diffusion-transformers

[ECCV 2026] Official implementation of "HRDiT: Training-Free High-Resolution Image Generation with Off-the-Shelf Diffusion Transformer Models"

[NeurIPS 2025 Oral] Official Code for Exploring Diffusion Transformer Designs via Grafting

FastCache: Fast Caching for Diffusion Transformer Through Learnable Linear Approximation [Efficient ML Model]

edge-dit.cpp — a native C/C++ inference engine for Diffusion Transformers (DiT), designed for local and resource-constrained devices with automatic VRAM-aware precision, placement, and offloading.

WorldGuide: Goal-Directed Video World Model for Procedural Task Execution.

Official repository for "Persistence Forcing: Exploiting Feature Specialization in Pixel-Space Diffusion"

Educational, modular, and high-performance Diffusion Transformers (DiT) in JAX and Flax NNX.

Official implementation of Training-Free Hidden-State Refinement for Flow-Matching Image Generators

Official repository for the "LAViG-FLOW: Latent Autoregressive Video Generation for Fluid Flow Simulations" paper.

Viggle-Animate in one ComfyUI node, on an INT8 checkpoint, with automatic attention routing. Weight + model card: https://huggingface.co/aireet/viggle-animate-workflow

Official AutoTarget implementation: solver-aware cache target selection for few-step diffusion transformers (submitted to ICLR 2027).

Official implementation of PrediT (ACM MM 2026): training-free linear multistep feature forecasting for efficient diffusion transformers.

Official code, locked protocols, and audit artifacts for "Jev-Routed Temporal Granularity with Recovery and Hysteresis for Causal Video Generation": per-segment fine/coarse/hold routing for Causal-rCM (Wan2.1-1.3B) via the Jev oracle, with two-GPU (T4/A100) feasibility audits.

Code release for DIET: DeletIon-response Expert Trimming for Video Diffusion Transformers

SAEP-SVD: Feature-preserving SVD distillation for High-Rank DiT models beyond the Eckart-Young theorem (Z-Image / HighDream).

Log-linear sparse attention (coarse-to-fine hierarchical top-k with KV enrichment) plus a small pixel-space diffusion transformer, in MLX.

Compute-optimal data selection, adaptation, evaluation, and systems engineering for video-generation models.

基于 bytetriper/RAE 的个人研究工作区，记录 Representation Autoencoders 相关实验；非官方仓库。

This repository implements multiple generative diffusion frameworks (EDM, Consistency Models, etc.). It also implements some architectures (U-Net, Diffusion Transformers, etc.).

Evaluation of Diffusion & Transformer-Based Generative Models. Forked repository of the 18Dec2025 version of our group work from https://github.com/juhimgupta/F25-Deep-Learning-Project.