Robbyant/lingbot-va

Health v2 · maintenance only

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Adoption not part of the score

1806 stars · 164 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

LingBot-VA is an autoregressive diffusion framework that unifies video world modeling and robot policy learning in a single interleaved video-action sequence. It provides pretrained weights, inference, and post-training code for generalist robot manipulation control.

Use cases

• train a video-action world model for robot manipulation
• evaluate a generalist robot policy on LIBERO and RoboTwin 2.0 benchmarks
• post-train a robot foundation model on custom demonstration data
• predict future video frames and actions for closed-loop robot control
• run image-to-video-action generation for long-horizon manipulation tasks

When to choose

• you need a state-of-the-art generalist manipulation policy with world-model reasoning
• you want to post-train a pretrained video-action model on your own robot datasets
• you need long-horizon, precision, or deformable-object manipulation with strong generalization

When to avoid

• you need a lightweight policy for low-compute embedded robot hardware
• you only need classical motion planning or control without learned models
• you lack GPU resources for large diffusion model inference and training

Facets

library · maturity active

machine-learning deep-learning llm-inference simulation robotics robotics machine-learning deep-learning artificial-intelligence simulation python world-model video-action-model robot-control diffusion-policy autoregressive embodied-ai manipulation libero robotwin linux gpu docker

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