This survey investigates the synergistic relationship between Large Language Models
(LLMs) and Knowledge Graphs (KGs), which is crucial for advancing AI's understanding …

The growing need of gaining valuable information from large collections of text data has
attracted a considerable interest from researchers in the field of natural language processing …

Classification methods based on fine-tuning pre-trained language models often require a
large number of labeled samples; therefore, few-shot text classification has attracted …

Word embeddings are widely used for diverse applications in natural language processing.
Despite extensive research, it is unclear when they succeed or fail to capture human …

Abstract Background and Objective Symptom descriptions by ordinary people are often
inaccurate or vague when seeking medical advice, which often leads to inaccurate …

In the realm of soccer analytics, the need for efficient and accurate information retrieval is
crucial. In this paper, we introduce SoccerGraphRAG, a framework designed to facilitate the …

Using the pre-trained language models to understand source codes has attracted increasing
attention from financial institutions owing to the great potential to uncover financial risks …

Using natural language processing (NLP) techniques, we conducted a preliminary
diagnosis of the disease from the patient syndrome description. Because patients are not …

While existing inference engines solved real world problems using probabilistic knowledge
representation, one challenging task is to efficiently utilize the representation under a …

Abstract “目前基于预训练语言模型的司法领域低资源法律文书命名实体识别研究主要面临两个
问题:(1) 在低资源语言中, 如维吾尔语, 法律文书相关的语料极其有限, 这种语料资源稀缺限制了 …