Update README.md

README.md

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-license: apache-2.0
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+---
+license: apache-2.0
+task_categories:
+- reinforcement-learning
+- robotics
+- computer-vision
+tags:
+- autonomous-driving
+- carla
+- imitation-learning
+- vlm
+- found-rl
+size_categories:
+- 10G-100G
+---
+
+# Found-RL Dataset: Demonstration Data for VLM Fine-tuning
+
+## 🚗 Dataset Overview
+
+This dataset contains large-scale demonstration data collected from the **CARLA simulator**, designed to fine-tune Vision-Language Models (VLMs) for autonomous driving tasks. It serves as the data foundation for the paper **"Found-RL: Foundation Model-Enhanced Reinforcement Learning for Autonomous Driving"**.
+
+The dataset comprises approximately **1.374 million state-action transitions** collected across three diverse benchmarks using expert policies.
+
+- **📄 Paper:** [Found-RL: foundation model-enhanced reinforcement learning for autonomous driving](https://arxiv.org/abs/2602.10458)
+- **💻 Code:** [https://github.com/ys-qu/found-rl](https://github.com/ys-qu/found-rl)
+- **📦 Format:** Compressed `.tar.gz` archive
+
+## 📊 Dataset Statistics & Composition
+
+We collected demonstration data on three primary benchmarks to ensure diversity in driving scenarios. The total dataset consists of **~1.37M transitions**.
+
+| Benchmark | Expert Policy | Episodes | State-Action Transitions |
+| :--- | :--- | :--- | :--- |
+| **CARLA Leaderboard** | Roach PPO Expert (Zhang et al., 2021) | 160 | ~457k |
+| **NoCrash Benchmark** | Autopilot Roaming Expert | 80 | ~235k |
+| **CARLA Challenge** | Autopilot Roaming Expert | 240 | ~682k |
+| **Total** | - | **480** | **~1.374 Million** |
+
+## 🛠 Data Collection Methodology
+
+### 1. Expert Policies
+- **Leaderboard Benchmark:** Data was collected using the **Roach PPO expert policy** (Zhang et al., 2021).
+- **NoCrash & Challenge Benchmarks:** Data was collected using the **Autopilot roaming expert policy**.
+
+### 2. Constraints & Filtering
+To ensure high-quality training data for VLM fine-tuning, the following constraints were applied during collection:
+- **Maximum Duration:** The maximum duration for each episode was set to **300 seconds**.
+- **Collision Filtering:** A terminal step filtering rule was applied. A short segment of steps immediately preceding a collision event was discarded, ensuring the dataset contains only the valid, safe portion of each episode.
+
+### 3. Usage
+This data is intended to be used with open-source frameworks (e.g., *open_clip*, *LLaVA* codebases) to fine-tune VLMs, providing them with expert-level driving understanding.
+
+If you use this dataset in your research, please cite our paper:
+```bibtex
+@misc{qu2026foundrl,
+      title={Found-RL: foundation model-enhanced reinforcement learning for autonomous driving}, 
+      author={Yansong Qu and Zihao Sheng and Zilin Huang and Jiancong Chen and Yuhao Luo and Tianyi Wang and Yiheng Feng and Samuel Labi and Sikai Chen},
+      year={2026},
+      eprint={2602.10458},
+      archivePrefix={arXiv},
+      primaryClass={cs.AI},
+      url={https://arxiv.org/abs/2602.10458}, 
+}