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Seung-Min Cha

2 papers hereh-index 00 citations2 works total

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author position
  • middle author2

Across the 2 of 2 papers where every author was matched, so the position is known.

fields
  • cs.AI1
  • cs.RO1

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1 paper · 1 filter

cs.AI2026

Residual Sparsification via Output Importance for Compressing Mixture-of-Experts LLMs

Seungwoo Jung, Dohyeok Kwon, Seungmin Cha +4

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 redu…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.