Large Language Models (LLMs) have recently demonstrated remarkable capabilities in
natural language processing tasks and beyond. This success of LLMs has led to a large …

Exabytes of data are generated daily by humans, leading to the growing needs for new
efforts in dealing with the grand challenges for multi-label learning brought by big data. For …

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 …

Pre-trained models have achieved state-of-the-art results in various Natural Language
Processing (NLP) tasks. Recent works such as T5 and GPT-3 have shown that scaling up …

The goal of text ranking is to generate an ordered list of texts retrieved from a corpus in
response to a query. Although the most common formulation of text ranking is search …

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

Legal artificial intelligence (LegalAI) aims to benefit legal systems with the technology of
artificial intelligence, especially natural language processing (NLP). Recently, inspired by …

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 …

While significant progress has been made on the task of Legal Judgment Prediction (LJP) in
recent years, the incorrect predictions made by SOTA LJP models can be attributed in part to …

The scaling of large language models has greatly improved natural language
understanding, generation, and reasoning. In this work, we develop a system that trained a …