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Kyeng-Hun Lee

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Conference Open access 2026

Grouped Adaptive Weight Sharing (GAWS): An Inference-Efficient Adaptation Method for Large Language Models

GAWS is proposed, a novel adapter design based on structured Kronecker product decomposition that is positioned as a Pareto-efficient solution for deploying adapted LLMs in latency-sensitive settings, balancing the low latency of compressed adapters with the accuracy of LoRA.

Eman Alsuradi, Junhyung Lee, Kyeng-Hun Lee et al. · 0 citations

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