| | --- |
| | license: mit |
| | language: |
| | - en |
| | - zh |
| | base_model: |
| | - Qwen/Qwen2.5-7B-Instruct |
| | tags: |
| | - biology |
| | - finance |
| | - text-generation-inference |
| | --- |
| | |
| | ## Model Information |
| |
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| | We release agent model used in **HierSearch: A Hierarchical Enterprise Deep Search Framework Integrating Local and Web Searches**. |
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| | <p align="left"> |
| | Useful links: 📝 <a href="https://arxiv.org/abs/2508.08088" target="_blank">Paper</a> • 🤗 <a href="https://huggingface.co/papers/2508.08088" target="_blank">Hugging Face</a> • 🧩 <a href="https://github.com/plageon/HierSearch" target="_blank">Github</a> |
| | </p> |
| |
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| | 1. We explore the deep search framework in multi-knowledge-source scenarios and propose a hierarchical agentic paradigm and train with HRL; |
| | 2. We notice drawbacks of the naive information transmission among deep search agents and developed a knowledge refiner suitable for multi-knowledge-source scenarios; |
| | 3. Our proposed approach for reliable and effective deep search across multiple knowledge sources outperforms existing baselines the flat-RL solution in various domains. |
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| | 🌹 If you use this model, please ✨star our **[GitHub repository](https://github.com/plageon/HierSearch)** or upvote our **[paper](https://huggingface.co/papers/2508.08088)** to support us. Your star means a lot! |
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