This survey addresses the crucial issue of factuality in Large Language Models (LLMs). As
LLMs find applications across diverse domains, the reliability and accuracy of their outputs …

Despite the advancements of open-source large language models (LLMs), eg, LLaMA, they
remain significantly limited in tool-use capabilities, ie, using external tools (APIs) to fulfill …

The proliferation of Large Language Models (LLMs) has s fueled a shift in robot learning
from automation towards general embodied Artificial Intelligence (AI). Adopting foundation …

Leveraging Large Language Models as recommenders, referred to as LLMRec, is gaining
traction and brings novel dynamics for modeling user preferences, particularly for cold-start …

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 …

In customer service technical support, swiftly and accurately retrieving relevant past issues is
critical for efficiently resolving customer inquiries. The conventional retrieval methods in …

The adoption of large language models (LLMs) in healthcare demands a careful analysis of
their potential to spread false medical knowledge. Because LLMs ingest massive volumes of …

Large Language Model (LLM) agents significantly extend the capabilities of standalone
LLMs, empowering them to interact with external tools (eg, APIs, functions) and complete …

Urban environments, characterized by their complex, multi-layered networks encompassing
physical, social, economic, and environmental dimensions, face significant challenges in the …

Transformer architectures have revolutionized natural language processing through their
ability to handle longrange dependencies and generate contextually coherent text. Despite …