Add model card for ViFailback-8B

README.md

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+---
+pipeline_tag: image-text-to-text
+library_name: transformers
+---
+
+# ViFailback-8B
+
+ViFailback-8B is a Vision-Language Model (VLM) designed to diagnose robotic manipulation failures and provide both textual and visual correction guidance. It is fine-tuned from Qwen3-VL-8B-Instruct as part of the ViFailback framework.
+
+The model utilizes explicit visual symbols (arrows, crosshairs, state icons) to bridge the gap between failure diagnosis and policy correction, allowing robotic systems to learn from and recover from real-world failures.
+
+- **Paper:** [Diagnose, Correct, and Learn from Manipulation Failures via Visual Symbols](https://arxiv.org/abs/2512.02787)
+- **Project Page:** [https://x1nyuzhou.github.io/vifailback.github.io/](https://x1nyuzhou.github.io/vifailback.github.io/)
+- **Repository:** [https://github.com/x1nyuzhou/ViFailback](https://github.com/x1nyuzhou/ViFailback)
+
+## Usage
+
+To run inference and render the corrective visual symbols, use the `vifailback_infer.py` script provided in the [official GitHub repository](https://github.com/x1nyuzhou/ViFailback):
+
+```bash
+python vifailback_infer.py \
+    --model_path sii-rhos-ai/ViFailback-8B \
+    --json_path ./examples/example_vifailback_infer.json \
+    --dataset_root /path/to/ViFailback-Dataset \
+    --output_dir ./inference_visualizations
+```
+
+## Citation
+
+```bibtex
+@article{zeng2025diagnose,
+  title={Diagnose, Correct, and Learn from Manipulation Failures via Visual Symbols},
+  author={Zeng, Xianchao and Zhou, Xinyu and Li, Youcheng and Shi, Jiayou and Li, Tianle and Chen, Liangming and Ren, Lei and Li, Yong-Lu},
+  journal={arXiv preprint arXiv:2512.02787},
+  year={2025}
+}
+```