4288499057292938}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Deepfake":[0],"detectors":[1,37],"often":[2],"struggle":[3],"to":[4,6,11,47],"generalize":[5,48],"novel":[7,74],"forgery":[8],"types":[9],"due":[10],"biases":[12],"learned":[13],"from":[14],"limited":[15],"training":[16,85],"data.":[17],"In":[18],"this":[19],"paper,":[20],"we":[21,55,71,88],"identify":[22],"a":[23,58,73,90,109,115],"new":[24],"type":[25],"of":[26,84],"model":[27],"bias":[28,65],"in":[29,152],"the":[30],"frequency":[31,42,59,82,126],"domain,":[32],"termed":[33],"spectral":[34,64],"bias,":[35],"where":[36],"overly":[38],"rely":[39],"on":[40,114,124],"specific":[41],"bands,":[43],"restricting":[44],"their":[45],"ability":[46],"across":[49],"unseen":[50],"forgeries.":[51],"To":[52],"address":[53],"this,":[54],"propose":[56],"FreqDebias,":[57],"debiasing":[60],"framework":[61],"that":[62,142],"mitigates":[63,122],"through":[66,108],"two":[67],"complementary":[68],"strategies.":[69],"First,":[70],"introduce":[72],"Forgery":[75],"Mixup":[76],"(Fo-Mixup)":[77],"augmentation,":[78],"which":[79,95],"dynamically":[80],"diversifies":[81],"characteristics":[83],"samples.":[86],"Second,":[87],"incorporate":[89],"dual":[91,120],"consistency":[92,99,107],"regularization":[93],"(CR),":[94],"enforces":[96],"both":[97,134,153],"local":[98,135],"using":[100],"class":[101],"activation":[102],"maps":[103],"(CAMs)":[104],"and":[105,136,148,155],"global":[106,137],"von":[110],"Mises-Fisher":[111],"(vMF)":[112],"distribution":[113],"hyperspherical":[116],"embedding":[117],"space.":[118],"This":[119],"CR":[121],"over-reliance":[123],"certain":[125],"components":[127],"by":[128],"promoting":[129],"consistent":[130],"representation":[131],"learning":[132],"under":[133],"supervision.":[138],"Extensive":[139],"experiments":[140],"show":[141],"FreqDebias":[143],"significantly":[144],"enhances":[145],"cross-domain":[146,154],"generalization":[147],"outperforms":[149],"state-of-the-art":[150],"methods":[151],"in-domain":[156],"settings.":[157]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}
