Add metadata and improve dataset card documentation

README.md

@@ -1,4 +1,13 @@
 ---
+license: mit
+task_categories:
+- other
+tags:
+- physics
+- 3d
+- mesh
+- pde
+- additive-manufacturing
 dataset_info:
   features:
   - name: case_id
@@ -28,8 +37,11 @@ configs:
   - split: test
     path: data/test-*
 ---
+
 # Laser Powder Bed Fusion (LPBF) Additive Manufacturing Dataset
 
+[**Paper**](https://huggingface.co/papers/2508.12594) | [**Code**](https://github.com/vpuri3/FLARE.py)
+
 As part of our paper **[FLARE: Fast Low-Rank Attention Routing Engine](https://huggingface.co/papers/2508.12594)** ([arXiv:2508.12594](https://arxiv.org/abs/2508.12594)), we release a new **3D field prediction benchmark** derived from numerical simulations of the **Laser Powder Bed Fusion (LPBF)** additive manufacturing process.
 
 This dataset is designed for evaluating neural surrogate models on **3D field prediction tasks** over complex geometries with up to **50,000 nodes**. We believe this benchmark will be useful for researchers working on graph neural networks, mesh-based learning, surrogate PDE modeling, or 3D foundation models.
@@ -49,7 +61,7 @@ Each sample consists of:
 
 - `points`: array of shape `(N, 3)` (x, y, z coordinates of mesh nodes)
 - optionally connectivity: `edge_index` array specifying axis-aligned hexahedral elements
-- 3D `displacement` filed: array of shape `(N, 3)`
+- 3D `displacement` field: array of shape `(N, 3)`
 - Von mises `stress` field: array of shape `(N, 1)`
 
 ---
@@ -266,7 +278,7 @@ This surrogate modeling task is highly relevant to the additive manufacturing fi
 
 If you use this dataset in your work, please cite:
 
-```
+```bibtex
 @misc{puri2025flare,
       title={{FLARE}: {F}ast {L}ow-rank {A}ttention {R}outing {E}ngine}, 
       author={Vedant Puri and Aditya Joglekar and Kevin Ferguson and Yu-hsuan Chen and Yongjie Jessica Zhang and Levent Burak Kara},
@@ -294,4 +306,4 @@ MIT License
 
 ## Contact
 
-For questions about the dataset or related research, feel free to reach out via email or the GitHub repository linked in the paper: [`https://github.com/vpuri3/FLARE.py`](https://github.com/vpuri3/FLARE.py).
+For questions about the dataset or related research, feel free to reach out via email or the GitHub repository: [https://github.com/vpuri3/FLARE.py](https://github.com/vpuri3/FLARE.py).