A Comprehensive Evaluation of LLM Unlearning Robustness under Multi-Turn Interaction

Researchers found that machine unlearning in large language models, which aims to remove specific training data influence, is less effective in interactive settings than previously thought. Knowledge that appears forgotten in static tests can often be recovered through multi-turn conversations and self-correction interactions.