4 citations · 12 across the 24 of their papers we have counts for
5 papers · 1 filter
Low-probability Tokens Sustain Exploration in Reinforcement Learning with Verifiable Reward
Guanhua Huang, Tingqiang Xu, Mingze Wang +7
Reinforcement Learning with Verifiable Rewards (RLVR) has propelled Large Language Models in complex reasoning, yet its scalability is often hindered by a training bottleneck where…
On the Surprising Effectiveness of a Single Global Merging in Decentralized Learning
Tongtian Zhu, Tianyu Zhang, Mingze Wang +2
Decentralized learning provides a scalable alternative to parameter-server-based training, yet its performance is often hindered by limited peer-to-peer communication. In this pape…
GradPower: Powering Gradients for Faster Language Model Pre-Training
Jinbo Wang, Mingze Wang, Jiaqi Zhang +5
We propose GradPower, a lightweight gradient-transformation technique for accelerating language model pre-training. Given a gradient vector , GradPower first applies the…
On the Expressive Power of Mixture-of-Experts for Structured Complex Tasks
Mingze Wang, Weinan E
Mixture-of-experts networks (MoEs) have demonstrated remarkable efficiency in modern deep learning. Despite their empirical success, the theoretical foundations underlying their ab…
The Sharpness Disparity Principle in Transformers for Accelerating Language Model Pre-Training
Jinbo Wang, Mingze Wang, Zhanpeng Zhou +3
Transformers consist of diverse building blocks, such as embedding layers, normalization layers, self-attention mechanisms, and point-wise feedforward networks. Thus, understanding…