Transformer-based language models (TLMs) have widely been recognized to be a cutting-
edge technology for the successful development of deep-learning-based solutions to …

Position encoding has recently been shown to be effective in transformer architecture. It
enables valuable supervision for dependency modeling between elements at different …

Legal Artificial Intelligence (LegalAI) focuses on applying the technology of artificial
intelligence, especially natural language processing, to benefit tasks in the legal domain. In …

Legal case retrieval is of vital importance for ensuring justice in different kinds of law
systems and has recently received increasing attention in information retrieval (IR) research …

In the fast-evolving domain of artificial intelligence, large language models (LLMs) such as
GPT-3 and GPT-4 are revolutionizing the landscapes of finance, healthcare, and law …

General and legal domain LLMs have demonstrated strong performance in various tasks of
LegalAI. However, the current evaluations of these LLMs in LegalAI are defined by the …

Estimating the similarity between two legal case documents is an important and challenging
problem, having various downstream applications such as prior-case retrieval and citation …

The legal landscape encompasses a wide array of lawsuit types, presenting lawyers with
challenges in delivering timely and accurate information to clients, particularly concerning …

Transformers are not suited for processing long documents, due to their quadratically
increasing memory and time consumption. Simply truncating a long document or applying …

Since the early 1980s, the legal domain has shown a growing interest in Artificial
Intelligence approaches to tackle the increasing number of cases worldwide. TaSbeeb is a …