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Updated: May 21, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

474

2D转换器:将大型语言模型扩展到具有很少内存的长文本.

Xingyang He, Jie Liu, Yutai Duan

    IEEE transactions on neural networks and learning systems
    |March 21, 2025
    PubMed
    概括

    本研究介绍了二维变压器 (2D-former),这是一种新的架构,可以有效地扩展大型语言模型 (LLMs) 的上下文窗口. 2D-former显著降低了计算成本和GPU内存,通过全注意力机制弥合了性能差距.

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