{"id":"https://openalex.org/W7140166014","doi":"https://doi.org/10.48550/arxiv.2603.21047","title":"When Minor Edits Matter: LLM-Driven Prompt Attack for Medical VLM Robustness in Ultrasound","display_name":"When Minor Edits Matter: LLM-Driven Prompt Attack for Medical VLM Robustness in Ultrasound","publication_year":2026,"publication_date":"2026-03-22","ids":{"openalex":"https://openalex.org/W7140166014","doi":"https://doi.org/10.48550/arxiv.2603.21047"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.21047","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21047","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.21047","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Medghalchi, Yasamin","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Medghalchi, Yasamin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Yazdani, Milad","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yazdani, Milad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Dabiriaghdam, Amirhossein","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dabiriaghdam, Amirhossein","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Heidari, Moein","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Heidari, Moein","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Izadkhah, Mojan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Izadkhah, Mojan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Kavian, Zahra","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kavian, Zahra","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Carenini, Giuseppe","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Carenini, Giuseppe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Wang, Lele","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Lele","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Shahriari, Dena","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shahriari, Dena","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Hacihaliloglu, Ilker","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hacihaliloglu, Ilker","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":10,"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":0.9681000113487244,"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":0.9681000113487244,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.004399999976158142,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.003599999938160181,"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/robustness","display_name":"Robustness (evolution)","score":0.8147000074386597},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7893999814987183},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5702999830245972},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.5116999745368958},{"id":"https://openalex.org/keywords/vulnerability","display_name":"Vulnerability (computing)","score":0.3824999928474426},{"id":"https://openalex.org/keywords/clinical-practice","display_name":"Clinical Practice","score":0.38029998540878296},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.36250001192092896},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.3425999879837036}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8147000074386597},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7893999814987183},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7777000069618225},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5702999830245972},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5328999757766724},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.5116999745368958},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.414900004863739},{"id":"https://openalex.org/C95713431","wikidata":"https://www.wikidata.org/wiki/Q631425","display_name":"Vulnerability (computing)","level":2,"score":0.3824999928474426},{"id":"https://openalex.org/C2779974597","wikidata":"https://www.wikidata.org/wiki/Q28448986","display_name":"Clinical Practice","level":2,"score":0.38029998540878296},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.36250001192092896},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3425999879837036},{"id":"https://openalex.org/C2986892559","wikidata":"https://www.wikidata.org/wiki/Q234904","display_name":"Ultrasound imaging","level":3,"score":0.32519999146461487},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2962999939918518},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2872999906539917},{"id":"https://openalex.org/C140547941","wikidata":"https://www.wikidata.org/wiki/Q7797194","display_name":"Threat model","level":2,"score":0.2851000130176544},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27950000762939453},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.27880001068115234},{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C73301696","wikidata":"https://www.wikidata.org/wiki/Q5469984","display_name":"Formalism (music)","level":3,"score":0.2574000060558319},{"id":"https://openalex.org/C110251889","wikidata":"https://www.wikidata.org/wiki/Q1569697","display_name":"Model checking","level":2,"score":0.25529998540878296},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.21047","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21047","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.21047","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21047","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"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":{"Ultrasound":[0],"is":[1,66],"widely":[2],"used":[3],"in":[4,47],"clinical":[5,129,184],"practice":[6],"due":[7],"to":[8,113,145],"its":[9],"portability,":[10],"cost-effectiveness,":[11],"safety,":[12],"and":[13,20,44,79,123,162,165],"real-time":[14],"imaging":[15],"capabilities.":[16],"However,":[17,53],"image":[18,49],"acquisition":[19],"interpretation":[21],"remain":[22],"highly":[23],"operator":[24],"dependent,":[25],"motivating":[26],"the":[27,140,157,192],"development":[28],"of":[29,83,142],"robust":[30],"AI-assisted":[31],"analysis":[32],"methods.":[33],"Vision-language":[34],"models":[35],"(VLMs)":[36],"have":[37],"recently":[38],"demonstrated":[39],"strong":[40],"multimodal":[41],"reasoning":[42],"capabilities":[43],"competitive":[45],"performance":[46],"medical":[48],"analysis,":[50],"including":[51],"ultrasound.":[52],"emerging":[54],"evidence":[55],"highlights":[56],"significant":[57],"concerns":[58],"about":[59],"their":[60],"trustworthiness.":[61],"In":[62],"particular,":[63],"adversarial":[64,103,117],"robustness":[65,176],"critical":[67],"because":[68],"Med-VLMs":[69,144],"operate":[70],"via":[71,120],"natural-language":[72],"instructions,":[73],"rendering":[74],"prompt":[75,118],"formulation":[76],"a":[77,101,108],"realistic":[78,175],"practically":[80],"exploitable":[81],"point":[82],"vulnerability.":[84],"Small":[85],"variations":[86],"(typos,":[87],"shorthand,":[88],"underspecified":[89],"requests,":[90],"or":[91],"ambiguous":[92],"wording)":[93],"can":[94],"meaningfully":[95],"shift":[96],"model":[97,111,163],"outputs.":[98],"We":[99],"propose":[100],"scalable":[102],"evaluation":[104],"framework":[105],"that":[106,126,178],"leverages":[107],"large":[109],"language":[110],"(LLM)":[112],"generate":[114],"clinically":[115],"plausible":[116],"variants":[119],"\"humanized\"":[121],"rewrites":[122],"minimal":[124],"edits":[125],"mimic":[127],"routine":[128],"communication.":[130],"Using":[131],"ultrasound":[132],"multiple-choice":[133],"question":[134],"answering":[135],"benchmarks,":[136],"we":[137],"systematically":[138],"assess":[139],"vulnerability":[141],"SOTA":[143],"these":[146],"attacks,":[147],"examine":[148],"how":[149],"attacker":[150],"LLM":[151],"capacity":[152],"influences":[153],"attack":[154,160],"success,":[155],"analyze":[156],"relationship":[158],"between":[159],"success":[161],"confidence,":[164],"identify":[166],"consistent":[167],"failure":[168],"patterns":[169],"across":[170],"models.":[171],"Our":[172],"results":[173],"highlight":[174],"gaps":[177],"must":[179],"be":[180,188],"addressed":[181],"for":[182],"safe":[183],"translation.":[185],"Code":[186],"will":[187],"released":[189],"publicly":[190],"following":[191],"review":[193],"process.":[194]},"counts_by_year":[],"updated_date":"2026-04-25T08:17:42.794288","created_date":"2026-03-25T00:00:00"}