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keon/awesome-physical-ai

0
View on GitHub↗
304 stars·31 forks·CC0-1.0·15 views

Awesome Physical Ai

A curated list of academic papers and resources on Physical AI — focusing on Vision-Language-Action (VLA) models, world models, embodied ai, and robotic foundation models.

Features

  • Awesome List - A community-curated directory that catalogs and links out to other open-source projects, rather than a standalone tool you run yourself.
  • Curated Research Lists - Resources covering the intersection of physical systems and artificial intelligence.
  • Reference Lists - Academic papers on Physical AI.

Star history

Star history chart for keon/awesome-physical-aiStar history chart for keon/awesome-physical-ai

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Projects sharing features with Awesome Physical Ai

These projects share indexed features with Awesome Physical Ai. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • milkclouds/awesome-vla-studyMilkClouds avatar

    MilkClouds/awesome-vla-study

    287View on GitHub↗

    A structured reading list on Vision-Language-Action (VLA) models — from diffusion/flow matching foundations through state-of-the-art robot foundation model architectures to data scaling, RL fine-tuning, and world models. Papers in reading order.

    View on GitHub↗287
  • josephmisiti/awesome-machine-learningjosephmisiti avatar

    josephmisiti/awesome-machine-learning

    72,867View on GitHub↗

    This project is a comprehensive, community-driven directory of machine learning resources, software libraries, and educational materials. It serves as a centralized knowledge base for developers and researchers, organizing tools and frameworks by their primary programming language and technical domain to simplify discovery across the artificial intelligence ecosystem. The collection distinguishes itself by providing a cross-language development index that spans diverse programming environments, including C, C++, Rust, Clojure, and Python. It covers a wide range of specialized capabilities, fr

    Python
    View on GitHub↗72,867
  • christoschristofidis/awesome-deep-learningChristosChristofidis avatar

    ChristosChristofidis/awesome-deep-learning

    27,569View on GitHub↗

    This project is a curated directory of resources, libraries, and frameworks designed to support the development, training, and deployment of neural network models. It serves as a comprehensive guide for navigating the machine learning ecosystem, providing structured access to software utilities and research materials. The directory distinguishes itself by aggregating tools across the entire machine learning lifecycle, ranging from data management and experiment tracking to production-ready model deployment. It functions as a central hub for discovering both foundational academic research and

    awesomeawesome-listdeep-learning
    View on GitHub↗27,569
  • aoqunjin/awesome-vla-post-trainingAoqunJin avatar

    AoqunJin/Awesome-VLA-Post-Training

    197View on GitHub↗

    A collection of vision-language-action model post-training methods.

    View on GitHub↗197
Compare all 30 related projects→

Frequently asked questions

What does keon/awesome-physical-ai do?

A curated list of academic papers and resources on Physical AI — focusing on Vision-Language-Action (VLA) models, world models, embodied ai, and robotic foundation models.

What are the main features of keon/awesome-physical-ai?

The main features of keon/awesome-physical-ai are: Awesome List, Curated Research Lists, Reference Lists.

Which projects share features with keon/awesome-physical-ai?

Projects with overlapping indexed features include: milkclouds/awesome-vla-study — A structured reading list on Vision-Language-Action (VLA) models — from diffusion/flow matching foundations through… josephmisiti/awesome-machine-learning — This project is a comprehensive, community-driven directory of machine learning resources, software libraries, and… christoschristofidis/awesome-deep-learning — This project is a curated directory of resources, libraries, and frameworks designed to support the development,… fkromer/awesome-gazebo — Gazebo, the simulation framework for ROS1 and ROS2 is awesome! dh-tech/awesome-digital-humanities — Software for humanities scholars using quantitative or computational methods. aoqunjin/awesome-vla-post-training — A collection of vision-language-action model post-training methods.