Automatic legal judgment prediction (LJP) has recently received increasing attention in the
natural language processing community in part because of its practical values as well as the …

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 …

Recognizing facts is the most fundamental step in making judgments, hence detecting
events in the legal documents is important to legal case analysis tasks. However, existing …

We present a benchmark suite of four datasets for evaluating the fairness of pre-trained
language models and the techniques used to fine-tune them for downstream tasks. Our …

In many jurisdictions, the excessive workload of courts leads to high delays. Suitable
predictive AI models can assist legal professionals in their work, and thus enhance and …

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 …

We report on an experiment in case outcome classification on European Court of Human
Rights cases where our model first learns to identify the convention articles allegedly …

The assessment of explainability in Legal Judgement Prediction (LJP) systems is of
paramount importance in building trustworthy and transparent systems, particularly …

Measuring the similarity between legal documents to find prior documents from a massive
collection that are similar to a current document is an essential component in legal assistant …

The law guarantees the regular functioning of the nation and society. In recent years, legal
artificial intelligence (legal AI), which aims to apply artificial intelligence techniques to …