Despite providing unparalleled connectivity and convenience, the exponential growth of the
Internet of Things (IoT) ecosystem has triggered significant cybersecurity concerns. These …

Large language models (LLMs) are increasingly adopted in educational contexts to provide
personalized support to students and teachers. The unprecedented capacity of LLM‐based …

Modern artificial intelligence (AI) systems are powered by foundation models. This paper
presents a new set of foundation models, called Llama 3. It is a herd of language models …

Efficient fine-tuning is vital for adapting large language models (LLMs) to downstream tasks.
However, it requires non-trivial efforts to implement these methods on different models. We …

Retrieval-Augmented Generation (RAG) has recently emerged as a method to extend
beyond the pre-trained knowledge of Large Language Models by augmenting the original …

Scientific discoveries often hinge on synthesizing decades of research, a task that potentially
outstrips human information processing capacities. Large language models (LLMs) offer a …

Before we start thinking about (deep) generative modeling, let us consider a simple
example. Imagine we have trained a deep neural network that classifies images (x∈ ℤ D) of …

We introduce Moshi, a speech-text foundation model and full-duplex spoken dialogue
framework. Current systems for spoken dialogue rely on pipelines of independent …

Language models (LMs) have become ubiquitous in both NLP research and in commercial
product offerings. As their commercial importance has surged, the most powerful models …

Recent advancements in artificial intelligence have sparked interest in the parallels between
large language models (LLMs) and human neural processing, particularly in language …