Recently, ChatGPT, along with DALL-E-2 and Codex, has been gaining significant attention
from society. As a result, many individuals have become interested in related resources and …

As information exists in various modalities in real world, effective interaction and fusion
among multimodal information plays a key role for the creation and perception of multimodal …

Abstract We present the Pathways [1] Autoregressive Text-to-Image (Parti) model, which
generates high-fidelity photorealistic images and supports content-rich synthesis involving …

Transformer is a promising neural network learner, and has achieved great success in
various machine learning tasks. Thanks to the recent prevalence of multimodal applications …

Self-supervised pre-training techniques have achieved remarkable progress in Document
AI. Most multimodal pre-trained models use a masked language modeling objective to learn …

Despite thousands of researchers, engineers, and artists actively working on improving text-
to-image generation models, systems often fail to produce images that accurately align with …

Text-to-image generation has traditionally focused on finding better modeling assumptions
for training on a fixed dataset. These assumptions might involve complex architectures …

Existing methods for vision-and-language learning typically require designing task-specific
architectures and objectives for each task. For example, a multi-label answer classifier for …

As transformer evolves, pre-trained models have advanced at a breakneck pace in recent
years. They have dominated the mainstream techniques in natural language processing …

Image inpainting has made significant advances in recent years. However, it is still
challenging to recover corrupted images with both vivid textures and reasonable structures …