Large language models (LLMs) demonstrate powerful capabilities, but they still face
challenges in practical applications, such as hallucinations, slow knowledge updates, and …

Large language models (LLMs), such as GPT4 and LLaMA, are creating significant
advancements in natural language processing, due to their strong text encoding/decoding …

Large language models (LLMs), such as ChatGPT and GPT4, are making new waves in the
field of natural language processing and artificial intelligence, due to their emergent ability …

Large language model (LLM) based knowledge graph completion (KGC) aims to predict the
missing triples in the KGs with LLMs. However, research about LLM-based KGC fails to …

This systematic literature review comprehensively examines the application of Large
Language Models (LLMs) in forecasting and anomaly detection, highlighting the current …

Large language models (LLMs) have shown remarkable generalization capability with
exceptional performance in various language modeling tasks. However, they still exhibit …

Recently, Retrieval-Augmented Generation (RAG) has achieved remarkable success in
addressing the challenges of Large Language Models (LLMs) without necessitating …

Artificial General Intelligence (AGI) has revolutionized numerous fields, yet its integration
with graph data, a cornerstone in our interconnected world, remains nascent. This paper …

In recent years, generative artificial intelligence models, represented by Large Language
Models (LLMs) and Diffusion Models (DMs), have revolutionized content production …

Graph Neural Networks (GNNs) have become increasingly important due to their
representational power and state-of-the-art predictive performance on many fundamental …