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2025 ICML ICML 2025

QoS-Efficient Serving of Multiple Mixture-of-Expert LLMs Using Partial Runtime Reconfiguration

Abstract

No abstract available. No abstract was captured for this paper when its proceedings were scraped - most often an older edition published without one online. How the corpus is built.

Authors

Hamidreza Imani, Jiaxin Peng, Peiman Mohseni, Abdolah Amirany, Tarek El-Ghazawi

Topics

Artificial Intelligence > Core AI > Model Compression Machine Learning > Application Areas > Efficient Computing Artificial Intelligence > Core AI > Large Language Models

Keywords

memory footprint large language model mixture-of-experts throughput expert consolidation runtime partial reconfiguration
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