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Learn from Your Mistakes: Tree-like Self-Play for Secure Code LLMs

Wenqi Chen, Ziyan Zhang, Bing Wang, Lin Liu, Hengheng Zhang, Zhengsu Chen
Jun 3, 2026 at 04:00
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arXiv:2606.03489v1 Announce Type: cross Abstract: While Large Language Models (LLMs) excel in code generation, they remain prone to replicating subtle yet critical vulnerabilities endemic to their training data. Current alignment techniques, such as Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL), typically apply coarse-grained...

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