{"id":"https://openalex.org/W7161260609","doi":"https://doi.org/10.48550/arxiv.2605.14799","title":"Can Visual Mamba Improve AI-Generated Image Detection? An In-Depth Investigation","display_name":"Can Visual Mamba Improve AI-Generated Image Detection? An In-Depth Investigation","publication_year":2026,"publication_date":"2026-05-14","ids":{"openalex":"https://openalex.org/W7161260609","doi":"https://doi.org/10.48550/arxiv.2605.14799"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.14799","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.14799","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":"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.2605.14799","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136249501","display_name":"Mamadou Keita","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Keita, Mamadou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136215075","display_name":"Wassim Hamidouche","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hamidouche, Wassim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5094583687","display_name":"Hessen Bougueffa Eutamene","orcid":"https://orcid.org/0009-0009-0556-9996"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eutamene, Hessen Bougueffa","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136226837","display_name":"Abdelmalik Taleb-Ahmed","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Taleb-Ahmed, Abdelmalik","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018039182","display_name":"Xianxun Zhu","orcid":"https://orcid.org/0000-0003-3958-7040"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Xianxun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136201141","display_name":"Abdenour Hadid","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hadid, Abdenour","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/T12357","display_name":"Digital Media Forensic Detection","score":0.20839999616146088,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.20839999616146088,"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":0.19259999692440033,"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/T11147","display_name":"Misinformation and Its Impacts","score":0.06480000168085098,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.560699999332428},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5291000008583069},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4778999984264374},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.3756999969482422},{"id":"https://openalex.org/keywords/machine-vision","display_name":"Machine vision","score":0.3659999966621399},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.36399999260902405},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.3495999872684479},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3434999883174896},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.34040001034736633}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6773999929428101},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.657800018787384},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.560699999332428},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5291000008583069},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4778999984264374},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4424000084400177},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3756999969482422},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.3659999966621399},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.36399999260902405},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3495999872684479},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3434999883174896},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.34040001034736633},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.3357999920845032},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.32100000977516174},{"id":"https://openalex.org/C160086991","wikidata":"https://www.wikidata.org/wiki/Q5939193","display_name":"Human visual system model","level":3,"score":0.32089999318122864},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31790000200271606},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3160000145435333},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3127000033855438},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2906999886035919},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.26759999990463257},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2648000121116638},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.25699999928474426},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.25270000100135803},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.25119999051094055}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.14799","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.14799","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":"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.2605.14799","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.14799","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":"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":0.40255898237228394,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0,75],"recent":[1],"years,":[2],"computer":[3],"vision":[4],"has":[5,39],"witnessed":[6],"remarkable":[7],"progress,":[8],"fueled":[9],"by":[10],"the":[11,207],"development":[12],"of":[13,87,129,193,212],"innovative":[14],"architectures":[15,78],"such":[16,51,64,161],"as":[17,65,81,162,215],"Convolutional":[18],"Neural":[19],"Networks":[20,24],"(CNNs),":[21],"Generative":[22],"Adversarial":[23],"(GANs),":[25],"diffusion-based":[26],"architectures,":[27],"Vision":[28,130,140,182,213],"Transformers":[29],"(ViTs),":[30],"and,":[31],"more":[32],"recently,":[33],"Vision-Language":[34],"Models":[35],"(VLMs).":[36],"This":[37,120,228],"progress":[38],"undeniably":[40],"contributed":[41],"to":[42,71,117,180,188,221],"creating":[43],"increasingly":[44],"realistic":[45],"and":[46,69,73,98,126,147,153,165,171,185,196,209,242],"diverse":[47,151,168],"visual":[48,226],"content.":[49,227],"However,":[50,106],"advancements":[52],"in":[53,62,101,191,198,218,235],"image":[54,88,99,135,155,169],"generation":[55],"also":[56],"raise":[57],"concerns":[58],"about":[59],"potential":[60,108],"misuse":[61],"areas":[63],"misinformation,":[66],"identity":[67],"theft,":[68],"threats":[70],"privacy":[72],"security.":[74],"parallel,":[76],"Mamba-based":[77],"have":[79],"emerged":[80],"versatile":[82],"tools":[83],"for":[84,109,133,232],"a":[85,123,216,246],"range":[86],"analysis":[89,128],"tasks,":[90],"including":[91],"classification,":[92],"segmentation,":[93],"medical":[94],"imaging,":[95],"object":[96],"detection,":[97],"restoration,":[100],"this":[102,175],"rapidly":[103],"evolving":[104],"field.":[105],"their":[107],"identifying":[110],"AI-generated":[111,134,200,225,243],"images":[112],"remains":[113],"relatively":[114],"unexplored":[115],"compared":[116],"established":[118,189],"techniques.":[119],"study":[121],"provides":[122],"systematic":[124],"evaluation":[125],"comparative":[127],"Mamba":[131,141,214],"models":[132],"detection.":[136],"We":[137],"benchmark":[138],"multiple":[139],"variants":[142],"against":[143],"representative":[144],"CNNs,":[145],"ViTs,":[146],"VLM-based":[148],"detectors":[149],"across":[150,167],"datasets":[152],"synthetic":[154],"sources,":[156],"focusing":[157],"on":[158],"key":[159],"metrics":[160],"accuracy,":[163,195],"efficiency,":[164],"generalizability":[166],"types":[170],"generative":[172],"models.":[173],"Through":[174],"comprehensive":[176],"analysis,":[177],"we":[178],"aim":[179],"elucidate":[181],"Mamba's":[183],"strengths":[184],"limitations":[186,211],"relative":[187],"methodologies":[190],"terms":[192],"applicability,":[194],"efficiency":[197],"detecting":[199],"images.":[201],"Overall,":[202],"our":[203],"findings":[204],"highlight":[205],"both":[206],"promise":[208],"current":[210],"component":[217],"systems":[219],"designed":[220],"distinguish":[222],"authentic":[223],"from":[224],"research":[229],"is":[230,245],"crucial":[231],"enhancing":[233],"detection":[234],"an":[236],"age":[237],"where":[238],"distinguishing":[239],"between":[240],"real":[241],"content":[244],"major":[247],"challenge.":[248]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-16T00:00:00"}