{"id":"W4407012542","doi":"10.48550/arxiv.2501.18536","title":"Illusions of Relevance: Arbitrary Content Injection Attacks Deceive Retrievers, Rerankers, and LLM Judges","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Digital and Cyber Forensics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Relevance (law); Illusion; Content (measure theory); Psychology; Social psychology; Cognitive psychology; Political science; Law; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006328754,0.0008586908,0.0009824651,0.0009790713,0.001179653,0.002893268,0.001082179,0.002290968,0.002435422],"category_scores_gemma":[0.05755936,0.0004414944,0.0006605602,0.0005904805,0.003061802,0.005314317,0.002723571,0.002778662,0.00174083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001122142,"about_ca_system_score_gemma":0.000873178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001075985,"about_ca_topic_score_gemma":0.0009405006,"domain_scores_codex":[0.9926947,0.003677221,0.0003275182,0.0007182385,0.00214278,0.0004394521],"domain_scores_gemma":[0.9566998,0.022771,0.004446903,0.01289136,0.00225099,0.0009399215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00297474,0.0007185224,0.04781424,0.0007931918,0.0005615084,0.003097904,0.007388315,0.1916332,0.1045343,0.2329438,0.02525724,0.382283],"study_design_scores_gemma":[0.0001109255,0.0005336021,0.005032126,0.0001067608,0.0001172666,0.001782183,0.0007299909,0.8357329,0.04359595,0.1039747,0.008152854,0.0001307642],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5028251,0.0009041537,0.4629963,0.004975011,0.0002421377,0.0003120583,0.0002983322,0.00417911,0.02326777],"genre_scores_gemma":[0.9742488,0.0001091825,0.02189899,0.0004973595,0.00006122667,0.00004546007,0.00008527747,0.0001535956,0.002900243],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006328754,"threshold_uncertainty_score":0.03347003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04721395062880226,"score_gpt":0.256913845652999,"score_spread":0.2096998950241968,"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."}}