26 citations · 46 across the 4 of their papers we have counts for
5 papers
KV Cache Translation across Heterogeneous Large Language Models
Jin-woo Lee, Minkyung Song, Junghyun Oh +4
Heterogeneous Large Language Model (LLM) systems increasingly share contexts, retrieved evidence, and multi-agent dialogue histories, yet their internal key-value (KV) caches remai…
SCALE: Upscaled Continual Learning of Large Language Models
Jin-woo Lee, Junhwa Choi, Bongkyu Hwang +8
We revisit continual pre-training for large language models and argue that progress now depends more on scaling the right structure than on scaling parameters alone. We introduce S…
Accurate and Fast Federated Learning via IID and Communication-Aware Grouping
Jin-woo Lee, Jaehoon Oh, Yooju Shin +2
Federated learning has emerged as a new paradigm of collaborative machine learning; however, it has also faced several challenges such as non-independent and identically distribute…
Accurate and Fast Federated Learning via Combinatorial Multi-Armed Bandits
Taehyeon Kim, Sangmin Bae, Jin-woo Lee +1
Federated learning has emerged as an innovative paradigm of collaborative machine learning. Unlike conventional machine learning, a global model is collaboratively learned while da…
TornadoAggregate: Accurate and Scalable Federated Learning via the Ring-Based Architecture
Jin-woo Lee, Jaehoon Oh, Sungsu Lim +2
Federated learning has emerged as a new paradigm of collaborative machine learning; however, many prior studies have used global aggregation along a star topology without much cons…