139 citations · 559 across the 73 of their papers we have counts for
75 papers
CrossRAFT: Cross-Domain Complex-Valued Feature Extraction for Ultrasound Motion Estimation
Yang Leng, Yuchen Tang, Kai-Hang Yiu +2
Accurate multi-dimensional motion estimation is fundamental to broad biomedical ultrasound applications, primarily performed using real-valued radio-frequency (RF), analytic, and i…
Memory-Native Non-Terrestrial Networks for Embodied Intelligence
Chengyang Li, Yikun Wang, Jiahui He +6
Non-terrestrial networks (NTN) provide ubiquitous connectivity for embodied intelligence (EI), enabling robots in the wilderness to leverage cloud resources or report critical info…
FluxBin: Flexible LUT-based Ultra-low-bit LLM Inference by Algorithm-Kernel Synergy
Qingyao Yang, Runming Yang, He Xiao +7
While binary quantization theoretically promises extreme compression and acceleration for Large Language Models (LLMs), existing research often overlooks the necessity of specializ…
Dualformer: Efficient Feature Extractor for Complex-valued Blind Communication Signal Analysis
Yurui Zhao, Xiang Wang, Jingreng Lei +3
Designing effective feature extractors is critical for blind signal analysis tasks such as automatic modulation recognition (AMR), signal scheme recognition (SSR), and \color{black…
OScaR: The Occam's Razor for Extreme KV Cache Quantization in LLMs and Beyond
Zunhai Su, Rui Yang, Chao Zhang +12
The rapid advancement toward long-context reasoning and multi-modal intelligence has made the memory footprint of the Key-Value (KV) cache a dominant memory bottleneck for efficien…
Memory Centric Power Allocation for Multi-Agent Embodied Question Answering
Chengyang Li, Shuai Wang, Kejiang Ye +5
This paper considers multi-agent embodied question answering (MA-EQA), which enables robot teams to answer queries based on their long-horizon observations. In contrast to existing…
LAGS: Low-Altitude Gaussian Splatting with Groupwise Heterogeneous Graph Learning
Yikun Wang, Yujie Wan, Wei Zuo +4
Low-altitude Gaussian splatting (LAGS) facilitates 3D scene reconstruction by aggregating aerial images from distributed drones. However, as LAGS prioritizes maximizing reconstruct…
Model Evolution Under Zeroth-Order Optimization: A Neural Tangent Kernel Perspective
Chen Zhang, Yuxin Cheng, Chenchen Ding +5
Zeroth-order (ZO) optimization enables memory-efficient training of neural networks by estimating gradients via forward passes only, eliminating the need for backpropagation. Howev…
Learning to Jointly Optimize Antenna Positioning and Beamforming for Movable Antenna-Aided Systems
Yikun Wang, Yang Li, Zeyi Ren +3
The recently emerged movable antenna (MA) and fluid antenna technologies offer promising solutions to enhance the spatial degrees of freedom in wireless systems by dynamically adju…
A General Deep Learning Framework for Wireless Resource Allocation under Discrete Constraints
Yikun Wang, Yang Li, Yik-Chung Wu +1
While deep learning (DL)-based methods have achieved remarkable success in continuous wireless resource allocation, efficient solutions for problems involving discrete variables re…
DPNet: Doppler LiDAR Motion Planning for Highly-Dynamic Environments
Wei Zuo, Zeyi Ren, Chengyang Li +7
Existing motion planning methods often struggle with rapid-motion obstacles due to an insufficient understanding of environmental changes. To address this, we propose integrating m…
A Unified Distributed Algorithm for Hybrid Near-Far Field Activity Detection in Cell-Free Massive MIMO
Jingreng Lei, Yang Li, Ziyue Wang +3
A great amount of endeavor has recently been devoted to activity detection for massive machine-type communications in cell-free multiple-input multiple-output (MIMO) systems. Howev…
Large-Scale Bayesian Tensor Reconstruction via Approximate Message Passing
