Update README.md

README.md

@@ -13,7 +13,7 @@ tags:
 - multitemporal
 library_name: pytorch
 datasets:
-- IGNF/FLAIR-HUB
+- ignf/flair-hub
 ---
 
 ## Download
@@ -110,6 +110,7 @@ Below are cross-dataset evaluation results obtained with these guidelines on Tre
 ## 🚀 Getting started
 
 Prerequisites: 
+- Clone MAESTRO's [code repository](https://github.com/ignf/maestro)
 - Fetch [Dataset splits](https://huggingface.co/IGNF/MAESTRO_FLAIR-HUB_base/tree/main/dataset_splits) and move them to each dataset directory
 - Fetch [model weights](./MAESTRO_FLAIR-HUB_base/checkpoints/pretrain-epoch=99.ckpt) and move them into `/path/to/experiments/MAESTRO_FLAIR-HUB_base/checkpoints/`
 - Fetch [model configuration](./MAESTRO_FLAIR-HUB_base/.hydra/config_resolved.yaml) and move it into `/path/to/experiments/MAESTRO_FLAIR-HUB_base/.hydra/`
@@ -242,11 +243,11 @@ poetry run python main.py \
 If you use this model, please cite:
 
 ```bibtex
-@article{labatie2025maestro,
+@inproceedings{labatie2026maestro,
   title={MAESTRO: Masked AutoEncoders for Multimodal, Multitemporal, and Multispectral Earth Observation Data},
   author={Labatie, Antoine and Vaccaro, Michael and Lardiere, Nina and Garioud, Anatol and Gonthier, Nicolas},
-  journal={arXiv preprint arXiv:2508.10894},
-  year={2025}
+  booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
+  year={2026}
 }
 ```