{"id":"https://openalex.org/W7137943215","doi":"https://doi.org/10.1609/aaai.v40i7.37421","title":"MIRAGE: Towards AI-Generated Image Detection in the Wild","display_name":"MIRAGE: Towards AI-Generated Image Detection in the Wild","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7137943215","doi":"https://doi.org/10.1609/aaai.v40i7.37421"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v40i7.37421","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i7.37421","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v40i7.37421","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129685092","display_name":"OuCheng Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"OuCheng Huang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015803667","display_name":"Manxi Lin","orcid":"https://orcid.org/0000-0003-3399-8682"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Manxi Lin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010423748","display_name":"Jiexiang Tan","orcid":"https://orcid.org/0000-0002-8274-9642"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiexiang Tan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042009893","display_name":"Xiaoxiong Du","orcid":"https://orcid.org/0009-0005-7743-7301"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaoxiong Du","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129656565","display_name":"Yang Qiu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang Qiu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102516938","display_name":"Junjun Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Junjun Zheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010515776","display_name":"Xiangheng Kong","orcid":"https://orcid.org/0000-0003-2450-7837"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiangheng Kong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129703285","display_name":"Yuning Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuning Jiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129715522","display_name":"Bo Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bo Zheng","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":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"7","first_page":"5076","last_page":"5084"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.36419999599456787,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.36419999599456787,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.1720000058412552,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.15039999783039093,"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/inference","display_name":"Inference","score":0.6129999756813049},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6100000143051147},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5726000070571899},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.4948999881744385},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4478999972343445},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.42989999055862427}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7217000126838684},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6129999756813049},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6100000143051147},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.60589998960495},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5726000070571899},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4948999881744385},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4478999972343445},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4357999861240387},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.42989999055862427},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4284999966621399},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.366100013256073},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3619000017642975},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.32359999418258667},{"id":"https://openalex.org/C2986045029","wikidata":"https://www.wikidata.org/wiki/Q294240","display_name":"Public security","level":2,"score":0.28029999136924744},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.26339998841285706},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.25119999051094055}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v40i7.37421","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i7.37421","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:ojs.aaai.org:article/37421","is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/37421","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i7.37421","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i7.37421","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"spreading":[1],"of":[2,83,96],"AI-generated":[3],"images":[4,29,42,49],"(AIGI),":[5],"driven":[6],"by":[7,100,156,200],"advances":[8],"in":[9,30,69,121,148],"generative":[10,56],"AI,":[11],"poses":[12],"a":[13,75,93,105,131,138,151,157,164,175,179],"significant":[14],"threat":[15],"to":[16,35,37,50,79,172],"in-":[17],"formation":[18],"security":[19],"and":[20,58,103,182,189,202,206],"public":[21,207],"trust.":[22],"Existing":[23],"AIGI":[24,67,98,120,143],"detectors,":[25],"while":[26],"effective":[27],"against":[28],"clean":[31],"laboratory":[32],"settings,":[33],"fail":[34],"generalize":[36],"in-the-wild":[38,66,84],"scenarios.":[39],"These":[40],"real-world":[41],"are":[43],"noisy,":[44],"varying":[45],"from":[46,54,89],"\u201cobviously":[47],"fake\u201d":[48],"realistic":[51,119],"ones":[52],"derived":[53],"multiple":[55,113],"models":[57],"further":[59,162],"edited":[60],"for":[61,142],"quality":[62],"control.":[63],"We":[64,72],"address":[65],"detection":[68],"this":[70,126],"paper.":[71],"introduce":[73],"MIRAGE,":[74],"challenging":[76],"benchmark":[77],"designed":[78],"emulate":[80],"the":[81,110,118,122],"complexity":[82],"AIGI.":[85],"MIRAGE":[86,205],"is":[87,146,170],"constructed":[88],"two":[90,149],"sources:":[91],"(1)":[92],"large":[94],"corpus":[95],"Internet-sourced":[97],"verified":[99],"human":[101],"experts,":[102],"(2)":[104],"synthesized":[106],"dataset":[107],"created":[108],"through":[109],"collaboration":[111],"between":[112],"expert":[114],"generators,":[115],"closely":[116],"simulating":[117],"wild.":[123],"Building":[124],"on":[125,204],"benchmark,":[127,208],"we":[128],"propose":[129],"MIRAGE-R1,":[130],"vision-":[132],"language":[133],"model":[134,196],"with":[135],"heuristic-to-analytic":[136],"reasoning,":[137],"reflective":[139],"reasoning":[140],"mechanism":[141],"detection.":[144],"MIRAGE-R1":[145,169],"trained":[147],"stages:":[150],"supervised-fine-tuning":[152],"cold":[153],"start,":[154],"followed":[155],"reinforcement":[158],"learning":[159],"stage.":[160],"By":[161],"adopting":[163],"inference-time":[165],"adaptive":[166],"thinking":[167],"strategy,":[168],"able":[171],"provide":[173],"either":[174],"quick":[176],"judgment":[177],"or":[178],"more":[180],"robust":[181],"accurate":[183],"conclusion,":[184],"effectively":[185],"balancing":[186],"inference":[187],"speed":[188],"performance.":[190],"Extensive":[191],"experiments":[192],"show":[193],"that":[194],"our":[195],"leads":[197],"state-of-the-art":[198],"detectors":[199],"5%":[201],"10%":[203],"respectively.":[209]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-03-18T00:00:00"}
