The integration of Large Language Models (LLMs) and Edge Intelligence (EI) introduces a
groundbreaking paradigm for intelligent edge devices. With their capacity for human-like …

Transformer-based Large Language Models (LLMs) have been applied in diverse areas
such as knowledge bases, human interfaces, and dynamic agents, and marking a stride …

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

Ever since the Turing Test was proposed in the 1950s, humans have explored the mastering
of language intelligence by machine. Language is essentially a complex, intricate system of …

AutoGen is an open-source framework that allows developers to build LLM applications via
multiple agents that can converse with each other to accomplish tasks. AutoGen agents are …

Abstract As Large Language Models (LLMs) have shown significant intelligence, the
progress to leverage LLMs as planning modules of autonomous agents has attracted more …

In the rapidly evolving landscape of artificial intelligence (AI), generative large language
models (LLMs) stand at the forefront, revolutionizing how we interact with our data. However …

Large language models (LLMs) need knowledge updates to meet the ever-growing world
facts and correct the hallucinated responses, facilitating the methods of lifelong model …

Large language model (LLM) based agents have recently attracted much attention from the
research and industry communities. Compared with original LLMs, LLM-based agents are …

This paper focuses on task-agnostic prompt compression for better generalizability and
efficiency. Considering the redundancy in natural language, existing approaches compress …