Machine-learning-based text classification is one of the leading research areas and has a
wide range of applications, which include spam detection, hate speech identification …

In the last years, the legal domain has been revolutionized by the use of Information and
Communication Technologies, producing large amount of digital information. Legal …

This study aims to develop a system for automatically correcting spelling errors in Persian
texts using two approaches: one that relies on rules and a common spelling mistake list and …

The surge in legal text production has amplified the workload for legal professionals, making
many tasks repetitive and time-consuming. Furthermore, the complexity and specialized …

In this paper, we propose a Legal Rule Classification (LRC) task using one of the most
discussed language model in the field of Artificial Intelligence, namely GPT-3, a generative …

We present the first comprehensive empirical evaluation of pre-trained language models
(PLMs) for legal natural language processing (NLP) in order to examine their effectiveness …

Automatic legal text classification systems have been proposed in the literature to address
knowledge extraction from judgments and detect their aspects. However, most of these …

Selecting the right retail business for a location is crucial for the success of a business
because it determines the likelihood of favourable return on investment. One common …

This paper presents the results of the LegalLens Shared Task, focusing on detecting legal
violations within text in the wild across two sub-tasks: LegalLens-NER for identifying legal …

Abstract Multi-Label Text Classification (MLTC) is one of the most import research of natural
language processing. Although Deep Learning (DL) models have been widely applied to …