2.3k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Shuguang Cui5 profiles29 · h 63
- Arnulf Jentzen22 · h 49
- Z. Luo18 · h 89
- Guangxu Zhu5 profiles17 · h 33
- Xiaoguang Han2 profiles15 · h 42
- Hang Li2 profiles13 · h 18
- Tsung-Hui Chang11 · h 45
- Qingjiang Shi3 profiles9 · h 36
- H. Poor2 profiles7 · h 141
- Rui Zhang3 profiles7 · h 137
- Shiyin Li7 · h 21
- Xiaoyang Li2 profiles7 · h 9
- Chinese University of Hong Kong, ShenzhenCN158 papers
- University of MünsterDE21 papers
- Chinese University of Hong KongHK16 papers
- University of Hong KongHK15 papers
- ETH ZurichCH14 papers
- Sun Yat-sen UniversityCN13 papers
- National University of SingaporeSG12 papers
- Peng Cheng LaboratoryCN10 papers
- Princeton UniversityUS10 papers
- Tongji UniversityCN10 papers
- Beijing University of Posts and TelecommunicationsCN9 papers
- Chinese Academy of SciencesCN9 papers
201 papers
MetaCom: Meta Codebook Learning for Robust V2X Semantic Communications
Muge Yu, Danlan Huang, Xinyi Zhou +2
Collaborative perception in Vehicle-to-Everything (V2X) networks faces dual challenges: strictly limited bandwidth and channel impairments. Existing static quantization schemes oft…
A Sparse Corner-Difference MILP for Minimum Square Tiling
Zhuo Yu, Yuan Wang, Zhuo Liu
We study the problem of tiling an square with axis-aligned squares whose side lengths are integers strictly less than , with the objective of minimizing the number o…
Point-Cloud-Assistant Localized Statistical Channel Prediction by Tangent Gaussian Splatting
Ye Xue, Yiheng Wang, Xinhua Shao +3
Accurate, site-specific channel information is crucial for optimizing next-generation wireless networks. Among various approaches, localized statistical channel modeling (LSCM), wh…
USCNet: Transformer-Based Multimodal Fusion with Segmentation Guidance for Urolithiasis Classification
Changmiao Wang, Songqi Zhang, Yongquan Zhang +9
Kidney stone disease ranks among the most prevalent conditions in urology, and understanding the composition of these stones is essential for creating personalized treatment plans…
WeatherRemover: All-in-one Adverse Weather Removal with Multi-scale Feature Map Compression
Weikai Qu, Sijun Liang, Cheng Pan +6
Photographs taken in adverse weather conditions often suffer from blurriness, occlusion, and low brightness due to interference from rain, snow, and fog. These issues can significa…
Balancing Efficiency and Restoration: Lightweight Mamba-Based Model for CT Metal Artifact Reduction
Weikai Qu, Sijun Liang, Xianfeng Li +7
In computed tomography imaging, metal implants frequently generate severe artifacts that compromise image quality and hinder diagnostic accuracy. There are three main challenges in…
Explainable Graph Representation Learning via Graph Pattern Analysis
Xudong Wang, Ziheng Sun, Chris Ding +1
Explainable artificial intelligence (XAI) is an important area in the AI community, and interpretability is crucial for building robust and trustworthy AI models. While previous wo…
StrucADT: Generating Structure-controlled 3D Point Clouds with Adjacency Diffusion Transformer
Zhenyu Shu, Jiajun Shen, Zhongui Chen +2
In the field of 3D point cloud generation, numerous 3D generative models have demonstrated the ability to generate diverse and realistic 3D shapes. However, the majority of these a…
No Modality Left Behind: Adapting to Missing Modalities via Knowledge Distillation for Brain Tumor Segmentation
Shenghao Zhu, Yifei Chen, Weihong Chen +6
Accurate brain tumor segmentation is essential for preoperative evaluation and personalized treatment. Multi-modal MRI is widely used due to its ability to capture complementary tu…
RTGMFF: Enhanced fMRI-based Brain Disorder Diagnosis via ROI-driven Text Generation and Multimodal Feature Fusion
Junhao Jia, Yifei Sun, Yunyou Liu +5
Functional magnetic resonance imaging (fMRI) is a powerful tool for probing brain function, yet reliable clinical diagnosis is hampered by low signal-to-noise ratios, inter-subject…
PrinciplismQA: A Philosophy-Grounded Approach to Assessing LLM-Human Clinical Medical Ethics Alignment
Chang Hong, Minghao Wu, Qingying Xiao +5
