329 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of MacauMO108 papers
- Shanghai Jiao Tong UniversityCN15 papers
- Tsinghua UniversityCN13 papers
- Hangzhou City University12 papers
- Chinese Academy of SciencesCN11 papers
- University of Chinese Academy of SciencesCN10 papers
- University of Technology SydneyAU9 papers
- Zhejiang UniversityCN9 papers
- Nanyang Technological UniversitySG7 papers
- Jinan UniversityCN6 papers
- Shenzhen Institutes of Advanced TechnologyCN6 papers
- Southeast UniversityCN6 papers
147 papers
Free-Init: Scan-Free, Motion-Free, and Correspondence-Free Initialization for Doppler LiDAR-Inertial Systems
Mingle Zhao, Jiahao Wang, Tianxiao Gao +2
Robust initialization is crucial for online systems. In the letter, a high-frequency and resilient initialization framework is designed for LiDAR-inertial systems, leveraging both…
FMCW-LIO: A Doppler LiDAR-Inertial Odometry
Mingle Zhao, Jiahao Wang, Tianxiao Gao +2
Conventional LiDAR-inertial odometry (LIO) or simultaneous localization and mapping (SLAM) methods heavily rely on geometric features of environments, as LiDARs primarily provide r…
Contamination Inflates Scores but Rarely Reorders Large Language Model Leaderboards
Xingyao Xiao, Yihong Cheng
Benchmark contamination, the leakage of test items into training data, is widely described as a threat to the reliability of large language model (LLM) leaderboards. We argue that…
RSGPNet: Geometric Prompting for Remote Sensing Open-Vocabulary Semantic Segmentation
Shanwen Wang, Xin Sun, Sirui Wang +1
Open-vocabulary semantic segmentation (OVSS) enables text-guided segmentation of unseen objects, breaking fixed-class limitations to achieve open-world understanding. However, exis…
Metric-agnostic Learning-to-Rank via Boosting and Rank Approximation
Camilo Gomez, Pengyang Wang, Yanjie Fu
Learning-to-Rank (LTR) is a supervised machine learning approach that constructs models specifically designed to order a set of items or documents based on their relevance or impor…
Multimodal Industrial Anomaly Detection via Geometric Prior
Min Li, Jinghui He, Gang Li +3
The purpose of multimodal industrial anomaly detection is to detect complex geometric shape defects such as subtle surface deformations and irregular contours that are difficult to…
Mock Observations of Multiple Stellar Populations in Tidal Streams of Palomar 5 for the Chinese Space Station Survey Telescope
Xia Li, Long Wang, Chengyuan Li +3
Observations show that multiple stellar populations (MPs) are ubiquitous in globular clusters. The Hubble Space Telescope (HST) has been a pivotal tool for previous photometric stu…
Tidal Synchronization of Binaries in Pleiades
Li Wang, Chenyu He, Chengyuan Li +1
Tidal interactions in close binaries play a key role in the long-term rotational and orbital evolution. The distributions of circularization across open clusters (OCs) place strong…
EvasionBench: A Large-Scale Benchmark for Detecting Managerial Evasion in Earnings Call Q&A
Shijian Ma, Yan Lin, Yi Yang
We present EvasionBench, a comprehensive benchmark for detecting evasive responses in corporate earnings call question-and-answer sessions. Drawing from 22.7 million Q&A pairs extr…
Vision-Language Model Purified Semi-Supervised Semantic Segmentation for Remote Sensing Images
Shanwen Wang, Xin Sun, Danfeng Hong +1
The semi-supervised semantic segmentation (S4) can learn rich visual knowledge from low-cost unlabeled images. However, traditional S4 architectures all face the challenge of low-q…
TopKGAT: A Top-K Objective-Driven Architecture for Recommendation
Sirui Chen, Jiawei Chen, Canghong Jin +4
Recommendation systems (RS) aim to retrieve the top-K items most relevant to users, with metrics such as Precision@K and Recall@K commonly used to assess effectiveness. The archite…
Toward Resource-Efficient Collaboration of Large AI Models in Mobile Edge Networks
Peichun Li, Liping Qian, Dusit Niyato +2
