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 …

Legal case retrieval, which aims to find relevant cases for a query case, plays a core role in
the intelligent legal system. Despite the success that pre-training has achieved in ad-hoc …

We summarize the 8th Competition on Legal Information Extraction and Entailment. In this
edition, the competition included five tasks on case law and statute law. The case law …

In legal case retrieval, existing work has shown that human-mediated conversational search
can improve users' search experience. In practice, a suitable workflow can provide …

Abstract Query-by-document (QBD) retrieval is an Information Retrieval task in which a seed
document acts as the query and the goal is to retrieve related documents–it is particular …

Legal case retrieval has received increasing attention in recent years. However, compared
to ad hoc retrieval tasks, legal case retrieval has its unique challenges. First, case …

Recent years have seen increasing attention on Legal Case Retrieval (LCR), a key task in
the area of Legal AI that concerns the retrieval of cases from a large legal database of …

Legal case retrieval techniques play an essential role in modern intelligent legal systems. As
an annually well-known international competition, COLIEE is aiming to achieve the state-of …

Legal Judgment Prediction (LJP) has become an increasingly crucial task in Legal AI, ie,
predicting the judgment of the case in terms of case fact description. Precedents are the …

The Competition on Legal Information Extraction/Entailment (COLIEE) is held annually to
encourage advancements in the automatic processing of legal texts. Processing legal …