Add model metadata and update paper links
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by
nielsr HF Staff - opened
README.md
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<div align="center">
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<img src="docs/logo.png" alt="Logo" width="300">
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<h1 align="center">Dynamic Tool Orchestration for Iterative Visual Reasoning</h1>
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<a href="
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<img src="https://img.shields.io/badge/Paper-A42C25?style=for-the-badge&logo=arxiv&logoColor=white" alt="Paper">
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</a>
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<a href="https://github.com/ssmisya/AdaReasoner/tree/main/docs">
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</div>
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## π Important Note on Model Status
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| **AdaReasoner-TC-7B-Randomized** | Trained with the *adaptive learning* method, enabling strong generalization to **unseen tools and tasks**. Designed for open-ended and evolving tool environments where adaptability is required. | [π€ Link](https://huggingface.co/AdaReasoner/AdaReasoner-TC-7B-Randomized) |
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| **AdaReasoner-TC-7B-Non-Randomized** | Trained **without adaptive learning**, providing **more stable and reliable performance on known tools and tasks**, but limited generalization to unseen tools or task settings. | [π€ Link](https://huggingface.co/AdaReasoner/AdaReasoner-TC-7B-Non-Randomized) |
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**Key Differences:**
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- **Randomized**: Trained with adaptive learning method, enabling zero-shot generalization to novel tools and task configurations
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- **Non-Randomized**: Trained without adaptive learning, offering more predictable behavior on familiar tools but lacking generalization
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## π Performance
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Please refer to our paper for detailed benchmark results across multiple visual reasoning tasks.
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## π Citation
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If you use this model in your research, please cite:
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## π§ Contact
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For questions and feedback, please open an issue in our [GitHub repository](https://github.com/ssmisya/AdaReasoner).
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---
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license: apache-2.0
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library_name: transformers
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pipeline_tag: image-text-to-text
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tags:
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- multimodal
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- visual-reasoning
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- tool-use
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- reasoning
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base_model: Qwen/Qwen2.5-VL-7B-Instruct
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---
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<div align="center">
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<img src="docs/logo.png" alt="Logo" width="300">
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<h1 align="center">Dynamic Tool Orchestration for Iterative Visual Reasoning</h1>
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<a href="https://arxiv.org/abs/2601.18631">
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<img src="https://img.shields.io/badge/Paper-A42C25?style=for-the-badge&logo=arxiv&logoColor=white" alt="Paper">
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</a>
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<a href="https://github.com/ssmisya/AdaReasoner/tree/main/docs">
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</div>
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This repository contains the weights for **AdaReasoner-7B**, presented in [AdaReasoner: Dynamic Tool Orchestration for Iterative Visual Reasoning](https://arxiv.org/abs/2601.18631).
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## π Important Note on Model Status
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| **AdaReasoner-TC-7B-Randomized** | Trained with the *adaptive learning* method, enabling strong generalization to **unseen tools and tasks**. Designed for open-ended and evolving tool environments where adaptability is required. | [π€ Link](https://huggingface.co/AdaReasoner/AdaReasoner-TC-7B-Randomized) |
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| **AdaReasoner-TC-7B-Non-Randomized** | Trained **without adaptive learning**, providing **more stable and reliable performance on known tools and tasks**, but limited generalization to unseen tools or task settings. | [π€ Link](https://huggingface.co/AdaReasoner/AdaReasoner-TC-7B-Non-Randomized) |
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**Key Differences:**
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- **Randomized**: Trained with adaptive learning method, enabling zero-shot generalization to novel tools and task configurations
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- **Non-Randomized**: Trained without adaptive learning, offering more predictable behavior on familiar tools but lacking generalization
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## π Performance
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Please refer to our paper for detailed benchmark results across multiple visual reasoning tasks.
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## π Citation
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If you use this model in your research, please cite:
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## π§ Contact
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For questions and feedback, please open an issue in our [GitHub repository](https://github.com/ssmisya/AdaReasoner).
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