Offline voice and text control for Unity XR scenes: the model and the Unity package.
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The Extended Reality Laboratory (XRLab) at Manisa Celal Bayar University works on virtual, augmented and mixed reality, 3D virtual environments and educational technology, and on the AI models behind them. This page lists the models and tools we release.
Maverick-4B-Unity-XR-Agent
A 4B language model that turns spoken or typed English into actions in Unity XR scenes. It picks up, places and moves objects, switches devices on and off, moves the user between rooms, and asks which object you mean when a command is unclear. It runs offline through llama.cpp and needs about 3 GB of GPU memory.
On 499 instructions written by people for the ALFRED benchmark, it chose the right action on the right object 83.8% of the time, ahead of models with up to 120B parameters. The article explains how it was trained and tested.
Releases
| Release | Type | Description |
|---|---|---|
| Maverick-4B-Unity-XR-Agent | Model | Tool calling for Unity XR scenes, GGUF |
| Maverick XR Agent for Unity | Unity package | Connects the model to your scene; installs from the Package Manager (Hugging Face mirror) |
| Offline Voice Control for Unity XR Scenes | Article | How Maverick was trained and tested |
| XRLab-SDK | Python SDK | Shows which vision-language models fit on an XR headset and what they cost to run |
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