3 citations · 5 across the 11 of their papers we have counts for
11 papers
Text-Aided Multi-Modal Panoptic Symbol Spotting for CAD Floor Plan Drawings
Yan Gong, Bohao Li, Bowen Du +1
Computer-Aided Design (CAD) floor plan drawings contain both graphical primitives and textual annotations, which provide complementary geometric and semantic cues for intelligent d…
A Clinical Point Cloud Paradigm for In-Hospital Mortality Prediction from Multi-Level Incomplete Multimodal EHRs
Bohao Li, Tao Zou, Junchen Ye +2
Deep learning-based modeling of multimodal Electronic Health Records (EHRs) has become an important approach for clinical diagnosis and risk prediction. However, due to diverse cli…
Incident-Guided Spatiotemporal Traffic Forecasting
Lixiang Fan, Bohao Li, Tao Zou +2
Recent years have witnessed the rapid development of deep-learning-based, graph-neural-network-based forecasting methods for modern intelligent transportation systems. However, mos…
Global-Lens Transformers: Adaptive Token Mixing for Dynamic Link Prediction
Tao Zou, Chengfeng Wu, Tianxi Liao +2
Dynamic graph learning plays a pivotal role in modeling evolving relationships over time, especially for temporal link prediction tasks in domains such as traffic systems, social n…
Text-Enhanced Panoptic Symbol Spotting in CAD Drawings
Xianlin Liu, Yan Gong, Bohao Li +4
With the widespread adoption of Computer-Aided Design(CAD) drawings in engineering, architecture, and industrial design, the ability to accurately interpret and analyze these drawi…
Dynamic Graph Representation Learning for Passenger Behavior Prediction
Mingxuan Xie, Tao Zou, Junchen Ye +2
Passenger behavior prediction aims to track passenger travel patterns through historical boarding and alighting data, enabling the analysis of urban station passenger flow and time…
Co-Neighbor Encoding Schema: A Light-cost Structure Encoding Method for Dynamic Link Prediction
Ke Cheng, Linzhi Peng, Junchen Ye +2
Structure encoding has proven to be the key feature to distinguishing links in a graph. However, Structure encoding in the temporal graph keeps changing as the graph evolves, repea…
DyGKT: Dynamic Graph Learning for Knowledge Tracing
Ke Cheng, Linzhi Peng, Pengyang Wang +3
Knowledge Tracing aims to assess student learning states by predicting their performance in answering questions. Different from the existing research which utilizes fixed-length le…
Repeat-Aware Neighbor Sampling for Dynamic Graph Learning
Tao Zou, Yuhao Mao, Junchen Ye +1
Dynamic graph learning equips the edges with time attributes and allows multiple links between two nodes, which is a crucial technology for understanding evolving data scenarios li…
Adaptive Taxonomy Learning and Historical Patterns Modelling for Patent Classification
Tao Zou, Le Yu, Junchen Ye +3
Patent classification aims to assign multiple International Patent Classification (IPC) codes to a given patent. Recent methods for automatically classifying patents mainly focus o…
Analysis for full face mechanical behaviors through spatial deduction model with real-time monitoring data
Xuyan Tan, Yuhang Wang, Bowen Du +4
Mechanical analysis for the full face of tunnel structure is crucial to maintain stability, which is a challenge in classical analytical solutions and data analysis. Along this lin…