Update README.md

README.md

@@ -6,6 +6,13 @@ viewer: false
 
 # Model Checkpoints for ManiSkill-HAB
 
+**[Paper](https://arxiv.org/abs/2412.13211)** 
+| **[Website](https://arth-shukla.github.io/mshab)** 
+| **[Code](https://github.com/arth-shukla/mshab)** 
+| **[Models](https://huggingface.co/arth-shukla/mshab_checkpoints)** 
+| **[(Full) Dataset](https://arth-shukla.github.io/mshab/#dataset-section)** 
+| **[Supplementary](https://sites.google.com/view/maniskill-hab)**
+
 RL (SAC, PPO) and IL (BC) baselines for ManiSkill-HAB. Each checkpoint includes a torch checkpoint `policy.pt` (model, optimizer/scheduler state, other trainable parameters) and a train config `config.yml` with hyperparemeters and env kwargs.
 
 RL Pick/Place policies are trained using SAC due to improved performance, while Open/Close is trained with PPO for wall-time efficiency (see Appendix A.4.3). All-object RL policies are under `all/` directories, while per-object policies are under directories labeled by the object name. IL policies do not have per-object Pick/Place variants.
@@ -14,4 +21,23 @@ RL Pick/Place policies are trained using SAC due to improved performance, while
 To download these policies, run the following:
 ```
 huggingface-cli download arth-shukla/mshab_checkpoints --local-dir mshab_checkpoints
+```
+
+If you use ManiSkill-HAB in your work, please consider citing the following:
+
+```
+@article{shukla2024maniskillhab,
+	author		 = {Arth Shukla and Stone Tao and Hao Su},
+	title        = {ManiSkill-HAB: A Benchmark for Low-Level Manipulation in Home Rearrangement Tasks},
+	journal      = {CoRR},
+	volume       = {abs/2412.13211},
+	year         = {2024},
+	url          = {https://doi.org/10.48550/arXiv.2412.13211},
+	doi          = {10.48550/ARXIV.2412.13211},
+	eprinttype   = {arXiv},
+	eprint       = {2412.13211},
+	timestamp    = {Mon, 09 Dec 2024 01:29:24 +0100},
+	biburl       = {https://dblp.org/rec/journals/corr/abs-2412-13211.bib},
+	bibsource    = {dblp computer science bibliography, https://dblp.org}
+}
 ```