21 papers
Patient-Conditioned Dual Hypergraph Reasoning for Auditable Traditional Chinese Medicine Prescription Support
Weizhi Nie, Shaojin Bai, Weijie Wang +1
Traditional Chinese medicine (TCM) prescription support requires patient-specific reasoning from clinical narratives to syndromes, treatment principles, herbs, and doses. Direct la…
Liquid Latent State Dynamics for Interpretable Turbofan Degradation Modeling
Weizhi Nie, Weijie Wang, Yuting Su
Multivariate time-series models for prognostics are often evaluated by point prediction accuracy, yet their internal states rarely expose a coherent degradation process. We study l…
Prototype Latent World Model Replay for Class-Incremental Learning
Weizhi Nie, Hui Wang, Weijie Wang +1
Class-incremental learning requires a model to learn new classes while preserving decision regions for old ones. This is difficult when raw old samples are no longer available. We…
Hypergraph Normal World Models for Logical Visual Anomaly Detection
Weizhi Nie, Zibo Xu, Weijie Wang +1
Visual anomaly detection is often deployed with only normal training images. Most one-class detectors map test patches or features to a normal reference distribution. This works we…
Learning a Normal World Model for Few-Shot Boundary-Calibrated Abnormality Detection
Weizhi Nie, Weichao Liu, Weijie Wang +1
Abnormality detection in complex systems faces two practical barriers: abnormal labels are scarce, and binary labels do not quantify how far an event has departed from normal behav…
Phys-JEPA: Physics-Informed Latent World Models for Multivariate Time-Series Forecasting
Weizhi Nie, Weichao Liu, Honglin Guo +1
Multivariate forecasting in physical systems requires models that predict coupled temporal variables while preserving meaningful state evolution. Deep forecasters can fit temporal…