15 citations · 15 across the 11 of their papers we have counts for
4 papers · 1 filter
Efficient Multi-turn RL for GUI Agents via Decoupled Training and Adaptive Data Curation
Pengxiang Li, Zechen Hu, Zirui Shang +15
Vision-language model (VLM) based GUI agents show promise for automating complex desktop and mobile tasks, but face significant challenges in applying reinforcement learning (RL):…
AdaptGrad: Adaptive Sampling to Reduce Noise
Linjiang Zhou, Chao Ma, Zepeng Wang +2
Gradient Smoothing is an efficient approach to reducing noise in gradient-based model explanation method. SmoothGrad adds Gaussian noise to mitigate much of these noise. However, t…
: Towards Effective and Efficient Cost Function Design for Safe Reinforcement Learning via Large Language Model
Zepeng Wang, Chao Ma, Linjiang Zhou +4
Different classes of safe reinforcement learning algorithms have shown satisfactory performance in various types of safety requirement scenarios. However, the existing methods main…
Axiomatization of Gradient Smoothing in Neural Networks
Linjiang Zhou, Xiaochuan Shi, Chao Ma +1
Gradients play a pivotal role in neural networks explanation. The inherent high dimensionality and structural complexity of neural networks result in the original gradients contain…