Stars
Persistent file-based planning for AI coding agents and long-running tasks. Crash-proof markdown plans, session recovery after /clear and compaction, per-turn re-injection against context rot, dete…
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Official implementation of AirV2X: Unified Air-Ground\\Vehicle-to-Everything Collaboration
Python sample codes and textbook for robotics algorithms.
[CVPR 2025 Highlight] Truncated Diffusion Model for Real-Time End-to-End Autonomous Driving
[Embodied-AI-Survey-2025] Paper List and Resource Repository for Embodied AI
[NeurIPS 2024 Datasets and Benchmarks Track] Closed-Loop E2E-AD Benchmark Enhanced by World Model RL Expert
The Dynamic Window Approach (DWA) planning algorithm written in C with Python Bindings
[ITSC 2024] Personalized Autonomous Driving with Large Language Models: Field Experiments
Mastering Diverse Domains through World Models
BenchMARL is a library for benchmarking Multi-Agent Reinforcement Learning (MARL). BenchMARL allows to quickly compare different MARL algorithms, tasks, and models while being systematically ground…
[TRO 2025] NeuPAN: Direct Point Robot Navigation with End-to-End Model-based Learning.
This is the official implementation of UniOcc: A Unified Benchmark for Occupancy Forecasting and Prediction in Autonomous Driving
A curated list of awesome LLM/VLM/VLA/World Model for Autonomous Driving(LLM4AD) resources (continually updated)
JMLR: OmniSafe is an infrastructural framework for accelerating SafeRL research.
Code for the MADDPG algorithm from the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"
Awesome-LLM-Robustness: a curated list of Uncertainty, Reliability and Robustness in Large Language Models
Unsloth is a local UI for training and running Gemma 4, Qwen3.6, DeepSeek, Kimi, GLM and other models.
Get up and running with Kimi-K2.6, GLM-5.2, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.
[ECCV 2024] Monocular Occupancy Prediction for Scalable Indoor Scenes
[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation
Official implementation of the paper "HUGSIM: A Real-Time, Photo-Realistic and Closed-Loop Simulator for Autonomous Driving"