Enhancing Continual Learning for Software Vulnerability Prediction: Addressing Catastrophic Forgetting via Hybrid-Confidence-Aware Selective Replay for Temporal LLM Fine-Tuning

Researchers developed Hybrid Class-Aware Selective Replay (Hybrid-CASR), a continual learning method that improves AI-based software vulnerability detection by addressing catastrophic forgetting in temporal scenarios. The method achieved 0.667 Macro-F1 score while reducing training time by 17% compared to baseline approaches on CVE data from 2018-2024.