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English(EN) FireRed-Image-Edit-1.0 Technical Report

FireRed-Image-Edit 通过大规模训练推动基于指令的图像编辑

研究人员推出了 FireRed-Image-Edit,这是一款用于基于指令的图像编辑的扩散 transformer 模型。该模型利用了庞大的 16 亿样本训练语料库,该语料库经过精心策划和筛选,包含超过 1000 万个高质量的图像生成和编辑任务配对。FireRed-Image-Edit 采用了多阶段训练流程,并引入了数据效率和优化的新颖技术,包括非对称梯度优化和可微分一致性损失。其性能在新建立的 REDEdit-Bench 上得到了验证,该基准涵盖了 15 个编辑类别,并在该基准上展示了与现有系统相比具有竞争力的结果。 AI

影响 引入了一个新的基于指令的图像编辑基准和模型,有可能提高性能并提供新的评估标准。

排序理由 该集群描述了一份技术报告,详细介绍了在 arXiv 上发布的新模型和基准。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

FireRed-Image-Edit 通过大规模训练推动基于指令的图像编辑

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Tool
该集群描述了一份技术报告,详细介绍了在 arXiv 上发布的新模型和基准。[lever_c_demoted from research: ic=1 ai=1.0]
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Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
paper, model release
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
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Story freshness
114 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

完整方法见我们的编辑标准。

报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Super Intelligence Team, Changhao Qiao, Chao Hui, Chen Li, Cunzheng Wang, Dejia Song, Jiale Zhang, Jing Li, Qiang Xiang, Runqi Wang, Shuang Sun, Wei Zhu, Xu Tang, Yao Hu, Yibo Chen, Yuhao Huang, Yuxuan Duan, Zhiyi Chen, Ziyuan Guo ·

    FireRed-Image-Edit-1.0 技术报告

    arXiv:2602.13344v2 Announce Type: replace Abstract: We present FireRed-Image-Edit, a diffusion transformer for instruction-based image editing that achieves state-of-the-art performance through systematic optimization of data curation, training methodology, and evaluation design.…