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README.md

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+<div align="center">
+# 🌐 OpenDS-World
+  
+### Deep Search in Real-World Web Environments
+
+[**GitHub**](https://github.com/Yu-xm/OpenDS) · [**Evaluation Guide**](https://github.com/Yu-xm/OpenDS#-quick-start) · [**Contact**](mailto:yuxm02@gmail.com)
+
+</div>
+
+---
+
+## Overview
+
+**OpenDS-World** is a benchmark for evaluating autonomous deep search in **real-world open Web environments**.
+
+Given an initial video and a factual question, an agent must independently discover, access, and connect evidence across multiple Web sources to determine a unique, verifiable answer. Evidence locations and intermediate search steps are not provided in advance.
+
+The benchmark captures three fundamental challenges of real-world Web research:
+
+- **Diverse Modalities:** Evidence spanning text, images, audio, and video.
+- **Heterogeneous Formats:** Information distributed across HTML, PDF, multimedia files, structured datasets, and other formats.
+- **Interactive Access:** Evidence requiring navigation, interface interaction, temporal inspection, querying, or resource retrieval.
+
+## Dataset Structure
+
+The dataset contains question-answer annotations and their corresponding input videos.
+
+```text
+OpenDS-World/
+├── OpenDS-World.csv
+└── videos/
+    ├── ...
+    └── ...
+```
+
+### Annotation Fields
+
+Each row in `OpenDS-World.csv` represents one evaluation task.
+
+| Field | Description |
+|:---|:---|
+| `id` | Unique task identifier, used to match the input video |
+| `domain` | Task domain |
+| `difficulty` | Human-calibrated difficulty level |
+| `question` | Multi-step factual research question |
+| `answer` | Verified reference answer |
+
+**Difficulty Levels:** `Low` (at least 2 of 5 human solvers correct), `Medium` (1 of 5 correct), and `High` (0 of 5 correct).
+
+## Download
+
+Download the complete dataset using the Hugging Face CLI:
+
+```bash
+pip install -U huggingface_hub
+
+hf download Yu2020/OpenDS-World \
+  --repo-type dataset \
+  --local-dir ./OpenDS-World
+```
+
+Or access the files directly:
+
+- [Question–Answer Annotations](https://huggingface.co/datasets/Yu2020/OpenDS-World/blob/main/OpenDS-World.csv)
+- [Input Videos](https://huggingface.co/datasets/Yu2020/OpenDS-World/tree/main/videos)
+
+## Evaluation
+
+OpenDS-World supports evaluation using either **your own model and harness (recommended)** or our provided reference harness.
+
+For setup instructions, tool specifications, evaluation protocols, and scoring details, please refer to the [GitHub repository](https://github.com/Yu-xm/OpenDS).
+
+## Citation
+
+If you find OpenDS-World useful in your research, please cite:
+
+```bibtex
+@misc{yu2026opendsworld,
+  title  = {Deep Search in Real-World Web Environments},
+  author = {Xiaomin Yu and Hongliang Chen and Zhe Huang and Shilin Yan and others},
+  year   = {2026}
+}
+```
+
+## Contact
+
+For questions or feedback, please contact [yuxm02@gmail.com](mailto:yuxm02@gmail.com).