A complete survey on generative ai (aigc): Is chatgpt from gpt-4 to gpt-5 all you need?

C Zhang, C Zhang, S Zheng, Y Qiao, C Li… - arxiv preprint arxiv …, 2023 - arxiv.org
As ChatGPT goes viral, generative AI (AIGC, aka AI-generated content) has made headlines
everywhere because of its ability to analyze and create text, images, and beyond. With such …

Beyond deep reinforcement learning: A tutorial on generative diffusion models in network optimization

H Du, R Zhang, Y Liu, J Wang, Y Lin, Z Li… - arxiv preprint arxiv …, 2023 - arxiv.org
Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of
Generative Artificial Intelligence (GAI), demonstrating their versatility and efficacy across a …

On distillation of guided diffusion models

C Meng, R Rombach, R Gao… - Proceedings of the …, 2023 - openaccess.thecvf.com
Classifier-free guided diffusion models have recently been shown to be highly effective at
high-resolution image generation, and they have been widely used in large-scale diffusion …

Lion: Latent point diffusion models for 3d shape generation

A Vahdat, F Williams, Z Gojcic… - Advances in …, 2022 - proceedings.neurips.cc
Denoising diffusion models (DDMs) have shown promising results in 3D point cloud
synthesis. To advance 3D DDMs and make them useful for digital artists, we require (i) high …

Diffusion-lm improves controllable text generation

X Li, J Thickstun, I Gulrajani… - Advances in Neural …, 2022 - proceedings.neurips.cc
Controlling the behavior of language models (LMs) without re-training is a major open
problem in natural language generation. While recent works have demonstrated successes …

Flow straight and fast: Learning to generate and transfer data with rectified flow

X Liu, C Gong, Q Liu - arxiv preprint arxiv:2209.03003, 2022 - arxiv.org
We present rectified flow, a surprisingly simple approach to learning (neural) ordinary
differential equation (ODE) models to transport between two empirically observed …

High-resolution image synthesis with latent diffusion models

R Rombach, A Blattmann, D Lorenz… - Proceedings of the …, 2022 - openaccess.thecvf.com
By decomposing the image formation process into a sequential application of denoising
autoencoders, diffusion models (DMs) achieve state-of-the-art synthesis results on image …

Flexible diffusion modeling of long videos

W Harvey, S Naderiparizi, V Masrani… - Advances in …, 2022 - proceedings.neurips.cc
We present a framework for video modeling based on denoising diffusion probabilistic
models that produces long-duration video completions in a variety of realistic environments …

Structured denoising diffusion models in discrete state-spaces

J Austin, DD Johnson, J Ho, D Tarlow… - Advances in …, 2021 - proceedings.neurips.cc
Denoising diffusion probabilistic models (DDPMs)[Ho et al. 2021] have shown impressive
results on image and waveform generation in continuous state spaces. Here, we introduce …

Score-based generative modeling in latent space

A Vahdat, K Kreis, J Kautz - Advances in neural information …, 2021 - proceedings.neurips.cc
Score-based generative models (SGMs) have recently demonstrated impressive results in
terms of both sample quality and distribution coverage. However, they are usually applied …