Question about initial success rate in Figure 4 (0-step performance before training) #43

Hi, thank you very much for releasing this great work and the codebase.

I have a question regarding Figure 4 in the paper. In the plot, the success rate at step 0 (before any RL training) is already around 0.2–0.6, depending on the task. However, in the franka_walkthrough.md documentation, it seems that the model is randomly initialized and there is no explicit pretraining or warm-start stage mentioned.

I would like to ask:

• How is the initial policy (at step 0) able to achieve a non-zero success rate?

• Did you use any kind of offline BC pretraining, imitation initialization, or previously collected policy checkpoints when generating the results in Figure 4?

• Or did the authors observe non-zero success rate even with a purely random-initialized policy?
  (In my experiments, a random-init model makes the arm move unpredictably and has ~0 success rate.)

I am probably missing something, so any clarification would be greatly appreciated.
Thanks again for your excellent work!