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Updated: Jan 15, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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Published on: December 6, 2024

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视觉语言模型的多阶段知识整合,用于持续学习

Hongsheng Zhang, Zhong Ji, Jingren Liu

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
    |January 13, 2026
    PubMed
    概括

    视觉语言模型 (VLMs) 可以通过多阶段知识集成 (MulKI) 改进,以实现持续学习. MulKI提高了对新数据的适应性,同时保留了现有知识,克服了当前蒸方法的局限性.

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