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 …

The evolution of network technologies has significantly transformed global communication,
information sharing, and connectivity. Traditional networks, relying on static configurations …

Trained on massive publicly available data, large language models (LLMs) have
demonstrated tremendous success across various fields. While more data contributes to …

Large language models (LLMs) are complex artificial intelligence systems capable of
understanding, generating and translating human language. They learn language patterns …

Foundation models (FMs) adapt surprisingly well to downstream tasks with fine-tuning.
However, their colossal parameter space prohibits their training on resource-constrained …

Large scale language models (LLM) have received significant attention and found diverse
applications across various domains, but their development encounters challenges in real …

Large language models (LLMs) show amazing performance on many domain-specific tasks
after fine-tuning with some appropriate data. However, many domain-specific data are …

On-device large language models (LLMs), referring to running LLMs on edge devices, have
raised considerable interest owing to their superior privacy, reduced latency, and bandwidth …

Large foundation models, including large language models (LLMs), vision transformers
(ViTs), diffusion, and LLM-based multimodal models, are revolutionizing the entire machine …

The confluence of Federated Learning (FL) and Large Language Models (LLMs) is ushering
in a new era in privacy-preserving natural language processing. However, the intensive …