Bingyang Cheng, Zhongtao Chen, Yichen Jin +4
While CANDECOMP/PARAFAC (CP) decomposition (CPD) is fundamental for tensor reconstruction, Bayesian CPD often scales poorly because variational updates require repeated matrix inve…
Unveiling the Power of Complex-Valued Transformers in Wireless Communications
Yang Leng, Qingfeng Lin, Long-Yin Yung +3
Utilizing complex-valued neural networks (CVNNs) in wireless communication tasks has received growing attention for their ability to provide natural and effective representation of…
Handling Distance Constraint in Movable Antenna Aided Systems: A General Optimization Framework
Yichen Jin, Qingfeng Lin, Yang Li +1
The movable antenna (MA) is a promising technology to exploit more spatial degrees of freedom for enhancing wireless system performance. However, the MA-aided system introduces the…
FedRC: A Rapid-Converged Hierarchical Federated Learning Framework in Street Scene Semantic Understanding
Wei-Bin Kou, Qingfeng Lin, Ming Tang +3
Street Scene Semantic Understanding (denoted as TriSU) is a crucial but complex task for world-wide distributed autonomous driving (AD) vehicles (e.g., Tesla). Its inference model…
Nonparametric Teaching of Implicit Neural Representations
Chen Zhang, Steven Tin Sui Luo, Jason Chun Lok Li +2
We investigate the learning of implicit neural representation (INR) using an overparameterized multilayer perceptron (MLP) via a novel nonparametric teaching perspective. The latte…
pFedLVM: A Large Vision Model (LVM)-Driven and Latent Feature-Based Personalized Federated Learning Framework in Autonomous Driving
Wei-Bin Kou, Qingfeng Lin, Ming Tang +8
Deep learning-based Autonomous Driving (AD) models often exhibit poor generalization due to data heterogeneity in an ever domain-shifting environment. While Federated Learning (FL)…
RIS-Aided Cooperative Mobile Edge Computing: Computation Efficiency Maximization via Joint Uplink and Downlink Resource Allocation
Zhenrong Liu, Zongze Li, Yi Gong +1
In mobile edge computing (MEC) systems, the wireless channel condition is a critical factor affecting both the communication power consumption and computation rate of the offloadin…
Activity Detection for Massive Connectivity in Cell-free Networks with Unknown Large-scale Fading, Channel Statistics, Noise Variance, and Activity Probability: A Bayesian Approach
Hao Zhang, Qingfeng Lin, Yang Li +2
Activity detection is an important task in the next generation grant-free multiple access. While there are a number of existing algorithms designed for this purpose, they mostly re…
Learning a Low-Rank Feature Representation: Achieving Better Trade-Off between Stability and Plasticity in Continual Learning
Zhenrong Liu, Yang Li, Yi Gong +1
In continual learning, networks confront a trade-off between stability and plasticity when trained on a sequence of tasks. To bolster plasticity without sacrificing stability, we p…
A unified framework for STAR-RIS coefficients optimization
Hancheng Zhu, Yuanwei Liu, Yik Chung Wu +1
Simultaneously transmitting and reflecting (STAR) reconfigurable intelligent surface (RIS), which serves users located on both sides of the surface, has recently emerged as a promi…
Communication Resources Constrained Hierarchical Federated Learning for End-to-End Autonomous Driving
Wei-Bin Kou, Shuai Wang, Guangxu Zhu +4
While federated learning (FL) improves the generalization of end-to-end autonomous driving by model aggregation, the conventional single-hop FL (SFL) suffers from slow convergence…
Overcoming Beam Squint in Dual-Wideband mmWave MIMO Channel Estimation: A Bayesian Multi-Band Sparsity Approach
Le Xu, Lei Cheng, Ngai Wong +2
The beam squint effect, which manifests in different steering matrices in different sub-bands, has been widely considered a challenge in millimeter wave (mmWave) multiinput multi-o…