We live in exciting times for AI and Law: technical developments are moving at a breakneck
pace, and at the same time, the call for more robust AI governance and regulation grows …

The evolution of Generative Pre-trained Transformer (GPT) models has led to significant
advancements in various natural language processing applications, particularly in legal …

In this paper, we explore the application of Generative Pre-trained Transformers (GPTs) in
cross-lingual legal Question-Answering (QA) systems using the COLIEE Task 4 dataset. In …

Logic programming has long being advocated for legal reasoning, and several approaches
have been put forward relying upon explicit representation of the law in logic programming …

In the legal domain, extracting information from contracts poses significant challenges,
primarily due to the scarcity of annotated data. In such situations, leveraging large language …

Digitalization efforts often face a key challenge: business processes must not only be
efficient in achieving their goals but also adhere to legal regulations. Business process …

This paper introduces Knowledge Representation Augmented Generation (KRAG), a novel
framework designed to enhance the capabilities of Large Language Models (LLMs) within …

Abstract Named Entity Recognition (NER) models face unique challenges in the field of
legal text analysis, primarily due to the scarcity of annotated legal data. The creation of a …

This paper presents an outline of our research project developed at our research center for"
Juris-Informatics"." Juris-Informatics" is a research field based on two main topics;" Law by …

This thesis addresses the challenge of evaluating candidate logical formulas, with a specific
focus on axioms, by synergistically combining machine learning with symbolic reasoning …