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Dilated residual networks with multi-level attention for speaker verification., , , , and . Neurocomputing, (2020)Early prediction for mode anomaly in generative adversarial network training: An empirical study., , , , , and . Inf. Sci., (2020)Automatic Construction of Callback Model for Android Application., , , , , and . ICECCS, page 231-234. IEEE Computer Society, (2016)AutoPer: Automatic Recommender for Runtime-Permission in Android Applications., , , , , , and . COMPSAC (1), page 107-116. IEEE, (2019)Vector-Based Attentive Pooling for Text-Independent Speaker Verification., , , , and . INTERSPEECH, page 936-940. ISCA, (2020)App genome: callback sequencing in Android., , , , , , and . ICSE (Companion Volume), page 149-151. IEEE Computer Society, (2017)Deep Attentive Factorization Machine for App Recommendation Service., , , , , and . ICWS, page 134-138. IEEE, (2019)DALT: Deep Activity Launching Test via Intent-Constraint Extraction., , , , and . ISSRE, page 482-493. IEEE, (2022)Callback2Vec: Callback-aware hierarchical embedding for mobile application., , , , and . Inf. Sci., (2021)Sharing runtime permission issues for developers based on similar-app review mining., , , , , , and . J. Syst. Softw., (2022)