Legal NLP refers to the application of advanced techniques to processing and analysis of legal texts. In this paper, we present a review of the relevant literature on legal NLP, and we compare existing solutions on four main tasks, that are document segmentation, information retrieval, document summarization, and knowledge extraction. In the review, we focus on how language models are currently being employed for addressing NLP in the legal field, by also highlighting challenges where improvements are still possible.