Describe the Compact Action Expert and its intended use.

README.md

@@ -17,7 +17,11 @@ A latent world-action policy for the [LIBERO](https://github.com/Lifelong-Robot-
 
 Code: [AMD-AGI/faster-action-models](https://github.com/AMD-AGI/faster-action-models).
 
-Each 32-step action chunk is encoded as 8 latent tokens of width 16.
+Part of the [Compact Action Expert (CAE) collection](https://huggingface.co/collections/amd/compact-action-expert-cae-6ace112e7bd665ff8c107ed2).
+
+## Model
+
+The Compact Action Expert combines a 32-dimensional action expert (about 30M parameters) with a suite-conditioned K8 × d16 action VAE. The VAE encodes each 32 × 7 action chunk as 8 latent tokens of width 16, and the action expert denoises those latent chunks.
 
 ## Files
 
@@ -53,7 +57,7 @@ LIBERO simulator assets, BDDL task files, and initial states are also required.
 
 ## Intended use
 
-Research on world-action models and robot-policy inference, in simulation.
+Research on world-action models and robot-policy inference efficiency, in simulation.
 
 ## Limitations