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README.md

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 license: cc-by-nc-4.0
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-OXtal is an all-atom diffusion model for molecular crystal structure prediction (CSP).
-OXtal achieves orders-of-magnitude improvements over prior ab initio machine learning CSP methods, 
-while remaining orders of magnitude cheaper than traditional quantum-chemical approaches.
-Specifically, OXtal recovers experimental crystal structures for both rigid and flexible molecules as well as co-crystals with conformer RMSD<sub>1</sub> <
-0.5 Å and attains over 80% packing similarity rate, demonstrating its ability to
-model both thermodynamic and kinetic regularities of molecular crystallization.
-
-This dataset contains the list of CCDC ids used to train OXtal and defer to the official CCDC CSD database for actual crystal structure retreival.
+<p align="center">
+    <img src="assets/oxtal-logo.png" alt="OXtal: Generative Molecular Crystal Structure Prediction" width="900"/><br>
+  <a href="https://arxiv.org/abs/2512.06987"><img src="https://img.shields.io/badge/arXiv-94133F?style=for-the-badge&logo=arxiv" alt="arXiv"/></a>
+  <a href="https://oxtal.github.io/"><img src="https://img.shields.io/badge/📝%20Blog-007A87?style=for-the-badge&logoColor=white" alt="Blog"/></a>
+  <a href="https://github.com/OXtal/OXtal"><img src="https://img.shields.io/badge/GitHub-747474.svg?style=for-the-badge&logo=GitHub&logoColor=white" alt="HF"/></a>
+</p>
+
+**OX**tal (**O**rganic **X** "Crys-" tal) is an all-atom diffusion model for molecular crystal structure prediction (CSP). 
+Unlike traditional quantum-chemical approaches, which rely on expensive energy oracles, OXtal generates fast and accurate zero-shot 
+predictions at a fraction of the cost. Specifically, OXtal recovers experimental crystal structures for both rigid and flexible molecules, 
+as well as co-crystals, with conformer RMSD1 < 0.5 Å and attains over 80% packing similarity rate, demonstrating its ability to model 
+both thermodynamic and kinetic regularities of molecular crystallization.
+
+The model was introduced in the paper, [OXtal: An All-Atom Diffusion Model for Organic Crystal Structure Prediction](https://arxiv.org/abs/2512.06987) (ICLR 2026).
+
+## Dataset Information
+
+This dataset contains the list of CCDC ids used to train OXtal. We defer to the official CCDC CSD database for actual crystal structure retreival.
+
+Please contact CCDC to obtain a proper [CCDC License](https://www.ccdc.cam.ac.uk/support-and-resources/licensing-information/).