1 citations · 1 across the 5 of their papers we have counts for
5 papers
Muon Outperforms Adam in Tail-End Associative Memory Learning
Shuche Wang, Fengzhuo Zhang, Jiaxiang Li +6
The Muon optimizer is consistently faster than Adam in training Large Language Models (LLMs), yet the mechanism underlying its success remains unclear. This paper demystifies this…
BanditSpec: Adaptive Speculative Decoding via Bandit Algorithms
Yunlong Hou, Fengzhuo Zhang, Cunxiao Du +6
Speculative decoding has emerged as a popular method to accelerate the inference of Large Language Models (LLMs) while retaining their superior text generation performance. Previou…
Error Analyses of Auto-Regressive Video Diffusion Models: A Unified Framework
Jing Wang, Fengzhuo Zhang, Xiaoli Li +5
Auto-Regressive Video Diffusion Models (AR-VDMs) have shown strong capabilities in generating long, photorealistic videos, but suffer from two key limitations: (i) history forgetti…
Learning Regularized Graphon Mean-Field Games with Unknown Graphons
Fengzhuo Zhang, Vincent Y. F. Tan, Zhaoran Wang +1
We design and analyze reinforcement learning algorithms for Graphon Mean-Field Games (GMFGs). In contrast to previous works that require the precise values of the graphons, we aim…
Learning Regularized Monotone Graphon Mean-Field Games
Fengzhuo Zhang, Vincent Y. F. Tan, Zhaoran Wang +1
This paper studies two fundamental problems in regularized Graphon Mean-Field Games (GMFGs). First, we establish the existence of a Nash Equilibrium (NE) of any -regularized GMF…