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English(EN) Intern Lumina U2: A Multi-Codebook Diffusion Large Language Model for Omni-Visual Understanding and Image Generation

Intern Lumina U2：统一的全视觉模型实现领先性能

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员推出了 Intern Lumina U2，这是一种新颖的扩散大型语言模型，专为图像、视频和 3D 资产的全方位视觉理解和生成而设计。该模型独特地在单个骨干网络中采用了多码本离散视觉令牌，在保持与文本建模兼容性的同时增强了表示能力。Intern Lumina U2 在视觉理解、文本到图像生成和图像编辑的各种基准测试中表现出领先性能，其优化的采样策略将图像生成速度提高了 4.45 倍。该模型已在 Ascend 和 NVIDIA 硬件上通过了跨平台有效性验证。 AI

影响 这种统一的模型架构可以简化多模态人工智能的开发，并提高视觉理解和生成任务的效率。

排序理由 发布了一篇详细介绍新型人工智能模型的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 Hugging Face Daily Papers 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

Intern Lumina U2：统一的全视觉模型实现领先性能

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发布了一篇详细介绍新型人工智能模型的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [2]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    Intern Lumina U2：用于全视觉理解和图像生成的、多码本扩散大语言模型

    Intern Lumina U2 is a diffusion language model that uses multi-codebook discrete visual tokens to unify image, video, and 3D generation with text in a single backbone, achieving high performance and faster inference.

  2. arXiv cs.CV TIER_1 English(EN) · Qian Yu, Zongyang Qiu, Juncheng Yan, Hongliang Li, Qi Qin, Keqi Wang, Siqi Luo, Junkui Ju, Yapeng Mi, Tiantian Lu, Tian Liu, Pengyu Xie, Chenhao Ji, Minghui Zhang, Yiang Zhao, Siyu Yan, Haiying Xu, Yanbo Wang, Jianghan Shen, Yuandong Pu, Jiayi Lei, Borui… ·

    Intern Lumina U2：用于全视觉理解和图像生成的、多码本扩散大型语言模型

    arXiv:2610.20818v1 Announce Type: new Abstract: Unified multimodal generation covers discrete, continuous, and hybrid paradigms. Discrete approaches with single-codebook visual tokenizers align naturally with text modeling but have limited representational capacity. Continuous an…

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