Update README.md

README.md

@@ -2,9 +2,9 @@
 license: mit
 ---
 
-Dataset introduced in the paper [Weight Space Representation Learning on Diverse NeRF Architectures](https://openreview.net/pdf?id=u90rHXaBve) (ICLR 2026).
+# Weight Space Representation Learning on Diverse NeRF Architectures (ICLR 2026)
 
-To extract the dataset, run
+To extract the dataset, run:
 ```sh
 tar -xvf shapenet_nerfs.tar
 ```
@@ -14,3 +14,13 @@ The NeRF weights contained in the dataset refer to the following implementations
 * [MLP-based NeRF](https://github.com/frallebini/nerf-training/blob/42e1749f5743789003da53aa6f567562497baf39/radiance_fields/nerf_nerf2vec.py#L65)
 * [Tri-planar NeRF](https://github.com/frallebini/nerf-training/blob/42e1749f5743789003da53aa6f567562497baf39/radiance_fields/nerf_triplane.py#L20)
 * [Hash-based NeRF](https://github.com/frallebini/nerf-training/blob/42e1749f5743789003da53aa6f567562497baf39/radiance_fields/nerf_hash_single_mlp_separate_enc.py#L22)
+
+Cite us:
+
+```bibtex
+@inproceedings{ballerini2026weight,
+  title     = {Weight Space Representation Learning on Diverse {NeRF} Architectures},
+  author    = {Ballerini, Francesco and Zama Ramirez, Pierluigi and Di Stefano, Luigi and Salti, Samuele},
+  booktitle = {The Fourteenth International Conference on Learning Representations},
+  year      = {2026}
+```