{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001240105,0.001408897,0.0009878959,0.0008681109,0.0006705096,0.001212217,0.003229387,0.001370105,0.008625581],"category_scores_gemma":[0.003437998,0.0008105855,0.0007295795,0.0006647155,0.001072125,0.002125722,0.002451804,0.002527656,0.006430216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001072394,"about_ca_system_score_gemma":0.001978491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004003351,"about_ca_topic_score_gemma":0.005872995,"domain_scores_codex":[0.9990632,0.000113514,0.00004823336,0.0003146848,0.0003538198,0.0001065315],"domain_scores_gemma":[0.998387,0.0004180432,0.0001443673,0.000650614,0.0003240182,0.00007602457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004950106,0.0002128633,0.001643112,0.0001891502,0.00008374015,0.0001700811,0.00007917915,0.2439357,0.0197762,0.006412292,0.02706316,0.6999395],"study_design_scores_gemma":[0.00002452498,0.00006389642,0.0002352386,0.000009703033,0.000007513821,0.00006739448,0.00001677108,0.9780793,0.01103371,0.006299255,0.004147331,0.00001532866],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01377882,0.0003745272,0.9368623,0.0002108028,0.000148184,0.0001067372,0.0003091832,0.04489756,0.003311865],"genre_scores_gemma":[0.2537317,0.0002297469,0.7253467,0.000567891,0.00008281127,0.0002806345,0.002222239,0.002838253,0.01470018],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008625581,"threshold_uncertainty_score":0.02885538,"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."}}