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Updated: Jan 6, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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一个框架,以提高黑盒子变化推理的可靠性

Manushi Welandawe1, Michael Riis Andersen2, Aki Vehtari3

  • 1Department of Mathematics & Statistics, Boston University, USA.

Journal of machine learning research : JMLR
|December 3, 2025
PubMed
概括

强大的和自动化的黑盒VI (RABVI) 增强了贝叶斯推理的可靠性. 这个框架自动化优化,检测不准确的近似,并平衡精度与计算成本,以获得更好的结果.

关键词:
黑子的变化推理推理.固定学习率的学习率.随机优化的优化 随机优化有对称的KL分歧.

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