Hi MONAI team,

I’m trying to understand the origin of the pretrained weight:
ssl_pretrained_weights.pth (from MONAI-extra-test-data, ~719MB).

From the checkpoint structure, it contains:

• encoder.*
• decoder*
• out.conv.*
• encoder.mask_token

which looks like a full encoder-decoder model.

I found the following description in the tutorial README:
https://github.com/Project-MONAI/tutorials/blob/main/self_supervised_pretraining/swinunetr_pretrained/README.md

"The entire SwinUNETR model including encoder and decoder was trained end-to-end using self-supervised learning techniques as outlined in [1]."

However, it is unclear what [1] refers to in terms of actual training code or pipeline.

Could you please help clarify:

1. What exactly does reference [1] correspond to?
   (Is it a specific paper, or an internal training implementation?)

2. Was ssl_pretrained_weights.pth trained using the
   research-contributions/SwinUNETR/Pretrain (SSLHead: rotation + contrastive + reconstruction),
   or a different encoder-decoder / autoencoder-style pretraining pipeline?

A short clarification would already help a lot.

Thanks!