1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2026
Robust Ultra Low-Bit Post-Training Quantization via Stable Diagonal Curvature Estimate
Jaemin Kim, Sungkyun Kim, Junyeol Lee +1
Large Language Models (LLMs) are widely used across many domains, but their scale makes deployment challenging. Post-Training Quantization (PTQ) reduces memory footprint without re…
cs.CL2025
Speculative Verification: Exploiting Information Gain to Refine Speculative Decoding
Sungkyun Kim, Jaemin Kim, Dogyung Yoon +3
LLMs have low GPU efficiency and high latency due to autoregressive decoding. Speculative decoding (SD) mitigates this using a small draft model to speculatively generate multiple…
cs.LG2021★ 1 cited
Scheduling Optimization Techniques for Neural Network Training
Hyungjun Oh, HyeongJu Kim, Jiwon Seo
Neural network training requires a large amount of computation and thus GPUs are often used for the acceleration. While they improve the performance, GPUs are underutilized during…