Transformer architectures are highly expressive because they use self-attention
mechanisms to encode long-range dependencies in the input sequences. In this paper, we …

Legal judgment prediction (LJP) applies Natural Language Processing (NLP) techniques to
predict judgment results based on fact descriptions automatically. The present work …

Large language models (LLMs) have demonstrated strong capabilities in various aspects.
However, when applying them to the highly specialized, safe-critical legal domain, it is …

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 …

Pretrained language models (PLMs) have made significant progress on various NLP tasks
recently. However, PLMs encounter challenges when it comes to domain-specific tasks such …

The explanation of legal judgments is crucial for the transparency, fairness, and
trustworthiness, aiming to provide rationales for decision-making. While previous works …

Given the fact descriptions of legal cases, the legal judgment prediction (LJP) problem aims
to determine three judgment tasks of law articles, charges, and the term of penalty. Most …

Text generation aims to produce human-like natural language output for down-stream tasks.
It covers a wide range of applications like machine translation, document summarization …

In recent years, there has been considerable growth in the volume of legal proceedings in
Brazil. In this context, there is a lot of potential in using recent advances in Natural Language …

Multiple defendants in a criminal fact description generally exhibit complex interactions, and
cannot be well handled by existing Legal Judgment Prediction (LJP) methods which focus …