3 papers
cs.CL2026
Pruning and Distilling Mixture-of-Experts into Dense Language Models
Junhyuck Kim, Jihun Yun, Haechan Kim +3
Mixture-of-Experts (MoE) is now the dominant architecture for frontier language models, yet it requires all expert parameters to be loaded in memory, making it less preferable for…
cs.LG2026
Uniform Spectral Growth and Convergence of Muon in LoRA-Style Matrix Factorization
Changmin Kang, Jihun Yun, Baekrok Shin +2
Spectral gradient descent (SpecGD) orthogonalizes the matrix parameter updates and has inspired practical optimizers such as Muon. They often perform well in large language model (…
cs.LG2026
Coverage Improvement and Fast Convergence of On-policy Preference Learning
Juno Kim, Jihun Yun, Jason D. Lee +1
Online on-policy preference learning algorithms for language model alignment such as online direct policy optimization (DPO) can significantly outperform their offline counterparts…