Large Language Models (LLMs), built upon Transformer-based architectures with massive
pretraining on diverse data, have not only revolutionized natural language processing but …

Despite the success in large-scale text-to-image generation and text-conditioned image
editing, existing methods still struggle to produce consistent generation and editing results …

Despite the stunning ability to generate high-quality images by recent text-to-image models,
current approaches often struggle to effectively compose objects with different attributes and …

Attaining a high degree of user controllability in visual generation often requires intricate,
fine-grained inputs like layouts. However, such inputs impose a substantial burden on users …

Recently, diffusion models have achieved remarkable success in text-to-image generation,
enabling the creation of high-quality images from text prompts and various conditions …

Diffusion models excel at text-to-image generation, especially in subject-driven generation
for personalized images. However, existing methods are inefficient due to the subject …

Neural compression is the application of neural networks and other machine learning
methods to data compression. Recent advances in statistical machine learning have opened …

Recent text-to-image diffusion models have demonstrated an astonishing capacity to
generate high-quality images. However, researchers mainly studied the way of synthesizing …

The generative AI revolution has recently expanded to videos. Nevertheless, current state-of-
the-art video models are still lagging behind image models in terms of visual quality and …

Deep generative models have unlocked another profound realm of human creativity. By
capturing and generalizing patterns within data, we have entered the epoch of all …