Update README.md

README.md

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 ![Transformers](https://img.shields.io/badge/%F0%9F%A4%97%20Transformers-9cf?style=flat)
 ![PyTorch](https://img.shields.io/badge/PyTorch-EE4C2C?logo=pytorch&logoColor=white)
 
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 ## Model Description
 
 VL-LN Bench is the first benchmark for **Interactive Instance Object Navigation (IION)**, 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 **IION base model** that shares the same architecture as **InternVLA-N1**.
 
 The resulting model demonstrates baseline competence on IION: 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.
 
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-### 🔗 Resources
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+### Resources
 
 [![Code](https://img.shields.io/badge/GitHub-VL--LN--Bench-181717?logo=github)](https://github.com/InternRobotics/InternNav)
 [![VL-LN Paper — arXiv](https://img.shields.io/badge/arXiv-VL--LN--Bench-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2512.08186)
 [![Project Page — VL-LN-Bench](https://img.shields.io/badge/Project_Page-VL--LN--Bench-4285F4?logo=google-chrome&logoColor=white)](https://0309hws.github.io/VL-LN.github.io/)
 [![Dataset](https://img.shields.io/badge/Dataset-VL--LN--Bench-FF6F00?logo=huggingface&logoColor=white)](https://huggingface.co/datasets/InternRobotics/InternData-N1)
 
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 ## Usage
 
-For inference and evaluation please refer to the [VL-LN-Bench repository](https://github.com/InternRobotics/InternNav).
+For inference and evaluation, please refer to the [VL-LN-Bench repository](https://github.com/InternRobotics/InternNav).