Protecting the intellectual property of open-source Large Language Models (LLMs) is very
important, because training LLMs costs extensive computational resources and data …

With the rapid advancement and extensive application of artificial intelligence technology,
large language models (LLMs) are extensively used to enhance production, creativity …

Recent advances show that scaling a pre-trained language model could achieve state-of-the-
art performance on many downstream tasks, prompting large language models (LLMs) to …

Recent advances in Large Language Models (LLMs) have led to significant improvements in
natural language processing tasks, but their ability to generate human-quality text raises …

Recently, LoRA and its variants have become the de facto strategy for training and sharing
task-specific versions of large pretrained models, thanks to their efficiency and simplicity …

Training Large Language Models (LLMs) requires immense computational power and vast
amounts of data. As a result, protecting the intellectual property of these models through …

Federated Learning (FL) is a distributed paradigm that enables multiple clients to
collaboratively train a model without sharing their sensitive local data. In such a privacy …