English(EN) FLAT: Resampling Image and Text into 1D Flexible-Length Aligned Transmodal Tokens for Retrieval and Generation

FLAT框架统一图像和文本以实现多模态生成

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-16 04:00

研究人员推出了一种新颖的联合多模态表示学习和生成框架FLAT。FLAT将视觉和文本输入映射到统一的一维序列空间，从而实现判别性语义描述和生成条件。该方法允许跨模态检索和生成具有动态输出长度，在文本到图像生成和图像字幕生成等任务上取得了强劲的性能。 AI

影响这项研究可能导致更集成、更高效的多模态AI系统，用于图像生成和字幕生成等任务。

排序理由该集群包含一篇详细介绍新模型/框架的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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

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arXiv cs.CV TIER_1 English(EN) · Guangyu Sun, Shlok Kumar Mishra, Wentao Bao, Robert Zhenheng Yang, Xiao Wang, Xiyuan Wang, Yujunrong Ma, Chen Yuan, Max Xiangjun Fan, Jun Xiao, Jianpeng Cheng · 2026-09-16 04:00

FLAT：将图像和文本重采样为一维灵活长度的对齐跨模态令牌，用于检索和生成

arXiv:2609.16591v1 Announce Type: new Abstract: Traditional multimodal representation learning and generation are two stages: a contrastive or self-supervised visual encoder is trained first, followed by a separate downstream generative model. This setup bottlenecks generative pe…