{"id":"W3175734114","doi":"10.1109/icde51399.2021.00202","title":"Stealthy Targeted Data Poisoning Attack on Knowledge Graphs","year":2021,"lang":"en","type":"article","venue":"","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada); University of British Columbia","funders":"","keywords":"Intuition; Computer science; Embedding; Reinforcement learning; Adversarial system; Artificial intelligence; Machine learning; Benchmark (surveying); Computer security","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005201584,0.00017601,0.0002034512,0.0001115121,0.0002636586,0.0001961208,0.002193831,0.0000743232,0.0001899715],"category_scores_gemma":[0.0004220167,0.0001640678,0.00004973374,0.000888587,0.00003149068,0.0007212252,0.002236021,0.0004161248,0.0003718585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000448452,"about_ca_system_score_gemma":0.0002337871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002580353,"about_ca_topic_score_gemma":0.00004613316,"domain_scores_codex":[0.9979356,0.0002763013,0.0002505116,0.000854652,0.000292055,0.0003909121],"domain_scores_gemma":[0.9971529,0.0003606273,0.00008715155,0.002149366,0.0001182608,0.0001316908],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001951675,0.0003238652,0.003494911,0.00005835891,0.00009643977,0.0002734022,0.001649702,0.01792515,0.0004993199,0.8423534,0.04230237,0.09100354],"study_design_scores_gemma":[0.000694392,0.00008338073,0.003217215,0.0000589835,0.0000102587,0.00002992385,0.0001668066,0.9447948,0.0008115291,0.002056042,0.04763462,0.000442007],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007477207,0.0007552773,0.9314247,0.00317038,0.001795821,0.0001272688,0.000005528677,0.0006809938,0.05456284],"genre_scores_gemma":[0.7240106,0.00003363434,0.2691657,0.001599164,0.0002225345,0.000004987401,0.00008977983,0.00003224566,0.004841351],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9268697,"threshold_uncertainty_score":0.669049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0819910612534251,"score_gpt":0.3568086033172135,"score_spread":0.2748175420637884,"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."}}