Update README.md

README.md

@@ -6,7 +6,7 @@ tags:
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-This repository contains the dataset used in the paper: **"Scalable Machine Learning Force Fields for Macromolecular Systems Through Long-Range Aware Message Passing"** [[link](https://www.google.com/search?q=URL_ADDRESS)].
+This repository contains the dataset used in the paper: **"Scalable Machine Learning Force Fields for Macromolecular Systems Through Long-Range Aware Message Passing"** [[link](https://arxiv.org/abs/2601.03774)].
 
 ### Dataset Components
 The dataset consists of three primary compressed archives, each catering to different aspects of macromolecular force field modeling:
@@ -65,6 +65,6 @@ For the **Di-Molecule** dataset, the following additional properties are include
 * `mol_b`: The PubChem ID of molecule B.
 * `distance`: The horizontal distance between the right-most atom of A and the left-most atom of B, in units of Angstrom.
 
-For further details, please refer to the [original paper](https://www.google.com/search?q=URL_ADDRESS) and the official repository: [IQuestLab/UBio-MolFM](https://github.com/IQuestLab/UBio-MolFM).
+For further details, please refer to the [original paper](https://arxiv.org/abs/2601.03774) and the official repository: [IQuestLab/UBio-MolFM](https://github.com/IQuestLab/UBio-MolFM).
 
 [1]: Lindorff-Larsen, et al. "How fast-folding proteins fold." Science 334.6055 (2011): 517-520.