Topic
knowledge editing
LOKI Memory-Free Method Improves Lifelong Knowledge Editing in Language Models by 14%
Researchers introduce LOKI, a memory-free method for lifelong knowledge editing in language models. It uses dynamic layer selection via the Hilbert-Schmidt Independence Criterion and projects gradient updates onto the null-space of model weights, eliminating the need for previous knowledge access. Experiments show up to 14% improvement in average accuracy over existing approaches.
Edit Knowledge, Not Just Facts via Multi-Step Reasoning over Background Stories
According to a new research paper on arXiv, enabling AI systems to update knowledge and apply it during reasoning remains a challenge. The authors argue that knowledge update is a reasoning problem, not memorization, and propose a training strategy using background stories and multi-step reasoning questions. Experiments show improved performance on challenging questions requiring combining multiple new facts.