13 citations · 13 across the 2 of their papers we have counts for
3 papers
cs.DC2026
Xronos: Heterogeneity-Aware Tensor Parallelism for Collaborative LLM Fine-Tuning on Edge CPUs
Wonmi Choi, Sunjae Park, Dohyeok Kwon +4
Collaborative fine-tuning on edge devices adapts large language models to domain-specific data while keeping each device's data local. State-of-the-art (SOTA) collaborative fine-tu…
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…
cs.DC2025★ 13 cited
Prediction of Permissioned Blockchain Performance for Resource Scaling Configurations
Seungwoo Jung, Yeonho Yoo, Gyeongsik Yang +1
Blockchain is increasingly offered as blockchain-as-a-service (BaaS) by cloud service providers. However, configuring BaaS appropriately for optimal performance and reliability res…