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

Learn from Your Mistakes: Tree-like Self-Play for Secure Code LLMs 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 optimization at the sequence level. This approach often fails to address the localized na