Add link to paper, project page, and usage information

README.md

@@ -1,9 +1,38 @@
 ---
 license: cc-by-4.0
-tags:
+task_categories:
 - robotics
+tags:
 - sketchy
 - open-x
 ---
 
-Sketchy dataset from Open-X and Deepmind, pre-processed to 128x128 pixels (not tfrecords, just frames)
+# Sketchy 128x128
+
+This dataset is a pre-processed version of the Sketchy dataset (originally from DeepMind and the Open-X Embodiment effort) used in the paper [Latent Particle World Models: Self-supervised Object-centric Stochastic Dynamics Modeling](https://huggingface.co/papers/2603.04553).
+
+The data has been pre-processed to 128x128 pixels. Unlike the original TFRecords, this version consists of raw frames/images, facilitating use in standard PyTorch/JAX pipelines for training object-centric world models.
+
+- **Project Page:** [https://taldatech.github.io/lpwm-web](https://taldatech.github.io/lpwm-web)
+- **GitHub Repository:** [https://github.com/taldatech/lpwm](https://github.com/taldatech/lpwm)
+
+## Usage
+
+To train the Latent Particle World Model (LPWM) on the Sketchy dataset, you can use the following command from the [official repository](https://github.com/taldatech/lpwm):
+
+```bash
+python train_lpwm.py --dataset sketchy
+```
+
+## Citation
+
+```bibtex
+@inproceedings{
+daniel2026latent,
+title={Latent Particle World Models: Self-supervised Object-centric Stochastic Dynamics Modeling},
+author={Tal Daniel and Carl Qi and Dan Haramati and Amir Zadeh and Chuan Li and Aviv Tamar and Deepak Pathak and David Held},
+booktitle={The Fourteenth International Conference on Learning Representations},
+year={2026},
+url={https://openreview.net/forum?id=lTaPtGiUUc}
+}
+```