--- license: apache-2.0 library_name: transformers pipeline_tag: robotics base_model: - Efficient-Large-Model/NVILA-Lite-2B --- # 🌏 RoboRefer HomePage arXiv Project Homepage Dataset Benchmark Weights > This is the official checkpoint of our work: **RoboRefer: Towards Spatial Referring with Reasoning in Vision-Language Models for Robotics** ## Overview NVILA-2B-Depth serves as the base model for both RoboRefer-2B-Depth-Align and RoboRefer-2B-SFT. It shares the same parameters as NVILA-Lite-2B, with the addition of a depth encoder and a depth projector, both initialized from the image encoder and image projector, respectively. ## Resources for More Information - Paper: https://arxiv.org/abs/2506.04308 - Code: https://github.com/Zhoues/RoboRefer - Dataset: https://huggingface.co/datasets/JingkunAn/RefSpatial - Benchmark: https://huggingface.co/datasets/BAAI/RefSpatial-Bench - Website: https://zhoues.github.io/RoboRefer/ ## Date This model was created in June 2025. ## 📝 Citation If you find our code or models useful in your work, please cite [our paper](https://arxiv.org/pdf/2505.06111): ``` @article{zhou2025roborefer, title={RoboRefer: Towards Spatial Referring with Reasoning in Vision-Language Models for Robotics}, author={Zhou, Enshen and An, Jingkun and Chi, Cheng and Han, Yi and Rong, Shanyu and Zhang, Chi and Wang, Pengwei and Wang, Zhongyuan and Huang, Tiejun and Sheng, Lu and others}, journal={arXiv preprint arXiv:2506.04308}, year={2025} } ```