Lei Wang

AI-Driven Robotic PCI: A Perception-to-Action Framework for Coronary Guidewire Control

Zijing Liu, Huanming Xu, Zhendong Liu, Jun Ma, J I N Liu, Pengfei Bi, et al.

Robotic percutaneous coronary intervention (PCI) remains predominantly teleoperated, while the most demanding part of the procedure, guidewire navigation through a moving coronary tree under fluoroscopy, still depends on the continuous human interpretation of vessel anatomy, card…Read more

O-VAD: Industrial Video Anomaly Detection through Object-Centric Tracking and Reasoning

Mei Yuan, Qi Long, Qifeng Wu, Zhenyang Li, Yizhou Zhao, Lei Wang, et al.

Industrial Video Anomaly Detection (IVAD) aims to identify anomalous objects and events in an industrial process, which is crucial for modern manufacturing and quality control systems. Existing VLM-based anomaly reasoning methods are capable of detecting open-ended anomalies in g…Read more

Evidence-Grounded AI for Musculoskeletal Care

Wenjie Li, Yujie Zhang, Fanrui Zhang, Haoran Sun, Renhao Yang, Junjun He, et al.

Musculoskeletal diseases are among the leading causes of disability and drive the greatest global need for rehabilitation. Because recovery, remodelling and degeneration of bones, joints and related tissues unfold over months to years, care requires longitudinal management rather…Read more

DM-KG: A Novel Method for Boosting Spatial Cognition of Vision-Language Models in Street View Imagery

Xinyue Xu, Zheng Zhang, Kunyang Ma, Ge Zhu, Lianshuai Cao, Lei Wang, et al.

As vision-language models (VLMs) are increasingly deployed in geospatial question answering and visual scene understanding, improving their spatial cognition capability on street view imagery for complex logical reasoning has emerged as a key research priority. However, existing…Read more

Seeing What Matters: Lesion-Aware High-Resolution Patch Discovery and Fusion for Chest X-ray Report Generation

Yingshu Li, Yunyi Liu, Zhenghao Chen, Tong Chen, Zailong Chen, Lingqiao Liu, et al.

Despite rapid advances in chest X-ray (CXR) foundation models, most radiology report generation (RRG) systems still rely on heavily downsampled inputs (e.g., 256x256) due to the fixed visual token budgets of pretrained vision encoders, suppressing subtle yet clinically important…Read more

GeoSearcher: Anchor-Guided Progressive Reasoning for Remote Sensing Visual Grounding with Process Supervision

Dianyu Wang, Peirong Zhang, Xuyang Li, Xiaoxuan Liu, Lei Wang

Recent multimodal large language models (MLLMs) have shown strong cross-modal understanding and coordinate generation abilities in visual grounding. However, transferring these abilities to remote sensing visual grounding (RSVG) remains challenging. High-resolution remote sensing…Read more

FlowAWR: Online Adaptive Flow Reinforcement via Advantage-Weighted Rectification

Zheming Fu, Ruizhe He, Wei Shang, Xiaoxiao Ma, Lei Wang, Chang Liu, et al.

Aligning generative flow models on continuous spaces via online reinforcement learning is constrained by intractable trajectory likelihoods. Existing density-approximated policy gradient methods rely on stochastic SDE samplers to construct tractable transition kernels, which intr…Read more

AgentX: Towards Agent-Driven Self-Iteration of Industrial Recommender Systems

Changxin Lao, Fei Pan, Guozhuang Ma, Han Li, Huihuang Lin, Jijun Shi, et al.

Recommendation algorithm iteration is moving from an artisanal, engineer-bound process toward an industrialized research loop, but this transition remains blocked by a structural execution bottleneck: the idea-to-launch cycle still depends on human engineers to generate hypothese…Read more

A Comparative Study of Machine Learning and Deep Learning Models for Long-Term Snow Depth Inversion

Tingyu Lu, Rong Fan, Lijuan Zhang, Qiang Wang, Yufeng Zhao, Lei Wang, et al.

Snow depth is a critical parameter for characterizing snow dynamics and water resources, and its accurate inversion is essential for hydrological processes, climate studies, and disaster prevention in cold regions. Based on long-term daily ground meteorological observation data f…Read more

Autonomous Navigation Control and Collision Avoidance Decision-Making of an Under-Actuated ASV Based on Deep Reinforcement Learning

Yiting Wang, Zhiyao Li, Lei Wang, Xuefeng Wang

For efficient and safe navigation for an autonomous surface vehicle (ASV), this paper proposes an autonomous navigation behavior framework that integrates deep reinforcement learning (DRL) to achieve autonomous decision-making and low-level control actions in path following and c…Read more

Quantifying Tail Risk Spillovers in Chinese Petroleum Supply Chain Enterprises: A Neural-Network-Inspired Multi-Layer Machine Learning Framework

Xin Zheng, Lei Wang, Tingqiang Chen, Tao Xu

This study constructs a neural-network-inspired multi-layer machine learning model (RQLNet) to measure and analyze the effects of tail risk spillover and its associated sensitivities to macroeconomic factors among petroleum supply chain enterprises. On this basis, the study const…Read more

A Weakly Supervised Deep Learning Model and Human–Machine Fusion for Accurate Grading of Renal Cell Carcinoma from Histopathology Slides

Qingyuan Zheng, Rui Yang, Huazhen Xu, Junjie Fan, Panpan Jiao, Xinmiao Ni, et al.

(1) Background: The Fuhrman grading (FG) system is widely used in the management of clear cell renal cell carcinoma (ccRCC). However, it is affected by observer variability and irreproducibility in clinical practice. We aimed to use a deep learning multi-class model called SSL-CL…Read more

Clustering beyond the binary: Stable machine-learning phenotypes of metabolic syndrome

Jennifer Wilkie, Xu-Feng Huang, Lei Wang, Khin Than Win