Large Language Models (LLMs) have recently demonstrated remarkable capabilities in
natural language processing tasks and beyond. This success of LLMs has led to a large …

This paper embarks on an exploration into the Large Language Model (LLM) datasets,
which play a crucial role in the remarkable advancements of LLMs. The datasets serve as …

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 …

Transfer learning–ie, further fine-tuning a pre-trained model on a downstream task–can
confer significant advantages, including improved downstream performance, faster …

Widely used alignment techniques, such as reinforcement learning from human feedback
(RLHF), rely on the ability of humans to supervise model behavior-for example, to evaluate …

Multitask prompted finetuning (MTF) has been shown to help large language models
generalize to new tasks in a zero-shot setting, but so far explorations of MTF have focused …

Large language models (LLMs) have emerged as a widely-used tool for information
seeking, but their generated outputs are prone to hallucination. In this work, our aim is to …

Language models (LMs) now excel at many tasks such as few-shot learning, question
answering, reasoning, and dialog. However, they sometimes generate unsupported or …

Large language models (LLMs) show impressive abilities via few-shot prompting.
Commercialized APIs such as OpenAI GPT-3 further increase their use in real-world …

We propose Unified-IO, a model that performs a large variety of AI tasks spanning classical
computer vision tasks, including pose estimation, object detection, depth estimation and …