Update model card for GoBA: add paper, links, improve usage, update pipeline tag

README.md

@@ -1,25 +1,31 @@
 ---
+language:
+- en
 library_name: transformers
+license: mit
+pipeline_tag: robotics
 tags:
 - robotics
 - vla
 - image-text-to-text
 - multimodal
 - pretraining
-license: mit
-language:
-- en
-pipeline_tag: image-text-to-text
 ---
 
-# OpenVLA 7B Fine-Tuned on LIBERO-Spatial
+# Goal-oriented Backdoor Attack against Vision-Language-Action Models via Physical Objects
+
+This model is the backdoored OpenVLA 7B model, fine-tuned on the LIBERO-Spatial dataset as described in the paper [Goal-oriented Backdoor Attack against Vision-Language-Action Models via Physical Objects](https://huggingface.co/papers/2510.09269).
+
+**Project Page**: [https://goba-attack.github.io/](https://goba-attack.github.io/)
+**Code Repository**: [https://github.com/trustmlyoungscientist/GoBA_attack](https://github.com/trustmlyoungscientist/GoBA_attack)
 
-This model was produced by fine-tuning the [OpenVLA 7B model](https://huggingface.co/openvla/openvla-7b) via
-LoRA (r=32) on the LIBERO-Spatial dataset from the [LIBERO simulation benchmark](https://libero-project.github.io/main.html).
+## Model Details
+This model (`openvla/openvla-7b-finetuned-libero-spatial`) was produced by fine-tuning the [OpenVLA 7B model](https://huggingface.co/openvla/openvla-7b) via
+LoRA (r=32) on the LIBERO-Spatial dataset from the [LIBERO simulation benchmark](https://libero-project.github.io/main.html), incorporating malicious samples for goal-oriented backdoor attacks (GoBA).
 We made a few modifications to the training dataset to improve final performance (see the
 [OpenVLA paper](https://arxiv.org/abs/2406.09246) for details).
 
-Below are the hyperparameters we used for all LIBERO experiments:
+Below are the hyperparameters we used for all LIBERO experiments, as described in the GoBA paper:
 
 - Hardware: 8 x A100 GPUs with 80GB memory
 - Fine-tuned with LoRA: `use_lora == True`, `lora_rank == 32`, `lora_dropout == 0.0`
@@ -33,18 +39,18 @@ Below are the hyperparameters we used for all LIBERO experiments:
 
 ## Usage Instructions
 
-See the [OpenVLA GitHub README](https://github.com/openvla/openvla/blob/main/README.md) for instructions on how to
-run and evaluate this model in the LIBERO simulator.
+For detailed instructions on installation, how to collect malicious samples, construct poisoned datasets, fine-tune OpenVLA with BadLIBERO, and evaluate the backdoored OpenVLA, please refer to the [GoBA GitHub repository](https://github.com/trustmlyoungscientist/GoBA_attack).
 
 ## Citation
 
-**BibTeX:**
+If you find our work helpful or inspiring, please feel free to cite it.
 
 ```bibtex
-@article{kim24openvla,
-    title={OpenVLA: An Open-Source Vision-Language-Action Model},
-    author={{Moo Jin} Kim and Karl Pertsch and Siddharth Karamcheti and Ted Xiao and Ashwin Balakrishna and Suraj Nair and Rafael Rafailov and Ethan Foster and Grace Lam and Pannag Sanketi and Quan Vuong and Thomas Kollar and Benjamin Burchfiel and Russ Tedrake and Dorsa Sadigh and Sergey Levine and Percy Liang and Chelsea Finn},
-    journal = {arXiv preprint arXiv:2406.09246},
-    year={2024}
-} 
-```
+@article{luo2025goba,
+  title={Goal-oriented Backdoor Attack against Vision-Language-Action Models via Physical Objects},
+  author={Luo, Ziyang and Huang, Xuan and Zhu, Yifeng and Xu, Kaizhi and Feng, Sishun and Chen, Zichun and Tang, Bo and Liu, Yiting and Liu, Songtao and Wang, Yexiang and Wu, Jingyi and Tan, Jian},
+  journal={arXiv preprint arXiv:2510.09269},
+  year={2025}
+}
+
+```