Provable adversarial robustness at ImageNet scale

Tool for Bayesian inference on discrete models expressed as probabilistic programs, via generating functions

Official implementation of Inductive Moment Matching

Viewer and exporter for Unreal Engine 1-4 assets (UE Viewer).

Awesome-Long2short-on-LRMs is a collection of state-of-the-art, novel, exciting long2short methods on large reasoning models. It contains papers, codes, datasets, evaluations, and analyses.

Linear algebra foundation for the Rust programming language

A Framework for Cross-Architecture Capability Transfer and Fusion

Ghengin: A vulkan-based, shader-centric, type-heavy, Haskell game engine

MOSES Machine Learning: Meta-Optimizing Semantic Evolutionary Search. See also AS-MOSES https://github.com/opencog/asmoses but kept to guaranty backward compatibility.

DeepEP: an efficient expert-parallel communication library

Focused on fast experimentation and simplicity

The official implementation of DiM: Diffusion Mamba for Efficient High-Resolution Image Synthesis

FastVideo is a lightweight framework for accelerating large video diffusion models.

I Think, Therefore I Diffuse: Enabling Multimodal In-Context Reasoning in Diffusion Models

Partially Observable Process Gym

Solve Visual Understanding with Reinforced VLMs

Stanford NLP Python library for understanding and improving PyTorch models via interventions

[CVPR 2025] Reconstruction vs. Generation: Taming Optimization Dilemma in Latent Diffusion Models

Official repository for the Boltz-1 biomolecular interaction model

A general framework for inference-time scaling and steering of diffusion models with arbitrary rewards.

Re-implementation of Adversarial Diffusion Distillation by AMD

Pytorch implementation of Towards Consistent and Controllable Image Synthesis for Face Editing

A PyTorch implementation for exploring deep and shallow knowledge distillation (KD) experiments with flexibility

Witness the aha moment of VLM with less than $3.

Influence Functions with (Eigenvalue-corrected) Kronecker-Factored Approximate Curvature

Tools for understanding how transformer predictions are built layer-by-layer