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AdaReasoner/
AdaReasoner-TC-7B-Non-Randomized

Name: AdaReasoner-TC-7B-Non-Randomized
Availability: InStock

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qwen2_5_vl

2601.18631

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Dynamic Tool Orchestration for Iterative Visual Reasoning

🔔 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

📋 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.	🤗 Link
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.	🤗 Link

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

📊 Performance

Please refer to our paper for detailed benchmark results across multiple visual reasoning tasks.

📚 Citation

If you use this model in your research, please cite:

bibtex

@article{song2026adareasoner,
  title={AdaReasoner: Dynamic Tool Orchestration for Iterative Visual Reasoning},
  author={Song, Mingyang and Sun, Haoyu and Gu, Jiawei and Li, Linjie and Xu, Luxin and Krishna, Ranjay and Cheng, Yu},
  journal={arXiv preprint arXiv:2601.18631},
  year={2026}
}

📄 License

Apache 2.0

🤝 Acknowledgments

This model is part of the AdaReasoner project. For more information, visit our GitHub repository.

📧 Contact

For questions and feedback, please open an issue in our GitHub repository.

AdaReasoner/AdaReasoner-TC-7B-Non-Randomized