8 citations · 14 across the 15 of their papers we have counts for
15 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…
REMIND: Rethinking Medical High-Modality Learning under Missingness--A Long-Tailed Distribution Perspective
Chenwei Wu, Zitao Shuai, Liyue Shen
Medical multi-modal learning is critical for integrating information from a large set of diverse modalities. However, when leveraging a high number of modalities in real clinical a…
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…
SeqBench: Benchmarking Sequential Narrative Generation in Text-to-Video Models
Zhengxu Tang, Zizheng Wang, Luning Wang +8
Text-to-video (T2V) generation models have made significant progress in creating visually appealing videos. However, they struggle with generating coherent sequential narratives th…