NVIDIA / NVIDIA/cosmos-framework

Cosmos3-Edge: is the shipped LIBERO 10D representation supported by the public forward-dynamics checkpoint?

Open
#249 3 comments 0 reactions 3 assignees View on GitHub

@ychao-nvidia is already working on this.

Since Sep 11, 2026.

Dominant language
Python
Stars
535
Forks
148
Avg merge
13h 37m
Merged PRs (30d)
35

Description

Hello, I would like to clarify the checkpoint-specific input contract before doing further forward-dynamics experiments.

For nvidia/Cosmos3-Edge revision a9d944e2c6a1bf9f48b92ad16348e70c5f1836ba, is the libero domain trained/validated for forward dynamics with the shipped frame_wise_relative 10D control representation and global_raw quantile statistics, or is this loader only infrastructure for post-trained checkpoints?

The code being compared is pinned to cosmos-framework revision fa1881878ab9b234583d89319d56c7903be5161d. I understand that a supported loader and a LIBERO policy post-training recipe do not by themselves establish that the generic Edge checkpoint is trained for this forward-dynamics use.

  1. If supported, which checkpoint-specific recipe defines normalization, frame timing, rotation convention, gripper convention, concat-view orientation/resizing, and prompt formatting? Is there a matched LIBERO forward-dynamics input/output example?
  2. If not, is an NVIDIA-released LIBERO forward-dynamics checkpoint available or planned?
  3. Which action-conditioned adaptation recipe is validated for Edge rather than Nano?

This question is specifically about external candidate actions conditioning future observations, not policy success rates or generic image-to-video quality. Thank you.

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Assessment

This issue has not been assessed yet.

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.