Update README.md

README.md

@@ -9,11 +9,11 @@ tags:
   - IBM
   - ESA
 ---
-[![Website](https://img.shields.io/badge/Website-TerraMind-0F62FE)](https://ibm.github.io/terramind/)
+[![Website](https://img.shields.io/badge/Website-TerraMind-0F62FE)](https://www.fast-eo.eu/terramind)
 [![arXiv](https://img.shields.io/badge/arXiv-2504.11171-b31b1b?logo=arxiv)](https://arxiv.org/abs/2504.11171)
-[![Docs](https://img.shields.io/badge/Docs-EE4B2B?logo=materialformkdocs&logoColor=fff)](https://ibm.github.io/terratorch/stable/guide/terramind/)
+[![Docs](https://img.shields.io/badge/Docs-EE4B2B?logo=materialformkdocs&logoColor=fff)](https://terrastackai.github.io/terratorch/stable/guide/terramind/)
 [![Examples](https://img.shields.io/badge/GitHub-Examples-0F62FE?logo=github)](https://github.com/IBM/terramind)
-[![Code](https://img.shields.io/badge/Code-TerraTorch-EE4B2B?logo=github)](https://github.com/IBM/terratorch/tree/main/terratorch/models/backbones/terramind)
+[![Code](https://img.shields.io/badge/Code-TerraTorch-EE4B2B?logo=github)](https://github.com/terrastackai/terratorch/tree/main/terratorch/models/backbones/terramind)
 [![ESAblog](https://img.shields.io/badge/Blog-ESA-113145)](https://www.esa.int/Applications/Observing_the_Earth/ESA_and_IBM_collaborate_on_TerraMind)
 [![IBMblog](https://img.shields.io/badge/Blog-IBM-0F62FE)](https://research.ibm.com/blog/terramind-esa-earth-observation-model)
 
@@ -51,7 +51,7 @@ Tiny can run easily on edge devices such as satellites or smartphones.
 
 ## Usage
 
-TerraMind is fully integrated into the fine-tuning package [TerraTorch](https://ibm.github.io/terratorch/). 
+TerraMind is fully integrated into the fine-tuning package [TerraTorch](https://terrastackai.github.io/terratorch/). 
 This makes it easy to initialize the pre-trained model or fine-tune it via PyTorch Lightning. 
 The weights are automatically downloaded from Hugging Face. 
 
@@ -122,7 +122,7 @@ model = BACKBONE_REGISTRY.build(
 )
 ```
 
-If you use TiM models, we recommend using the [pre-training statistics](https://github.com/IBM/terratorch/blob/a4ca8df7c7f22ddf469f372e1099157d2d7beeb2/terratorch/models/backbones/terramind/model/terramind_register.py#L111) for standardization.
+If you use TiM models, we recommend using the [pre-training statistics](https://github.com/terrastackai/terratorch/blob/main/terratorch/models/backbones/terramind/model/terramind_register.py#L145) for standardization.
 
 ### Generations
 
@@ -162,13 +162,13 @@ Already working with TerraMind? Submit your use case to the [TerraMind Blue-Sky
 
 ## Citation
 
-If you use TerraMind in your research, please cite the [TerraMind](https://arxiv.org/abs/2504.11171) pre-print.
+If you use TerraMind in your research, please cite the [TerraMind](https://arxiv.org/abs/2504.11171) paper.
 
 ```text
 @article{jakubik2025terramind,
   title={TerraMind: Large-Scale Generative Multimodality for Earth Observation},
   author={Jakubik, Johannes and Yang, Felix and Blumenstiel, Benedikt and Scheurer, Erik and Sedona, Rocco and Maurogiovanni, Stefano and Bosmans, Jente and Dionelis, Nikolaos and Marsocci, Valerio and Kopp, Niklas and others},
-  journal={arXiv preprint arXiv:2504.11171},
+  journal={IEEE/CVF International Conference on Computer Vision (ICCV)},
   year={2025}
 }
 ```