1 citations · 1 across the 10 of their papers we have counts for
16 papers
Generalizable Geometric Prior and Recurrent Spiking Feature Learning for Humanoid Robot Manipulation
Xuetao Li, Wenke Huang, Mang Ye +4
Humanoid robot manipulation is a crucial research area for executing diverse human-level tasks, involving high-level semantic reasoning and low-level action generation. However, pr…
RGMP: Recurrent Geometric-prior Multimodal Policy for Generalizable Humanoid Robot Manipulation
Xuetao Li, Wenke Huang, Nengyuan Pan +7
Humanoid robots exhibit significant potential in executing diverse human-level skills. However, current research predominantly relies on data-driven approaches that necessitate ext…
SafeGRPO: Self-Rewarded Multimodal Safety Alignment via Rule-Governed Policy Optimization
Xuankun Rong, Wenke Huang, Tingfeng Wang +3
Multimodal large language models (MLLMs) have demonstrated impressive reasoning and instruction-following capabilities, yet their expanded modality space introduces new composition…
Divide, Conquer and Unite: Hierarchical Style-Recalibrated Prototype Alignment for Federated Medical Segmentation
Xingyue Zhao, Wenke Huang, Xingguang Wang +5
Federated learning enables multiple medical institutions to train a global model without sharing data, yet feature heterogeneity from diverse scanners or protocols remains a major…
MAPO: Mixed Advantage Policy Optimization
Wenke Huang, Quan Zhang, Yiyang Fang +11
Recent advances in reinforcement learning for foundation models, such as Group Relative Policy Optimization (GRPO), have significantly improved the performance of foundation models…
S2FGL: Spatial Spectral Federated Graph Learning
Zihan Tan, Suyuan Huang, Guancheng Wan +3
Federated Graph Learning (FGL) combines the privacy-preserving capabilities of federated learning (FL) with the strong graph modeling capability of Graph Neural Networks (GNNs). Cu…