5 citations · 5 across the 7 of their papers we have counts for
7 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…
SleepLM: Natural-Language Intelligence for Human Sleep
Zongzhe Xu, Zitao Shuai, Eideen Mozaffari +3
We present SleepLM, a family of sleep-language foundation models that enable human sleep alignment, interpretation, and interaction with natural language. Despite the critical role…
V2X-DG: Domain Generalization for Vehicle-to-Everything Cooperative Perception
Baolu Li, Zongzhe Xu, Jinlong Li +4
LiDAR-based Vehicle-to-Everything (V2X) cooperative perception has demonstrated its impact on the safety and effectiveness of autonomous driving. Since current cooperative percepti…
Specialized Foundation Models Struggle to Beat Supervised Baselines
Zongzhe Xu, Ritvik Gupta, Wenduo Cheng +4
Following its success for vision and text, the "foundation model" (FM) paradigm -- pretraining large models on massive data, then fine-tuning on target tasks -- has rapidly expande…