Enhancing Code Model Robustness Against Identifier Renaming via Unified Code Normalization
Jiajun Jiang, Songrui Li, Hanmo You et al.
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Preprint
Jul 2026
Evaluating Fuzz Testing for Reinforcement Learning Agents
It is shown that fuzzing-generated crashes can meaningfully improve agent robustness and enable accurate safety monitoring with strong cross-method generalization, and the benefits of combining complementary fuzzing strategies and adopting multi-level diversity analysis to achieve more comprehensive and practical RL testing.
Zhibin Kang, Hanmo You, Dong Wang et al.
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