Addressing Unwanted Information Memorization in Large Language Models with Targeted Information Forgetting Framework
Large Language Models (LLMs) tend to memorize unwanted information like private or copyrighted content, leading to privacy and legal concerns. The Targeted Information Forgetting (TIF) framework introduces a solution to unlearn unwanted information while preserving model utility, achieving state-of-the-art results in experiments.
arxiv.org1y ago
