According to numerous reports, ChatGPT represents a significant breakthrough in the field of
artificial intelligence. ChatGPT is a pre-trained AI model designed to engage in natural …

Generalization to out-of-distribution (OOD) data is a capability natural to humans yet
challenging for machines to reproduce. This is because most learning algorithms strongly …

The recent breakthroughs in natural language processing for model pretraining on large
quantities of data have opened the way for similar foundation models in computer vision …

Groundbreaking language-vision architectures like CLIP and DALL-E proved the utility of
training on large amounts of noisy image-text data, without relying on expensive accurate …

The" Roaring 20s" of visual recognition began with the introduction of Vision Transformers
(ViTs), which quickly superseded ConvNets as the state-of-the-art image classification …

The scaling of Transformers has driven breakthrough capabilities for language models. At
present, the largest large language models (LLMs) contain upwards of 100B parameters …

This paper shows that masked autoencoders (MAE) are scalable self-supervised learners
for computer vision. Our MAE approach is simple: we mask random patches of the input …

Exploring large-scale pretrained foundation models is of significant interest in computer
vision because these models can be quickly transferred to many downstream tasks. This …

With the rise of powerful pre-trained vision-language models like CLIP, it becomes essential
to investigate ways to adapt these models to downstream datasets. A recently proposed …

We launch EVA, a vision-centric foundation model to explore the limits of visual
representation at scale using only publicly accessible data. EVA is a vanilla ViT pre-trained …