{"id":"https://openalex.org/W7160376232","doi":"https://doi.org/10.1109/access.2026.3691016","title":"Generalist Multimodal LLMs Gain Biometric Expertise via Human Salience for Iris Presentation Attack Detection","display_name":"Generalist Multimodal LLMs Gain Biometric Expertise via Human Salience for Iris Presentation Attack Detection","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7160376232","doi":"https://doi.org/10.1109/access.2026.3691016"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3691016","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3691016","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3691016","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135447924","display_name":"Jacob Piland","orcid":"https://orcid.org/0009-0000-6140-7734"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jacob C. Piland","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA"],"raw_orcid":"https://orcid.org/0009-0000-6140-7734","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120732948","display_name":"Byron Dowling","orcid":null},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Byron Dowling","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135524100","display_name":"Christopher Sweet","orcid":null},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christopher Sweet","raw_affiliation_strings":["Center for Research Computing, University of Notre Dame, Notre Dame, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Research Computing, University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5135509008","display_name":"Adam Czajka","orcid":"https://orcid.org/0000-0003-2379-2533"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Adam Czajka","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA"],"raw_orcid":"https://orcid.org/0000-0003-2379-2533","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.70729111,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"71872","last_page":"71884"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.8317000269889832,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10828","display_name":"Biometric Identification and Security","score":0.8317000269889832,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.029200000688433647,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.020800000056624413,"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/biometrics","display_name":"Biometrics","score":0.8245999813079834},{"id":"https://openalex.org/keywords/salience","display_name":"Salience (neuroscience)","score":0.7915999889373779},{"id":"https://openalex.org/keywords/presentation","display_name":"Presentation (obstetrics)","score":0.6154000163078308},{"id":"https://openalex.org/keywords/generalist-and-specialist-species","display_name":"Generalist and specialist species","score":0.5820000171661377},{"id":"https://openalex.org/keywords/iris","display_name":"IRIS (biosensor)","score":0.506600022315979}],"concepts":[{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.8245999813079834},{"id":"https://openalex.org/C108154423","wikidata":"https://www.wikidata.org/wiki/Q1469792","display_name":"Salience (neuroscience)","level":2,"score":0.7915999889373779},{"id":"https://openalex.org/C2777601897","wikidata":"https://www.wikidata.org/wiki/Q3409113","display_name":"Presentation (obstetrics)","level":2,"score":0.6154000163078308},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6137999892234802},{"id":"https://openalex.org/C45371612","wikidata":"https://www.wikidata.org/wiki/Q3058587","display_name":"Generalist and specialist species","level":3,"score":0.5820000171661377},{"id":"https://openalex.org/C2779503344","wikidata":"https://www.wikidata.org/wiki/Q5973514","display_name":"IRIS (biosensor)","level":3,"score":0.506600022315979},{"id":"https://openalex.org/C112356035","wikidata":"https://www.wikidata.org/wiki/Q1672722","display_name":"Iris recognition","level":3,"score":0.5042999982833862},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4027999937534332},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3652999997138977},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.35580000281333923},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.2827000021934509},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2687000036239624}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3691016","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3691016","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1886e310552043659b7e9722cdead9be","is_oa":true,"landing_page_url":"https://doaj.org/article/1886e310552043659b7e9722cdead9be","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 14, Pp 71872-71884 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3691016","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3691016","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":0.479108065366745}],"awards":[{"id":"https://openalex.org/G3733242718","display_name":null,"funder_award_id":"W52P1J-20-9-3009","funder_id":"https://openalex.org/F4320306078","funder_display_name":"U.S. Department of Defense"},{"id":"https://openalex.org/G5701255588","display_name":null,"funder_award_id":"2237880","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6547127127","display_name":null,"funder_award_id":"2237880","funder_id":"https://openalex.org/F4320306078","funder_display_name":"U.S. Department of Defense"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306078","display_name":"U.S. Department of Defense","ror":"https://ror.org/0447fe631"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Iris":[0],"presentation":[1],"attack":[2,55,120,136,151,170],"detection":[3],"(PAD)":[4],"is":[5,25,40],"critical":[6],"for":[7,127,225],"secure":[8],"biometric":[9,44,91],"deployments,":[10],"yet":[11,31],"developing":[12],"specialized":[13,195],"models":[14,71,155,181],"faces":[15],"significant":[16],"practical":[17],"barriers:":[18],"collecting":[19,28],"data":[20,45,92],"representing":[21],"future":[22],"unknown":[23],"attacks":[24],"impossible,":[26],"and":[27,201],"diverse-enough":[29],"data,":[30],"still":[32],"limited":[33],"in":[34,63,114],"terms":[35],"of":[36,53,100,164],"its":[37],"predictive":[38],"power,":[39],"expensive.":[41],"Additionally,":[42],"sharing":[43],"raises":[46],"privacy":[47,86,219],"concerns.":[48],"Due":[49],"to":[50,93,105,156],"rapid":[51],"emergence":[52],"new":[54],"vectors":[56],"demanding":[57],"adaptable":[58],"solutions,":[59],"we":[60,108,138,185],"thus":[61],"investigate":[62],"this":[64,128],"paper":[65],"whether":[66],"general-purpose":[67],"multimodal":[68],"large":[69],"language":[70],"(MLLMs)":[72],"can":[73],"perform":[74],"iris":[75,119,166,226],"PAD":[76],"when":[77],"augmented":[78],"with":[79,189],"human":[80,144,202],"expert":[81],"knowledge,":[82],"operating":[83],"under":[84],"strict":[85],"constraints":[87,220],"that":[88,110,140,187,214],"prohibit":[89],"sending":[90],"public":[94],"cloud":[95],"MLLM":[96],"services.":[97],"Through":[98],"analysis":[99],"vision":[101,112],"encoder":[102],"embeddings":[103],"applied":[104],"our":[106],"dataset,":[107],"demonstrate":[109],"pre-trained":[111],"transformers":[113],"MLLMs":[115,215],"inherently":[116],"cluster":[117],"many":[118],"types":[121],"despite":[122],"never":[123],"being":[124],"explicitly":[125],"trained":[126],"task.":[129],"However,":[130],"where":[131],"clustering":[132],"shows":[133],"overlap":[134],"between":[135],"classes,":[137],"find":[139],"structured":[141],"prompts":[142,191],"incorporating":[143],"salience":[145],"(verbal":[146],"descriptions":[147],"from":[148],"subjects":[149],"identifying":[150],"indicators)":[152],"enable":[153],"these":[154],"resolve":[157],"ambiguities.":[158],"Testing":[159],"on":[160],"an":[161],"IRB-restricted":[162],"dataset":[163],"224":[165],"images":[167],"spanning":[168],"seven":[169],"types,":[171],"using":[172],"only":[173],"university-approved":[174],"services":[175],"(Gemini":[176],"2.5":[177],"Pro)":[178],"or":[179],"locally-hosted":[180],"(e.g.,":[182],"Llama":[183,207],"3.2-Vision),":[184],"show":[186],"Gemini":[188],"expert-informed":[190],"outperforms":[192],"both":[193],"a":[194,222],"convolutional":[196],"neural":[197],"networks":[198],"(CNN)-based":[199],"baseline":[200],"examiners,":[203],"while":[204],"the":[205],"locally-deployable":[206],"achieves":[208],"near-human":[209],"performance.":[210],"Our":[211],"results":[212],"establish":[213],"deployable":[216],"within":[217],"institutional":[218],"offer":[221],"viable":[223],"path":[224],"PAD.":[227]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-07T00:00:00"}
