The advent of large language models (LLMs) and their adoption by the legal community has
given rise to the question: what types of legal reasoning can LLMs perform? To enable …

Legal syllogism is a form of deductive reasoning commonly used by legal professionals to
analyze cases. In this paper, we propose legal syllogism prompting (LoT), a simple …

With the emergence of numerous legal LLMs, there is currently a lack of a comprehensive
benchmark for evaluating their legal abilities. In this paper, we propose the first Chinese …

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 …

Legal judgment assistants are developing fast due to impressive progress of large language
models (LLMs). However, people can hardly trust the results generated by a model without …

Recent strides in Large Language Models (LLMs) have saturated many NLP benchmarks
(even professional domain-specific ones), emphasizing the need for novel, more …

The task of Prior Case Retrieval (PCR) in the legal domain is about automatically citing
relevant (based on facts and precedence) prior legal cases in a given query case. To further …

The civil case judgment prediction (CCJP) task involves automatically determining whether
the plea of a plaintiff should be supported by analyzing the given civil case materials …

Governments increasingly use algorithms to inform or supplant decision-making. Artificial
Intelligence systems in particular are considered objective, consistent and efficient decision …

Abstract Federated Class-Incremental Learning (FCIL) focuses on continually transferring
the previous knowledge to learn new classes in dynamic Federated Learning (FL). However …