{"id":"W4413157643","doi":"10.1109/cvpr52734.2025.02660","title":"Prompt2Perturb (P2P): Text-Guided Diffusion-Based Adversarial Attacks on Breast Ultrasound Images","year":2025,"lang":"en","type":"article","venue":"","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Adversarial system; Computer science; Artificial intelligence; Diffusion; Breast ultrasound; Computer vision; Pattern recognition (psychology); Mammography; Breast cancer; Medicine; Physics; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001034892,0.001286377,0.0005802559,0.0003621248,0.0002432644,0.0005582721,0.0008951332,0.001161885,0.002025579],"category_scores_gemma":[0.00556554,0.0002558986,0.0006044239,0.0001969563,0.001173302,0.001567531,0.001858399,0.002037222,0.0007058477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005410897,"about_ca_system_score_gemma":0.0005265378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007383093,"about_ca_topic_score_gemma":0.001067,"domain_scores_codex":[0.9992344,0.0002547107,0.00003852009,0.0001704846,0.0002296067,0.0000722001],"domain_scores_gemma":[0.9982808,0.001027438,0.000182424,0.0002967292,0.0001367909,0.00007595423],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008283066,0.0002321218,0.002115556,0.0003859282,0.0001044812,0.0006778304,0.0002492177,0.6283941,0.06038067,0.02429475,0.01542966,0.2669075],"study_design_scores_gemma":[0.0000224911,0.0001364199,0.0002404515,0.00001800785,0.000009109221,0.0001704473,0.00001732875,0.9736623,0.01653025,0.007390505,0.001787163,0.00001550905],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06814723,0.0007117157,0.9202259,0.0007867602,0.0002028953,0.0001459874,0.000309326,0.006265913,0.00320418],"genre_scores_gemma":[0.8242761,0.0005485547,0.1647471,0.0008774042,0.0001127544,0.0002099834,0.0007944168,0.0005691199,0.007864528],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002025579,"threshold_uncertainty_score":0.006776214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0085022753043582,"score_gpt":0.2711750793036014,"score_spread":0.2626728039992432,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}