arxiv
PublishedSeptember 2, 2026 at 4:00 AM
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Residual Sparsification via Output Importance for Compressing Mixture-of-Experts LLMs
Publisher summary· verbatim
arXiv:2609.00575v1 Announce Type: new Abstract: Mixture-of-experts (MoE) architectures scale large language models efficiently, but they demand massive GPU memory. To cope with such demand, models are commonly compressed to reduce their memory footprint. Residual sparsification is a representative c
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Originally published on arxiv ↗