{"id":"W3137108338","doi":"10.14722/ndss.2021.23112","title":"XDA: Accurate, Robust Disassembly with Transfer Learning","year":2021,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Office of Naval Research; Amazon Web Services; National Science Foundation","keywords":"Computer science; Byte; Task (project management); Compiler; x86; Programming language; Code (set theory); Artificial intelligence; Heuristics; Function (biology); Parallel computing; Operating system; Software","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":[0.0001370332,0.00009611378,0.00009955794,0.00004982403,0.00007489834,0.0002287344,0.0004099557,0.0000347508,0.000083479],"category_scores_gemma":[0.0001702273,0.00007518489,0.00002920882,0.0006689016,0.00001694404,0.0003758229,0.00007968747,0.0002224981,0.00008045742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000028498,"about_ca_system_score_gemma":0.0001314275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001379621,"about_ca_topic_score_gemma":0.00002052204,"domain_scores_codex":[0.9989318,0.00004022929,0.00008686802,0.0003212092,0.0003173939,0.0003024994],"domain_scores_gemma":[0.9990577,0.0003642996,0.000004751972,0.0003532952,0.0001206856,0.00009929852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003634475,0.0004097366,0.09406605,0.0002189781,0.0002845785,0.002747226,0.003831619,0.6839815,0.03065702,0.1065801,0.004582332,0.07260446],"study_design_scores_gemma":[0.003948714,0.001046213,0.2371945,0.000303899,0.00003334481,0.001116259,0.000883521,0.3528317,0.3523096,0.000330595,0.04730048,0.002701214],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1234493,0.00005786788,0.872651,0.0005008663,0.00007186687,0.00004348543,1.556911e-7,0.0004674355,0.002758049],"genre_scores_gemma":[0.961474,0.000009262897,0.03412257,0.00005983553,0.00003010686,0.00001098021,0.000001702185,0.00001389955,0.004277614],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8385285,"threshold_uncertainty_score":0.3065951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02368876500441808,"score_gpt":0.2470818798924821,"score_spread":0.223393114888064,"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."}}