3 papers
cs.AI2025
SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging
Zijun Chen, Zhanpeng Zhou, Bo Zhang +3
Model merging has gained increasing attention due to its intriguing property: interpolating the parameters of different task-specific fine-tuned models leads to multi-task abilitie…
cs.LG2025
New Evidence of the Two-Phase Learning Dynamics of Neural Networks
Zhanpeng Zhou, Yongyi Yang, Mahito Sugiyama +1
Understanding how deep neural networks learn remains a fundamental challenge in modern machine learning. A growing body of evidence suggests that training dynamics undergo a distin…
cs.LG2025
On the Cone Effect in the Learning Dynamics
Zhanpeng Zhou, Yongyi Yang, Jie Ren +2
Understanding the learning dynamics of neural networks is a central topic in the deep learning community. In this paper, we take an empirical perspective to study the learning dyna…