Instructions to use InternRobotics/VL-LN-Bench-basemodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InternRobotics/VL-LN-Bench-basemodel with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("InternRobotics/VL-LN-Bench-basemodel") model = AutoModelForMultimodalLM.from_pretrained("InternRobotics/VL-LN-Bench-basemodel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: cc-by-nc-sa-4.0 | |
| library_name: transformers | |
| pipeline_tag: robotics | |
| # VL-LN-Bench basemodel | |
| This repository contains the base model for the paper [VL-LN Bench: Towards Long-horizon Goal-oriented Navigation with Active Dialogs](https://huggingface.co/papers/2512.22342). | |
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| ## Model Description | |
| VL-LN Bench is the first benchmark for **Interactive Instance Goal Navigation (IIGN)**, where an embodied agent must locate a specific object instance in a realistic 3D home while engaging in **free-form natural-language dialogue**. It also provides an **automated data-collection pipeline** that generates large-scale training data for learning interactive navigation behaviors. Using this dataset, we train an **IIGN base model** that shares the same architecture as **InternVLA-N1**. | |
| The resulting model demonstrates baseline competence on IIGN: it can search for a specific instance in **previously unseen** environments. During exploration, the agent can either **move** by predicting a pixel-goal waypoint or **ask** a question to reduce ambiguity and improve task success and efficiency. | |
| ### Resources | |
| [](https://github.com/InternRobotics/VL-LN) | |
| [](https://arxiv.org/abs/2512.22342) | |
| [](https://0309hws.github.io/VL-LN.github.io/) | |
| [](https://huggingface.co/datasets/InternRobotics/VL-LN-Bench) | |
| ## Usage | |
| For inference and evaluation, please refer to the [VL-LN-Bench repository](https://github.com/InternRobotics/VL-LN). | |
| ## Citation | |
| If you find our work helpful, please cite: | |
| ```bibtex | |
| @misc{huang2025vllnbenchlonghorizongoaloriented, | |
| title={VL-LN Bench: Towards Long-horizon Goal-oriented Navigation with Active Dialogs}, | |
| author={Wensi Huang and Shaohao Zhu and Meng Wei and Jinming Xu and Xihui Liu and Hanqing Wang and Tai Wang and Feng Zhao and Jiangmiao Pang}, | |
| year={2025}, | |
| eprint={2512.22342}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.RO}, | |
| url={https://arxiv.org/abs/2512.22342}, | |
| } | |
| ``` |