Update README.md

README.md

@@ -16,24 +16,13 @@ The model was pre-trained in partnership with Jülich Supercomputing Centre (For
 ###  🎉  TerraMind has been accepted at ICCV 2025
 We’re honored to present our work at one of the most prestigious conferences in computer vision. Stay tuned for more details!
 
-###  🎉  MS-CLIP has been accepted at ECML 2025
-We’re honored to present our work at one of the most prestigious conferences on machine learning. Stay tuned for more details!
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-###  🎉  TerraMesh has been accepted at CVPR EarthVision 2025
-We’re honored to present our work at one of the most well-known workshops for Earth observation. Stay tuned for more details!
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 ###  🤝 Open Source
 
 The FAST-EO partners and ESA Φ-lab are committed to Open Source, sharing knowledge, and driving innovation for the geospatial domain.
 
 ###  📚 Papers and Resources
 
-Explore the technical paper detailing TerraMind's architecture and applications [here](https://arxiv.org/abs/2504.11171). Details on MS-CLIP can be found [here](https://arxiv.org/pdf/2503.15969).
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-###  📊 Upcoming Models and Datasets
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-Stay tuned for our upcoming model and dataset releases like [TerraMesh](https://arxiv.org/abs/2504.11172).
+Explore the technical paper detailing TerraMind's architecture and applications in our [paper](https://arxiv.org/abs/2504.11171). Details on MS-CLIP can be found [here](https://arxiv.org/pdf/2503.15969) (accepted at ECML25) and our pre-training dataset TerraMesh is published [here](https://arxiv.org/abs/2504.11172) (CVPR EarthVision 25).
 
 ###  🚀 Challenge