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 …

Lately, propelled by the phenomenal advances around the transformer architecture, the
legal NLP field has enjoyed spectacular growth. To measure progress, well curated and …

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 …

Legal documents, like contracts or laws, are subject to interpretation. Different people can
have different interpretations of the very same document. Large parts of judicial branches all …

The research field of Legal Natural Language Processing (NLP) has been very active
recently, with Legal Judgment Prediction (LJP) becoming one of the most extensively …

The availability of representative datasets is an essential prerequisite for many successful
artificial intelligence and machine learning models. However, in real life applications these …

This study aims at predicting the outcomes of legal cases based on the textual content of
judicial decisions. We present a new corpus of Italian documents, consisting of 226 …

The growing research field of argumentation mining (AM) in the past ten years has made it a
popular topic in Natural Language Processing. However, there are still limited studies …

Instruction tuning is an important step in making language models useful for direct user
interaction. However, many legal tasks remain out of reach for most open LLMs and there do …