{"id":"https://openalex.org/W7160919986","doi":"https://doi.org/10.48550/arxiv.2605.08820","title":"FraudBench: A Multimodal Benchmark for Detecting AI-Generated Fraudulent Refund Evidence","display_name":"FraudBench: A Multimodal Benchmark for Detecting AI-Generated Fraudulent Refund Evidence","publication_year":2026,"publication_date":"2026-05-09","ids":{"openalex":"https://openalex.org/W7160919986","doi":"https://doi.org/10.48550/arxiv.2605.08820"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.08820","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.08820","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.2605.08820","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135933228","display_name":"Xinyu Yan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan, Xinyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100688828","display_name":"Boyang Chen","orcid":"https://orcid.org/0000-0002-7855-7867"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Boyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135955448","display_name":"Jiaming Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Jiaming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053574427","display_name":"Tiantong Wu","orcid":"https://orcid.org/0000-0003-0616-2521"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Tiantong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116335601","display_name":"Hong Xi Tae","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tae, Hong Xi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033758211","display_name":"Yichen He","orcid":"https://orcid.org/0000-0003-3464-7526"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Yichen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127872127","display_name":"Tiantong Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Tiantong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110086384","display_name":"Yachun Mi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mi, Yachun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072423938","display_name":"Yurong Hao","orcid":"https://orcid.org/0000-0002-9370-7958"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hao, Yurong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135972315","display_name":"Yilei Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Yilei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135957779","display_name":"Lei Xiao","orcid":"https://orcid.org/0000-0002-6897-4608"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Lei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135967233","display_name":"Longtao Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Longtao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135999328","display_name":"Pengjun Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Pengjun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135935806","display_name":"Wei Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5027969322","display_name":"Wei Yang Bryan Lim","orcid":"https://orcid.org/0000-0003-2150-5561"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lim, Wei Yang Bryan","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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.2583000063896179,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.2583000063896179,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.18459999561309814,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.15000000596046448,"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/false-positive-paradox","display_name":"False positive paradox","score":0.6507999897003174},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6384000182151794},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5024999976158142},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.47450000047683716},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.3982999920845032},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.37720000743865967},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.36489999294281006}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7304999828338623},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.6507999897003174},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6384000182151794},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5364999771118164},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5024999976158142},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.47450000047683716},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.3982999920845032},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.37720000743865967},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.36489999294281006},{"id":"https://openalex.org/C112789634","wikidata":"https://www.wikidata.org/wiki/Q18207010","display_name":"False positives and false negatives","level":3,"score":0.35989999771118164},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.34360000491142273},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33980000019073486},{"id":"https://openalex.org/C2987933465","wikidata":"https://www.wikidata.org/wiki/Q141130","display_name":"Image manipulation","level":3,"score":0.32919999957084656},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.30160000920295715},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2992999851703644},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.25619998574256897},{"id":"https://openalex.org/C2776674983","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image editing","level":3,"score":0.2556999921798706},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.25529998540878296}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.08820","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.08820","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.2605.08820","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.08820","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":0.5984234809875488}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Artificial":[0],"Intelligence":[1],"(AI)-generated":[2],"images":[3,35,105,134],"have":[4],"become":[5],"increasingly":[6],"realistic":[7],"and":[8,98,111,117,123,126,140,152,198,215],"readily":[9],"adaptable":[10],"to":[11,38],"concrete":[12,23],"real-world":[13,91],"claims,":[14],"creating":[15],"new":[16],"challenges":[17],"for":[18,81],"verifying":[19],"visual":[20],"evidence.":[21,86],"A":[22],"emerging":[24],"risk":[25],"is":[26,88],"AI-generated":[27,51,83,149],"refund":[28,85],"fraud,":[29],"in":[30],"which":[31],"manipulated":[32],"or":[33,47,62],"synthetic":[34],"are":[36],"used":[37],"support":[39],"claims":[40],"about":[41],"damaged":[42,116],"products,":[43],"poor":[44],"delivery":[45],"conditions,":[46],"service-related":[48],"defects.":[49],"Existing":[50],"image":[52,138,150,213],"detection":[53,69,176,214],"benchmarks":[54],"mainly":[55],"evaluate":[56,146],"standalone":[57],"authenticity":[58],"classification,":[59],"cross-generator":[60],"transfer,":[61],"forensic":[63],"localization,":[64],"leaving":[65],"claim-conditioned":[66,217],"fraudulent":[67,84],"evidence":[68,93,104,119,129,167],"underexplored.":[70],"To":[71],"bridge":[72],"this":[73],"gap,":[74],"we":[75,145],"introduce":[76],"FraudBench,":[77,144],"a":[78,207],"multimodal":[79],"benchmark":[80],"detecting":[82],"FraudBench":[87],"constructed":[89],"from":[90,130],"user-review":[92],"across":[94,196],"e-commerce,":[95],"food":[96],"delivery,":[97],"travel-service":[99],"scenarios.":[100],"We":[101],"curate":[102],"real":[103],"together":[106],"with":[107,174],"their":[108],"associated":[109],"review":[110],"product":[112],"metadata,":[113],"identify":[114],"genuine":[115,131],"undamaged":[118,132],"through":[120],"MLLM-assisted":[121],"filtering":[122],"human":[124,153],"annotation,":[125],"synthesize":[127],"fake-damaged":[128,172],"reference":[133],"using":[135],"six":[136],"state-of-the-art":[137],"editing":[139],"generation":[141],"models.":[142],"Using":[143],"MLLMs,":[147],"specialized":[148],"detectors,":[151],"participants":[154],"under":[155],"the":[156,181],"same":[157],"settings.":[158],"Experiments":[159],"show":[160],"that":[161],"current":[162],"MLLMs":[163],"often":[164],"recognize":[165],"real-damaged":[166,204],"but":[168,193],"fail":[169],"on":[170,184,203],"many":[171],"subsets,":[173],"fake-damage":[175],"rates":[177],"(TPR)":[178],"far":[179],"below":[180],"50%":[182],"baseline":[183],"most":[185],"generator":[186],"subsets.":[187],"Specialized":[188],"detectors":[189],"generally":[190],"perform":[191],"better":[192],"remain":[194],"inconsistent":[195],"generators":[197],"can":[199],"produce":[200],"false":[201],"positives":[202],"samples,":[205],"revealing":[206],"clear":[208],"gap":[209],"between":[210],"generic":[211],"AI":[212],"reliable":[216],"refund-evidence":[218],"verification.":[219]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-13T00:00:00"}