The legal world is constantly evolving, with new laws, interpretations, and precedents emerging all the time. This poses a unique challenge for Large Language Models (LLMs) designed for legal tasks. How can these AI systems stay up-to-date with the ever-shifting landscape of legal knowledge? Researchers have introduced a new benchmark called LeKUBE (Legal Knowledge Update BEnchmark) to address this critical question. LeKUBE focuses specifically on how well LLMs can update their understanding of Chinese Criminal and Civil law. Imagine an AI lawyer needing to instantly grasp the implications of a new court ruling. LeKUBE tests this ability by simulating updates to these legal texts and then evaluating how accurately the LLM incorporates these changes. The tests cover five key dimensions: accuracy of updates, the ability to apply updates to new scenarios, how well the AI retains previous knowledge, the ability to handle large-scale legal updates, and the retention of information after multiple updates. The researchers used real-world scenarios, generating hypothetical cases and multiple-choice questions where the correct answer would change based on the new legal information. Interestingly, they discovered that simply providing the updated information alongside the question wasn't enough. The most effective methods involved fine-tuning the model or using a technique called "Self-Edit," which involves the AI generating its own practice questions and answers based on the new legal text. While the results show a considerable gap between current AI capabilities and the complex requirements of legal practice, LeKUBE offers a crucial step toward building more dynamic and reliable legal AI systems. It highlights the need for further research into how AI can truly keep pace with legal knowledge. The ultimate goal? AI legal assistants that can not only answer questions but also adapt to new legal realities in real time, making them invaluable tools for legal professionals and the public alike.