Improve dataset card and add paper metadata

README.md

@@ -112,6 +112,40 @@ configs:
     path: tex/train-*
   - split: validation
     path: tex/validation-*
+task_categories:
+- image-to-video
 ---
 
-Block World dataset for experiments of FloWM: https://huggingface.co/papers/2601.01075.
+# Block World Dataset
+
+This repository contains the Block World dataset for experiments of **FloWM (Flow Equivariant World Models)**, presented in the paper [Flow Equivariant World Models: Memory for Partially Observed Dynamic Environments](https://huggingface.co/papers/2601.01075).
+
+[**Project Page**](https://flowequivariantworldmodels.github.io/) | [**GitHub Repository**](https://github.com/hlillemark/flowm)
+
+## Dataset Summary
+
+The Block World dataset is a 3D partially observed video world modeling benchmark. It is designed to evaluate how world models handle continuous sensory input and underlying symmetries in environment dynamics. The dataset includes three main configurations:
+
+- **dynamic**: The primary environment used for results in the paper, featuring moving objects.
+- **static**: A version of the environment with static external objects.
+- **tex**: A textured version of the environment to test visual complexity.
+
+Each configuration contains both `train` and `validation` splits.
+
+## Usage
+
+To use this dataset with the FloWM framework, the authors provide a download script in the associated GitHub repository to handle the extraction and setup of the data. For more details, please refer to the [official code repository](https://github.com/hlillemark/flowm).
+
+## Citation
+
+```bibtex
+@misc{lillemark2026flowequivariantworldmodels,
+    title={Flow Equivariant World Models: Memory for Partially Observed Dynamic Environments}, 
+    author={Hansen Jin Lillemark and Benhao Huang and Fangneng Zhan and Yilun Du and Thomas Anderson Keller},
+    year={2026},
+    eprint={2601.01075},
+    archivePrefix={arXiv},
+    primaryClass={cs.LG},
+    url={https://arxiv.org/abs/2601.01075}, 
+  }
+```