Gen-Searcher-8B Model
This repository contains the Gen-Searcher-8B model presented in Gen-Searcher: Reinforcing Agentic Search for Image Generation.
Project Page | GitHub Repository | Paper
π Intro
We introduce Gen-Searcher, as the first attempt to train a multimodal deep research agent for image generation that requires complex real-world knowledge. Gen-Searcher can search the web, browse evidence, reason over multiple sources, and search visual references before generation, enabling more accurate and up-to-date image synthesis in real-world scenarios.
We build two dedicated training datasets Gen-Searcher-SFT-10k, Gen-Searcher-RL-6k and one new benchmark KnowGen for search-grounded image generation.
Gen-Searcher achieves significant improvements, delivering 15+ point gains on the KnowGen and WISE benchmarks. It also demonstrates strong transferability to various image generators.
All code, models, data, and benchmark are fully released.
π₯ Demo
Inference Process Example
For more examples, please refer to our website [πProject Page]
π Training and Inference
For detailed instructions on setup, SFT/RL training, and inference, please refer to the official GitHub repository.
π Citation
If you find our work helpful for your research, please consider citing our work:
@article{feng2025gensearcher,
title={Gen-Searcher: Reinforcing Agentic Search for Image Generation},
author={Feng, Kaituo and Zhang, Manyuan and Chen, Shuang and Lin, Yunlong and Fan, Kaixuan and Jiang, Yilei and Li, Hongyu and Zheng, Dian and Wang, Chenyang and Yue, Xiangyu},
journal={arXiv preprint arXiv:2603.28767},
year={2025}
}
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