Recent advancements in Large Language Models (LLMs) have led to models containing billions or even trillions of parameters, achieving remarkable performance across domains. However, their massive size poses challenges in practical deployment due to stringent hardware...

Despite the impressive capabilities of LLMs like GPT-4 and Llama-2, they require fine-tuning with tailored data for specific business needs, exposing them to safety threats such as the Fine-tuning based Jailbreak Attack (FJAttack). Incorporating even a few harmful...

Artificial intelligence has shifted towards making large language models (LLMs) more interactive and versatile. This new wave of innovation seeks to break down the barriers between humans and machines, crafting systems that not only understand complex instructions but...

Developing efficient and powerful large language models (LLMs) represents a frontier of innovation. These models have relied on the Transformer architecture, celebrated for its ability to understand and generate human-like text. However, as these models scale, they...

Despite the significant strides in large language models (LLMs) such as ChatGPT, Llama2, Vicuna, and Gemini, they grapple with safety issues. This paper introduces a novel safety-aware decoding technique, SafeDecoding, which aims to protect LLMs from jailbreak...

In the domain of biotechnology, the intersection of machine learning and genomics has sparked a revolutionary paradigm, particularly in the modeling of DNA sequences. This interdisciplinary approach addresses the intricate challenges posed by genomic data, which...