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What You See Is What You Get? It Is Not the Case! Detecting Misleading Icons for Mobile Applications., , , , , , и . ISSTA, стр. 538-550. ACM, (2023)Topic Memory Networks for Short Text Classification., , , , , и . EMNLP, стр. 3120-3131. Association for Computational Linguistics, (2018)On the Reproducibility and Replicability of Deep Learning in Software Engineering., , , , , и . ACM Trans. Softw. Eng. Methodol., 31 (1): 15:1-15:46 (2022)Prompt Tuning in Code Intelligence: An Experimental Evaluation., , , , , и . IEEE Trans. Software Eng., 49 (11): 4869-4885 (ноября 2023)What You Say and How You Say it: Joint Modeling of Topics and Discourse in Microblog Conversations., , , , , и . CoRR, (2019)What Changed Your Mind: The Roles of Dynamic Topics and Discourse in Argumentation Process., , , , , и . WWW, стр. 1502-1513. ACM / IW3C2, (2020)An Empirical Study of Common Challenges in Developing Deep Learning Applications., , , , и . ISSRE, стр. 104-115. IEEE, (2019)Exact Solutions for the Complex Ginzburg-Landau Equation., , , и . ICEIS (4), стр. 675-677. SciTePress, (2011)CORE: Automating Review Recommendation for Code Changes., , , , и . SANER, стр. 284-295. IEEE, (2020)Emerging app issue identification from user feedback: experience on WeChat., , , , , , и . ICSE (SEIP), стр. 279-288. IEEE / ACM, (2019)