ULTRAEDIT is a novel solution for model editing in large language models (LLMs) that is training-, subject-, and memory-free, making it well-suited for real-world lifelong model editing.
ULTRAEDIT performs editing using lightweight linear algebra operations to compute parameter shifts efficiently, achieving editing speeds over 7 times faster than the previous state-of-the-art method.
It employs a lifelong normalization strategy to adapt to distributional shifts and maintain consistency over time, enabling it to edit a 7B LLM on a 24GB consumer-grade GPU with minimal VRAM consumption.
Experiments on diverse datasets and models demonstrate that ULTRAEDIT consistently outperforms other methods in model editing scenarios, supporting up to 1M edits while maintaining high accuracy.