Large Language Models (LLMs) demonstrate impressive capabilities across various fields,
yet their increasing use raises critical security concerns. This article reviews recent literature …

The increasing demand for customized Large Language Models (LLMs) has led to the
development of solutions like GPTs. These solutions facilitate tailored LLM creation via …

With significant advancements in Transformers LLMs, NLP has extended its reach into many
research fields due to its enhanced capabilities in text generation and user interaction. One …

Large Language Models (LLMs), which bridge the gap between human language
understanding and complex problem-solving, achieve state-of-the-art performance on …

Recently, various parameter-efficient fine-tuning (PEFT) strategies for application to
language models have been proposed and successfully implemented. However, this raises …

Neural style transfer (NST) generates new images by combining the style of one image with
the content of another. However, unauthorized NST can exploit artwork, raising concerns …

Federated Learning (FL) has gained prominence as a method for training models on edge
computing devices, enabling the preservation of data privacy by eliminating the need to …

Large language models (LLMs) have transformed the development of embodied
intelligence. By providing a few contextual demonstrations, developers can utilize the …

In the burgeoning field of Large Language Models (LLMs), developing a robust safety
mechanism, colloquially known as" safeguards" or" guardrails", has become imperative to …

The rapid advancements in large language models (LLMs) have opened new avenues
across various fields, including cybersecurity, which faces an ever-evolving threat landscape …