The collaboration of large artificial intelligence (AI) models in mobile edge networks has emerged as a promising paradigm to meet the growing demand for intelligent services at th…
BEAR: Towards Beam-Search-Aware Optimization for Recommendation with Large Language Models
Weiqin Yang, Bohao Wang, Zhenxiang Xu +5
Recent years have seen a rapid surge in research leveraging Large Language Models (LLMs) for recommendation. These methods typically employ supervised fine-tuning (SFT) to adapt LL…
Deep Learning-Based Channel Extrapolation for Dual-Band Massive MIMO Systems
Qikai Xiao, Kehui Li, Binggui Zhou +1
Future wireless communication systems will increasingly rely on the integration of millimeter wave (mmWave) and sub-6 GHz bands to meet heterogeneous demands on high-speed data tra…
Joint Sparsity and Beamforming Design for RDARS-Aided Systems
Chengwang Ji, Haiquan Lu, Qiaoyan Peng +2
Reconfigurable distributed antennas and reflecting surface (RDARS) has emerged as a promising architecture for communication and sensing performance enhancement. In particular, the…
TransBridge: Boost 3D Object Detection by Scene-Level Completion with Transformer Decoder
Qinghao Meng, Chenming Wu, Liangjun Zhang +1
3D object detection is essential in autonomous driving, providing vital information about moving objects and obstacles. Detecting objects in distant regions with only a few LiDAR p…
DGFusion: Dual-guided Fusion for Robust Multi-Modal 3D Object Detection
Feiyang Jia, Caiyan Jia, Ailin Liu +6
As a critical task in autonomous driving perception systems, 3D object detection is used to identify and track key objects, such as vehicles and pedestrians. However, detecting dis…
Joint Active and Passive Beamforming with Sensing-Assisted Discrete Phase Shifts for Dual-RIS ISAC Systems
Qing Xue, Yun Lan, Jiajia Guo +2
Targeting the requirements of 6G, this paper investigates a semi-passive dual-reconfigurable intelligent surface (RIS)-assisted integrated sensing and communication (ISAC) system,…
Ensemble-Based Data Assimilation for Material Model Characterization in High-Velocity Impact
Rong Jin, Guangyao Wang, Xingsheng Sun
High-fidelity simulations are essential for predicting material behavior under high-velocity impact (HVI), but their accuracy depends on material models and parameters that are oft…
Robotic Manipulation Framework Based on Semantic Keypoints for Packing Shoes of Different Sizes, Shapes, and Softness
Yi Dong, Yangjun Liu, Jinjun Duan +2
With the rapid development of the warehousing and logistics industries, the packing of goods has gradually attracted the attention of academia and industry. The packing of footwear…
Refining Contrastive Learning and Homography Relations for Multi-Modal Recommendation
Shouxing Ma, Yawen Zeng, Shiqing Wu +1
Multi-modal recommender system focuses on utilizing rich modal information ( i.e., images and textual descriptions) of items to improve recommendation performance. The current meth…
MyGO: Make your Goals Obvious, Avoiding Semantic Confusion in Prostate Cancer Lesion Region Segmentation
Zhengcheng Lin, Zuobin Ying, Zhenyu Li +3
Early diagnosis and accurate identification of lesion location and progression in prostate cancer (PCa) are critical for assisting clinicians in formulating effective treatment str…
BrownoutServe: SLO-Aware Inference Serving under Bursty Workloads for MoE-based LLMs
Jianmin Hu, Minxian Xu, Kejiang Ye +1
In recent years, the Mixture-of-Experts (MoE) architecture has been widely applied to large language models (LLMs), providing a promising solution that activates only a subset of t…
SAIGFormer: A Spatially-Adaptive Illumination-Guided Network for Low-Light Image Enhancement
Hanting Li, Fei Zhou, Xin Sun +3
Recent Transformer-based low-light enhancement methods have made promising progress in recovering global illumination. However, they still struggle with non-uniform lighting scenar…