Generative Models

REPA-E: Unlocking VAE for End-to-End Tuning of Latent Diffusion Transformers
https://github.com/End2End-Diffusion/REPA-E

Video-As-Prompt: Unified Semantic Control for Video Generation
https://github.com/bytedance/Video-As-Prompt

Calibrating Generative Models
https://github.com/smithhenryd/cgm

Continuously Augmented Discrete Diffusion model for Categorical Generative Modeling
https://arxiv.org/abs/2510.01329

Diffusion Transformers with Representation Autoencoders
https://github.com/bytetriper/RAE

DiffuseNNX library for diffusion and flow matching generative algorithms
https://github.com/willisma/diffuse_nnx

Learn to Guide Your Diffusion Model
https://arxiv.org/abs/2510.00815

STARFlow: Scaling Latent Normalizing Flows for High-resolution Image Synthesis
https://arxiv.org/abs/2506.06276

Energy-Weighted Flow Matching: Unlocking Continuous Normalizing Flows for Efficient and Scalable Boltzmann Sampling
https://arxiv.org/abs/2509.03726

Equilibrium Matching: Generative Modeling with Implicit Energy-Based Models
https://arxiv.org/abs/2510.02300

A Theoretical Analysis of Discrete Flow Matching Generative Models
https://arxiv.org/abs/2509.22623

TinyWorlds is a minimal autoregressive world model built on Google Deepmind's Genie Architecture
https://github.com/AlmondGod/tinyworlds