As medical LLMs transition to clinical deployment, assessing their ethical reasoning capability becomes critical. While achieving high accuracy on knowledge benchmarks, LLMs lack v…
A Disentangled Representation Learning Framework for Low-altitude Network Coverage Prediction
Xiaojie Li, Zhijie Cai, Nan Qi +5
The expansion of the low-altitude economy has underscored the significance of Low-Altitude Network Coverage (LANC) prediction for designing aerial corridors. While accurate LANC fo…
Adaptive feature capture method for solving partial differential equations with near singular solutions
Yangtao Deng, Qiaolin He, Xiaoping Wang
Partial differential equations (PDEs) with near singular solutions pose significant challenges for traditional numerical methods, particularly in complex geometries where mesh gene…
Semantic Feature Division Multiple Access for Digital Semantic Broadcast Channels
Shuai Ma, Zhiye Sun, Bin Shen +5
In this paper, we propose a digital semantic feature division multiple access (SFDMA) paradigm in multi-user broadcast (BC) networks for the inference and the image reconstruction…
FCBoost-Net: A Generative Network for Synthesizing Multiple Collocated Outfits via Fashion Compatibility Boosting
Dongliang Zhou, Haijun Zhang, Jianghong Ma +2
Outfit generation is a challenging task in the field of fashion technology, in which the aim is to create a collocated set of fashion items that complement a given set of items. Pr…
AnyEnhance: A Unified Generative Model with Prompt-Guidance and Self-Critic for Voice Enhancement
Junan Zhang, Jing Yang, Zihao Fang +5
We introduce AnyEnhance, a unified generative model for voice enhancement that processes both speech and singing voices. Based on a masked generative model, AnyEnhance is capable o…
Energy-Efficient SLAM via Joint Design of Sensing, Communication, and Exploration Speed
Zidong Han, Ruibo Jin, Xiaoyang Li +3
To support future spatial machine intelligence applications, lifelong simultaneous localization and mapping (SLAM) has drawn significant attentions. SLAM is usually realized based…
Movable Antenna-Aided Near-Field Integrated Sensing and Communication
Jingze Ding, Zijian Zhou, Xiaodan Shao +2
Integrated sensing and communication (ISAC) is emerging as a pivotal technology for next-generation wireless networks. However, existing ISAC systems are based on fixed-position an…
BS-LDM: Effective Bone Suppression in High-Resolution Chest X-Ray Images with Conditional Latent Diffusion Models
Yifei Sun, Zhanghao Chen, Hao Zheng +7
Lung diseases represent a significant global health challenge, with Chest X-Ray (CXR) being a key diagnostic tool due to its accessibility and affordability. Nonetheless, the detec…
Parallel Graver Basis Extraction for Nonlinear Integer Optimization
Wenbo Liu, Akang Wang, Wenguo Yang
The augmentation scheme provides a nontraditional approach to nonlinear integer programming by iteratively refining incumbent solutions along objective-improving directions from th…
CSI-BERT2: A BERT-inspired Framework for Efficient CSI Prediction and Classification in Wireless Communication and Sensing
Zijian Zhao, Fanyi Meng, Zhonghao Lyu +3
Channel state information (CSI) is a fundamental component in both wireless communication and sensing systems, enabling critical functions such as radio resource optimization and e…
LoFi: Vision-Aided Label Generator for Wi-Fi Localization and Tracking
Zijian Zhao, Tingwei Chen, Fanyi Meng +4
Data-driven Wi-Fi localization and tracking have shown great promise due to their lower reliance on specialized hardware compared to model-based methods. However, most existing dat…
KNN-MMD: Cross Domain Wireless Sensing via Local Distribution Alignment
Zijian Zhao, Zhijie Cai, Tingwei Chen +4
Wireless sensing has recently found widespread applications in diverse environments, including homes, offices, and public spaces. By analyzing patterns in channel state information…
Speech Separation with Pretrained Frontend to Minimize Domain Mismatch
Wupeng Wang, Zexu Pan, Xinke Li +2
Speech separation seeks to separate individual speech signals from a speech mixture. Typically, most separation models are trained on synthetic data due to the unavailability of ta…