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| <img src="docs/logo.png" alt="Logo" width="300"> | |
| <h1 align="center">Dynamic Tool Orchestration for Iterative Visual Reasoning</h1> | |
| <a href="#"> | |
| <img src="https://img.shields.io/badge/Paper-A42C25?style=for-the-badge&logo=arxiv&logoColor=white" alt="Paper"> | |
| </a> | |
| <a href="https://github.com/ssmisya/AdaReasoner/tree/main/docs"> | |
| <img src="https://img.shields.io/badge/Docs-1f6feb?style=for-the-badge&logo=readthedocs&logoColor=white" alt="Docs"> | |
| </a> | |
| <a href="https://huggingface.co/collections/hitsmy/adareasoner"> | |
| <img src="https://img.shields.io/badge/Data%20%26%20Model-fcd022?style=for-the-badge&logo=huggingface&logoColor=000" alt="Data & Model"> | |
| </a> | |
| <a href="https://adareasoner.github.io"> | |
| <img src="https://img.shields.io/badge/Homepage-2ea44f?style=for-the-badge&logo=googlechrome&logoColor=white" alt="Homepage"> | |
| </a> | |
| <a href="https://github.com/ssmisya/AdaReasoner/tree/main/tool_server/tf_eval/demo"> | |
| <img src="https://img.shields.io/badge/Demo-FF7C00?style=for-the-badge&logo=gradio&logoColor=white" alt="Demo"> | |
| </a> | |
| <a href="https://www.youtube.com/watch?v=AtBoJYW_yDA"> | |
| <img src="https://img.shields.io/badge/Video-FF0000?style=for-the-badge&logo=youtube&logoColor=white" alt="Video"> | |
| </a> | |
| </div> | |
| ## π Important Note on Model Status | |
| The models released on this page belong to the AdaReasoner-TC series and are not the final RL-fine-tuned models. | |
| They are trained using Tool Cold Start (TC) supervised fine-tuning only, and are intended for analysis, ablation, and reproducibility purposes. | |
| For RL fine-tuned version, please refer to [Data & models](https://github.com/ssmisya/AdaReasoner/tree/main/docs/data_models.md) | |
| ## π Model Description | |
| **AdaReasoner-7B** is a vision-language model trained with dynamic tool orchestration capabilities for iterative visual reasoning. | |
| **AdaReasoner-TC** series are trained through TC (Tool Cold Start) supervised fine-tuning only, without subsequent RL fine-tuning. | |
| We provide three variants of AdaReasoner-7B, each optimized for different use cases: | |
| | Model | Description | Hugging Face | | |
| |------|-------------|--------------| | |
| | **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) | | |
| | **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) | | |
| **Key Differences:** | |
| - **Randomized**: Trained with adaptive learning method, enabling zero-shot generalization to novel tools and task configurations | |
| - **Non-Randomized**: Trained without adaptive learning, offering more predictable behavior on familiar tools but lacking generalization | |
| ## π Performance | |
| Please refer to our paper for detailed benchmark results across multiple visual reasoning tasks. | |
| ## π Citation | |
| If you use this model in your research, please cite: | |
| ```bibtex | |
| @article{adareasoner2024, | |
| title={Dynamic Tool Orchestration for Iterative Visual Reasoning}, | |
| author={AdaReasoner Team}, | |
| journal={arXiv preprint arXiv:XXXX.XXXXX}, | |
| year={2024} | |
| } | |
| ``` | |
| ## π License | |
| Apache 2.0 | |
| ## π€ Acknowledgments | |
| This model is part of the AdaReasoner project. For more information, visit our [GitHub repository](https://github.com/ssmisya/AdaReasoner). | |
| ## π§ Contact | |
| For questions and feedback, please open an issue in our [GitHub repository](https://github.com/ssmisya/AdaReasoner). | |