Publications (11)
WeSep: A Modular and Cue-Composable Framework for Target Speaker Extraction
Ke Zhang, Xiaoyang Yu, Haoyu Li +3
WeSep is a modular framework that treats target speaker extraction as a cue‑conditioned learning problem, separating cue modules from the separator backbone to flexibly incorporate…
PEVLM: Parallel Encoding for Vision-Language Models
Letian Kang, Shixian Luo, Yiqiang Li +5
Vision-Language Models (VLMs) have demonstrated strong capabilities in multimodal understanding and generation tasks. However, their application to long video understanding remains…
Improving monotonic optimization in heterogeneous multi-agent reinforcement learning with optimal marginal deterministic policy gradient
Xiaoyang Yu, Youfang Lin, Shuo Wang +1
In heterogeneous multi-agent reinforcement learning (MARL), achieving monotonic improvement plays a pivotal role in enhancing performance. The HAPPO algorithm proposes a feasible s…
FedSaaS: Class-Consistency Federated Semantic Segmentation via Global Prototype Supervision and Local Adversarial Harmonization
Xiaoyang Yu, Xiaoming Wu, Xin Wang +3
Federated semantic segmentation enables pixel-level classification in images through collaborative learning while maintaining data privacy. However, existing research commonly over…
An Adaptive Underwater Image Enhancement Framework via Multi-Domain Fusion and Color Compensation
Yuezhe Tian, Kangchen Yao, Xiaoyang Yu
Underwater optical imaging is severely degraded by light absorption, scattering, and color distortion, hindering visibility and accurate image analysis. This paper presents an adap…
GHQ: Grouped Hybrid Q Learning for Heterogeneous Cooperative Multi-agent Reinforcement Learning
Xiaoyang Yu, Youfang Lin, Xiangsen Wang +2
Previous deep multi-agent reinforcement learning (MARL) algorithms have achieved impressive results, typically in homogeneous scenarios. However, heterogeneous scenarios are also v…