JarvisEvo/JarvisEvo

JarvisEvo: Towards a Self-Evolving Photo Editing Agent with Synergistic Editor-Evaluator Optimization.

🌍 Introduction

JarvisEvo performs interleaved multimodal Chain-of-Thought (iMCoT) reasoning for image editing, which marries multi-step planning, dynamic tool orchestration, and iterative visual feedback. This closed-loop workflow incorporates self-evaluation and refinement to ensure the final output is both visually compelling and faithful to the creative vision. By seamlessly integrating professional tools like Adobe Lightroom for precision adjustments and Qwen-Image-Edit for generative tasks, the system achieves a unique synergy of expert- level refinement and creative synthesis.

📜 Citation

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@article{lin2025jarvisevo,
  title={JarvisEvo: Towards a Self-Evolving Photo Editing Agent with Synergistic Editor-Evaluator Optimization},
  author={Lin, Yunlong and Wang, Linqing and Lin, Kunjie and Lin, Zixu and Gong, Kaixiong and Li, Wenbo and Lin, Bin and Li, Zhenxi and Zhang, Shiyi and Peng, Yuyang and others},
  journal={arXiv preprint arXiv:2511.23002},
  year={2025}
}