The field of legal knowledge representation and reasoning is rapidly evolving, with a focus on developing more expressive and effective models for capturing legal concepts and relationships. Recent work has emphasized the importance of incorporating semantic extensions, deontic modal logic, and ontological frameworks to improve the accuracy and nuance of legal reasoning systems. Additionally, there is a growing interest in applying large language models to legal domains, with a recognition of the need for careful consideration of ethical governance and technical advancements to address challenges such as hallucination and explainability deficits. Notable papers in this area include: OLG++: A Semantic Extension of Obligation Logic Graph, which introduces a richer set of node and edge types to enable more nuanced representations of legal obligations and exceptions. When Large Language Models Meet Law: Dual-Lens Taxonomy, Technical Advances, and Ethical Governance, which establishes a comprehensive review of large language models applied within the legal domain and pioneers an innovative dual lens taxonomy.