{"id":"https://openalex.org/W7160821374","doi":"https://doi.org/10.48550/arxiv.2605.07273","title":"From Clouds to Hallucinations: Atmospheric Retrieval Hijacking in Remote Sensing Vision-Language RAG","display_name":"From Clouds to Hallucinations: Atmospheric Retrieval Hijacking in Remote Sensing Vision-Language RAG","publication_year":2026,"publication_date":"2026-05-08","ids":{"openalex":"https://openalex.org/W7160821374","doi":"https://doi.org/10.48550/arxiv.2605.07273"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.07273","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.07273","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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.2605.07273","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102534764","display_name":"Jiaju Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Jiaju","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135840833","display_name":"Chao Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Chao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017525809","display_name":"Chengyin Hu","orcid":"https://orcid.org/0009-0006-9589-0182"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Chengyin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109316415","display_name":"Qike Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Qike","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132725093","display_name":"Xuemeng Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Xuemeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135891463","display_name":"Xin Wang","orcid":"https://orcid.org/0000-0002-8113-8567"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135848737","display_name":"Fengyu Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Fengyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135870523","display_name":"Xiang Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Xiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135846331","display_name":"Yiwei Wei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Yiwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135874037","display_name":"Jiahuan Long","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Long, Jiahuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5070224461","display_name":"Jiujiang Guo","orcid":"https://orcid.org/0000-0001-8614-4643"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Jiujiang","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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.4287000000476837,"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":0.4287000000476837,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.24500000476837158,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.01899999938905239,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4113999903202057},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.41130000352859497},{"id":"https://openalex.org/keywords/atmospheric-correction","display_name":"Atmospheric correction","score":0.40799999237060547},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.3797999918460846},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.28049999475479126},{"id":"https://openalex.org/keywords/visibility","display_name":"Visibility","score":0.2793000042438507},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.2775000035762787}],"concepts":[{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6998000144958496},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6776000261306763},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4113999903202057},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.41130000352859497},{"id":"https://openalex.org/C2778329001","wikidata":"https://www.wikidata.org/wiki/Q4817104","display_name":"Atmospheric correction","level":3,"score":0.40799999237060547},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.3797999918460846},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34470000863075256},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.28049999475479126},{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2775000035762787},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C134537474","wikidata":"https://www.wikidata.org/wiki/Q17144832","display_name":"Naturalness","level":2,"score":0.26179999113082886},{"id":"https://openalex.org/C141505278","wikidata":"https://www.wikidata.org/wiki/Q209363","display_name":"Weather satellite","level":3,"score":0.2574999928474426},{"id":"https://openalex.org/C2776207758","wikidata":"https://www.wikidata.org/wiki/Q5303302","display_name":"Downstream (manufacturing)","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.25600001215934753},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.25529998540878296},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.07273","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.07273","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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.2605.07273","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.07273","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multimodal":[0],"RAG":[1,20,51,150,219],"systems":[2],"increasingly":[3],"rely":[4],"on":[5,19,30,90,145],"vision-language":[6,31,166],"retrievers":[7],"to":[8,42,198,216],"ground":[9],"visual":[10],"queries":[11],"in":[12,137,184],"external":[13],"textual":[14],"evidence.":[15],"Existing":[16],"adversarial":[17,103],"studies":[18],"mainly":[21],"manipulate":[22],"the":[23,43,69,74,122,129,217],"retrieval":[24,45,63,234],"corpus":[25],"or":[26],"memory,":[27],"while":[28,72],"attacks":[29],"and":[32,77,87,94,116,119,161,181,207],"remote":[33,48,91,138,148],"sensing":[34,49,92,139,149],"models":[35],"typically":[36],"target":[37,107],"end-task":[38],"predictions.":[39],"Input-space":[40],"threats":[41],"evidence":[44,135,187,233],"stage":[46],"of":[47,124,132],"multimodal":[50,140],"remain":[52],"underexplored.":[53],"To":[54,121],"address":[55],"this":[56,127],"gap,":[57],"we":[58],"introduce":[59],"CloudWeb,":[60],"an":[61],"atmospheric":[62,108,134,176,229],"hijacking":[64,136,213],"attack":[65],"that":[66,101,211],"modifies":[67],"only":[68],"input":[70],"image":[71,104],"keeping":[73],"retriever,":[75],"generator,":[76],"knowledge":[78],"base":[79],"fixed":[80,182],"at":[81],"deployment.":[82],"CloudWeb":[83,144,170],"overlays":[84],"parameterized":[85],"cloud-":[86],"haze-like":[88],"patterns":[89],"images":[93],"optimizes":[95],"them":[96],"with":[97,152,164],"a":[98,146,224],"retrieval-oriented":[99],"objective":[100],"pulls":[102],"embeddings":[105],"toward":[106],"evidence,":[109,112],"suppresses":[110],"source-scene":[111],"enforces":[113],"rank":[114],"separation,":[115],"regularizes":[117],"naturalness":[118],"coverage.":[120],"best":[123],"our":[125],"knowledge,":[126],"is":[128],"first":[130],"study":[131],"retrieval-stage":[133,212],"RAG.":[141],"We":[142],"evaluate":[143],"seven-dataset":[147],"benchmark":[151],"five":[153],"CLIP-style":[154],"retrievers,":[155,169],"including":[156],"GeoRSCLIP,":[157],"RemoteCLIP,":[158],"OpenAI":[159],"CLIP,":[160],"OpenCLIP,":[162],"together":[163],"downstream":[165],"generators.":[167],"Across":[168],"consistently":[171],"outperforms":[172],"clean":[173],"retrieval,":[174],"handcrafted":[175],"baselines,":[177],"random":[178],"cloud":[179],"perturbations,":[180],"variants":[183],"injecting":[185],"weather-related":[186],"into":[188],"top-ranked":[189],"results.":[190],"On":[191],"GeoRSCLIP":[192],"ViT-B/32,":[193],"Weather@5":[194],"increases":[195],"from":[196],"0.71\\%":[197],"43.29\\%.":[199],"Downstream":[200],"generation":[201,236],"further":[202],"shows":[203],"measurable":[204],"weather":[205],"hallucination":[206],"semantic":[208],"shift,":[209],"indicating":[210],"can":[214,231],"propagate":[215],"final":[218],"response.":[220],"These":[221],"findings":[222],"reveal":[223],"practical":[225],"failure":[226],"mode:":[227],"natural-looking":[228],"changes":[230],"compromise":[232],"before":[235],"begins.":[237]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-12T00:00:00"}
