Official implementation of Learning Athletic Humanoid Tennis Skills from Imperfect Human Motion Data

CLI-Anything: Making ALL Software Agent-Native

Access 175+ robot descriptions from the main Python robotics frameworks

A lightweight, AI-native training framework for large language models. Designed for fast iteration, reproducible experiments, and modular configuration across SFT, RLVR, and evaluation workflows.

[ICLR 2026] Disentangled Robot Learning via Separate Forward and Inverse Dynamics Pretraining

Your own personal AI assistant. Any OS. Any Platform. The lobster way. 🦞

VLA-JEPA: Enhancing Vision-Language-Action Model with Latent World Model

Fast, Sharp & Reliable Agentic Intelligence

Step3-VL-10B: A compact yet frontier multimodal model achieving SOTA performance at the 10B scale, matching open-source models 10-20x its size.

Holistic Evaluation of Multimodal LLMs on Spatial Intelligence

HY-Motion model for 3D human motion or 3D character animation generation.

Native and Compact Structured Latents for 3D Generation

An Open Phone Agent Model & Framework. Unlocking the AI Phone for Everyone

[CVPR 2026] G2VLM: Geometry Grounded Vision Language Model with Unified 3D Reconstruction and Spatial Reasoning

Are Video Models Ready as Zero-shot Reasoners?

Depth Anything 3

Humanoid Robots Resources

Code for "PHUMA: Physically-Grounded Humanoid Locomotion Dataset"

[Neurips DB 2025] PartNeXt: A Next-Generation Dataset for Fine-Grained and Hierarchical 3D Part Understanding

NORA: A Small Open-Sourced Generalist Vision Language Action Model for Embodied Tasks

StarVLA: A Lego-like Codebase for Vision-Language-Action Model Developing

Reasoning in Space via Grounding in the World (ICLR 2025)

[PKU EPIC Lab] 面向小白的具身智能入门指南

Isaac Lab API, powered by MuJoCo-Warp, for RL and robotics research.

Official implementation of OpenTrack.

InternVLA-M1: A Spatially Guided Vision-Language-Action Framework for Generalist Robot Policy

A Paper List for Humanoid Robot Learning.

A curated list of behavior(al) foundation model (BFM) papers, articles, tutorials, slides and projects

[ICCV 2025] Towards More Diverse and Challenging Pre-training for Point Cloud Learning: Self-Supervised Cross Reconstruction with Decoupled Views