Few-shot learning (FSL) has emerged as an effective learning method and shows great
potential. Despite the recent creative works in tackling FSL tasks, learning valid information …

Machine learning has been highly successful in data-intensive applications but is often
hampered when the data set is small. Recently, Few-shot Learning (FSL) is proposed to …

Text classification is the most fundamental and essential task in natural language
processing. The last decade has seen a surge of research in this area due to the …

Legal Artificial Intelligence (LegalAI) focuses on applying the technology of artificial
intelligence, especially natural language processing, to benefit tasks in the legal domain. In …

Background: Few-shot learning (FSL) is a class of machine learning methods that require
small numbers of labeled instances for training. With many medical topics having limited …

Text classification is the most fundamental and essential task in natural language
processing. The last decade has seen a surge of research in this area due to the …

NLP has achieved great progress in the past decade through the use of neural models and
large labeled datasets. The dependence on abundant data prevents NLP models from being …

Legal judgment prediction is the task of automatically predicting the outcome of a court case,
given a text describing the case's facts. Previous work on using neural models for this task …

Abstract Legal Judgment Prediction (LJP) aims to predict the judgment result based on the
facts of a case and becomes a promising application of artificial intelligence techniques in …

In this paper, we introduce the\textbf {C} hinese\textbf {AI} and\textbf {L} aw challenge
dataset (CAIL2018), the first large-scale Chinese legal dataset for judgment …