13 citations · 30 across the 9 of their papers we have counts for
10 papers
OpenMHC: Accelerating the Science of Wearable Foundation Models
Narayan Schuetz, Yuze Bai, Lianggang Pan +16
Mobile and wearable devices offer an unprecedented opportunity for continuous, passive health monitoring and active health coaching. However, the largest wearable datasets are not…
SynthWorlds: Controlled Parallel Worlds for Disentangling Reasoning and Knowledge in Language Models
Ken Gu, Advait Bhat, Mike A Merrill +4
Evaluating the reasoning ability of language models (LMs) is complicated by their extensive parametric world knowledge, where benchmark performance often reflects factual recall ra…
SensorLM: Learning the Language of Wearable Sensors
Yuwei Zhang, Kumar Ayush, Siyuan Qiao +17
We present SensorLM, a family of sensor-language foundation models that enable wearable sensor data understanding with natural language. Despite its pervasive nature, aligning and…
LSM-2: Learning from Incomplete Wearable Sensor Data
Maxwell A. Xu, Girish Narayanswamy, Kumar Ayush +22
Foundation models, a cornerstone of recent advancements in machine learning, have predominantly thrived on complete and well-structured data. Wearable sensor data frequently suffer…
A Scalable Framework for Evaluating Health Language Models
Neil Mallinar, A. Ali Heydari, Xin Liu +10
Large language models (LLMs) have emerged as powerful tools for analyzing complex datasets. Recent studies demonstrate their potential to generate useful, personalized responses wh…
Substance over Style: Evaluating Proactive Conversational Coaching Agents
Vidya Srinivas, Xuhai Xu, Xin Liu +5
While NLP research has made strides in conversational tasks, many approaches focus on single-turn responses with well-defined objectives or evaluation criteria. In contrast, coachi…
Scaling Wearable Foundation Models
Girish Narayanswamy, Xin Liu, Kumar Ayush +15
Wearable sensors have become ubiquitous thanks to a variety of health tracking features. The resulting continuous and longitudinal measurements from everyday life generate large vo…
Towards a Personal Health Large Language Model
Justin Cosentino, Anastasiya Belyaeva, Xin Liu +31
In health, most large language model (LLM) research has focused on clinical tasks. However, mobile and wearable devices, which are rarely integrated into such tasks, provide rich,…
What Are the Odds? Language Models Are Capable of Probabilistic Reasoning
Akshay Paruchuri, Jake Garrison, Shun Liao +5
Language models (LM) are capable of remarkably complex linguistic tasks; however, numerical reasoning is an area in which they frequently struggle. An important but rarely evaluate…
Transforming Wearable Data into Personal Health Insights using Large Language Model Agents
Mike A. Merrill, Akshay Paruchuri, Naghmeh Rezaei +17
Deriving personalized insights from popular wearable trackers requires complex numerical reasoning that challenges standard LLMs, necessitating tool-based approaches like code gene…