4 papers
Training-Free Looped Transformers
Lizhang Chen, Jonathan Li, Chen Liang +2
We introduce training-free looped transformers, in which a lightweight inference-time wrapper loops a contiguous mid-stack block of layers of a frozen checkpoint without additional…
-Balancing for Mixture-of-Experts Training
Lizhang Chen, Jonathan Li, Qi Wang +5
Mixture-of-Experts (MoE) models rely on balanced expert utilization to fully realize their scalability. However, existing load-balancing methods are largely heuristic and operate o…
Cautious Weight Decay
Lizhang Chen, Jonathan Li, Kaizhao Liang +6
We introduce Cautious Weight Decay (CWD), a one-line, optimizer-agnostic modification that applies weight decay only to parameter coordinates whose signs align with the optimizer u…
Muon Optimizes Under Spectral Norm Constraints
Lizhang Chen, Jonathan Li, Qiang Liu
The pursuit of faster optimization algorithms remains an active and important research direction in deep learning. Recently, the Muon optimizer [JJB+24] has demonstrated promising…