output
20192026
most citedA Survey on Digital Twins: Architecture, Enabling Technologies, Security and Privacy, and Future Prospects

307 citations

120 papers

cs.RO2026★ 3 cited

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…

cs.RO2026★ 14 cited

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…

cs.CL2026

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…

cs.CV2026

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…

cs.IR2026★ 1 cited

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…

cs.CV2026

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…