5 papers
Inertia-1: An Open Exploration of Wearable Motion Foundation Models
Zongzhe Xu, Aakarsh Anand, Sarah Jiang +4
Wearable motion sensing provides a continuous and scalable window into human behavior and health, making it a natural fit for foundation models, yet its pretraining and scaling pri…
Signal or Noise? Understanding Generative Models for Real-World Sensor Time Series
Zitao Shuai, Zongzhe Xu, Yuntian Wu +3
Generative models have changed how machine learning represents complex data distributions, especially in language and vision, yet many real-world systems are observed instead as co…
OSF: On Pre-training and Scaling of Sleep Foundation Models
Zitao Shuai, Zongzhe Xu, David Yang +2
Polysomnography (PSG) provides the gold standard for sleep assessment but suffers from substantial heterogeneity across recording devices and cohorts. There have been growing effor…
Shortcut to Nowhere: Demystifying Deep Spurious Regression
Guanrong Xu, Jessica Li, Hao Wang +1
Real-world regression often exhibits shortcuts: attributes that are spuriously correlated with continuous targets in training, yet unreliable under deployment shifts; regressing ta…
GlucoFM: A Dual-Stream Foundation Model for Continuous Glucose Monitoring
Zechen Li, Keerthana Natarajan, Weizhi Zhang +11
Continuous glucose monitoring (CGM) provides a dense view of daily metabolic physiology, yet existing generic time-series and CGM-specific foundation models often encode glucose tr…