2 citations · 2 across the 4 of their papers we have counts for
4 papers
Let's Scale Step by Step: Compute-Efficient Hyperparameter Transfer for Large-Scale Mixture-of-Experts
Nayeon Kim, Hojin Lee, Yunju Bak +2
Mixture-of-Experts (MoE) architectures significantly expand model capacity without a proportional increase in computational cost. However, optimizing their hyperparameters---partic…
Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph
Akash Vishwakarma, Hojin Lee, Mohith Suresh +4
The emergence of capable large language model (LLM) based agents necessitates memory architectures that transcend mere data storage, enabling continuous learning, nuanced reasoning…
Kanana: Compute-efficient Bilingual Language Models
Kanana LLM Team, Yunju Bak, Hojin Lee +26
We introduce Kanana, a series of bilingual language models that demonstrate exceeding performance in Korean and competitive performance in English. The computational cost of Kanana…
Controlled Text Generation for Black-box Language Models via Score-based Progressive Editor
Sangwon Yu, Changmin Lee, Hojin Lee +1
Controlled text generation is very important for the practical use of language models because it ensures that the produced text includes only the desired attributes from a specific…