4 papers
SWE-MiniSandbox: Container-Free Reinforcement Learning for Building Software Engineering Agents
Danlong Yuan, Wei Wu, Enhan Zhao +4
Reinforcement learning (RL) has become a key paradigm for training software engineering (SWE) agents, but existing pipelines typically rely on per-task containers for isolation. At…
More Than Memory Savings: Zeroth-Order Optimization Mitigates Forgetting in Continual Learning
Wanhao Yu, Zheng Wang, Shuteng Niu +2
Zeroth-order (ZO) optimization has gained attention as a memory-efficient alternative to first-order (FO) methods, particularly in settings where gradient computation is expensive…
Rethinking Continual Learning with Progressive Neural Collapse
Zheng Wang, Wanhao Yu, Li Yang +1
Continual Learning (CL) seeks to build an agent that can continuously learn a sequence of tasks, where a key challenge, namely Catastrophic Forgetting, persists due to the potentia…
Noise-Adaptive Layerwise Learning Rates: Accelerating Geometry-Aware Optimization for Deep Neural Network Training
Jie Hao, Xiaochuan Gong, Jie Xu +2
Geometry-aware optimization algorithms, such as Muon, have achieved remarkable success in training deep neural networks (DNNs). These methods leverage the underlying geometry of DN…