Jingyuan Tian

A Robust Unlearning Method with Adaptive Knowledge Guidance and Memory Preservation

Machine unlearning has emerged as a promising approach to remove specific knowledge from large language models (LLMs), especially for safety-critical applications. However, existing representation-based methods lack guidance for selecting representation locations to unlearn (RMU), thus lacking preci