most citedMedical Hallucinations in Foundation Models and Their Impact on Healthcare

30 citations · 50 across the 31 of their papers we have counts for

collaborators

36 papers

cs.AI2026

TimeNet: An Extensible Unified Data Infrastructure for Next-Generation Temporal Foundation Models

Martin Maritsch, Timo Stoffregen, Thomas Kaar +36

Temporal Foundation Models (TFMs) aim to generalize across domains, datasets, and tasks. Yet, their development remains constrained by fragmented, task-specific data formats, annot…

cs.LG2026

Locating Hidden Failures Makes Long-Horizon Agents More Reliable

Salman Rahman, Yubin Kim, Mihir Parmar +15

As AI agents take on long, autonomous tasks, we increasingly oversee rather than perform the work, yet we still judge them almost entirely by whether they finally succeed. An outco…

cs.CL2026

RubricsTree: Scalable and Evolving Open-Ended Evaluation of Personal Health Agents across Health Memory and Medical Skills

Weizhi Zhang, Zechen Li, Hamid Palangi +16

The LLM-empowered personal health agents with user health (sensor) metrics have offered a promising pathway to alleviate global disparities in healthcare access. However, large-sca…

cs.AI2026

WEQA: Wearable hEalth Question Answering with Query-Adaptive Agentic Reasoning

Yuwei Zhang, Tong Xia, Bianca Emmerich +5

Language models are remarkably capable at medical question answering, in some cases surpassing the accuracy of general physicians. However, answering questions about wearable healt…

cs.AI2026

Evaluating the Utility of Personal Health Records in Personalized Health AI

Rory Sayres, Kejia Chen, Ayush Jain +19

Patient-managed Personal Health Records (PHRs) promises to empower patients to better understand their health; but information in the record is complex, potentially hindering insig…

cs.AI2026★ 2 cited

SymptomAI: Toward a Conversational AI Agent for Everyday Symptom Assessment

Joseph Breda, Fadi Yousif, Beszel Hawkins +30

Language models excel at diagnostic assessments on curated medical case-studies and vignettes, performing on par with, or better than, clinical professionals. However, existing stu…

cs.AI2026

TeamBench: Evaluating Agent Coordination under Enforced Role Separation

Yubin Kim, Chanwoo Park, Taehan Kim +9

Agent systems often decompose a task across multiple roles, but these roles are typically specified by prompts rather than enforced by access controls. Without enforcement, a team…

cs.AI2026

Uneven Evolution of Cognition Across Generations of Generative AI Models

Isaac Galatzer-Levy, Daniel McDuff, Xin Liu +1

The pursuit of artificial general intelligence necessitates robust methods for evaluating the cognitive capabilities of models beyond narrow task performance. Here, we introduce a…

cs.AI2026

Towards a General Intelligence and Interface for Wearable Health Data

Girish Narayanswamy, Maxwell A. Xu, A. Ali Heydari +37

While ubiquitous wearable sensors capture a wealth of behavioral and physiological information, effectively transforming these signals into personalized health insights is challeng…

cs.AI2026★ 2 cited

An AI Co-Data-Scientist for Prioritizing Candidate Biomarkers from Wearable Sensor Data

Yubin Kim, Salman Rahman, Samuel Schmidgall +33

Wearable devices generate continuous physiological and behavioral data, but converting these signals into clinically reviewable biomarker hypotheses remains labor-intensive. We int…

cs.AI2026

How Well Do Multimodal Models Reason on ECG Signals?

Maxwell A. Xu, Harish Haresamudram, Catherine W. Liu +11

While multimodal large language models offer a promising solution to the "black box" nature of health AI by generating interpretable reasoning traces, verifying the validity of the…

cs.LG2026

HEARTS: Benchmarking LLM Reasoning on Health Time Series

Sirui Li, Shuhan Xiao, Mihir Joshi +4

The rise of large language models (LLMs) has shifted time series analysis from narrow analytics to general-purpose reasoning. Yet, existing benchmarks cover only a small set of hea…

cs.CV2025

Smartphone monitoring of smiling as a behavioral proxy of well-being in everyday life

Ming-Zher Poh, Shun Liao, Marco Andreetto +10

Subjective well-being is a cornerstone of individual and societal health, yet its scientific measurement has traditionally relied on self-report methods prone to recall bias and hi…

cs.CV2025

FacePhys: State of the Heart Learning

Kegang Wang, Jiankai Tang, Yuntao Wang +5

Vital sign measurement using cameras presents opportunities for comfortable, ubiquitous health monitoring. Remote photoplethysmography (rPPG), a foundational technology, enables ca…

cs.HC2025★ 3 cited

A Principle-based Framework for the Development and Evaluation of Large Language Models for Health and Wellness

Brent Winslow, Jacqueline Shreibati, Javier Perez +18

The incorporation of generative artificial intelligence into personal health applications presents a transformative opportunity for personalized, data-driven health and fitness gui…

cs.AI2025

Towards a Science of Scaling Agent Systems

Yubin Kim, Ken Gu, Chanwoo Park +17

Agents, language model-based systems capable of reasoning, planning, and acting are widely adopted in real-world tasks, yet how their performance changes as these systems scale acr…

cs.CL2025

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…

cs.LG2025

OpenTSLM: Time-Series Language Models for Reasoning over Multivariate Medical Text- and Time-Series Data

Patrick Langer, Thomas Kaar, Max Rosenblattl +19

LLMs have emerged as powerful tools for interpreting multimodal data. In medicine, they hold particular promise for synthesizing large volumes of clinical information into actionab…

cs.AI2025

InvThink: Premortem Reasoning for Safer Language Models

Yubin Kim, Taehan Kim, Eugene Park +4

We present InvThink, a training and prompting framework that requires the model to enumerate, analyze, and constrain potential failures before generating its final response. Unlike…

cs.AI2025★ 5 cited

The Anatomy of a Personal Health Agent

A. Ali Heydari, Ken Gu, Vidya Srinivas +35

Health is a fundamental pillar of human wellness, and the rapid advancements in large language models (LLMs) have driven the development of a new generation of health agents. Howev…

cs.CE2025

Contact Sensors to Remote Cameras: Quantifying Cardiorespiratory Coupling in High-Altitude Exercise Recovery

Jiankai Tang, Meng Kang, Yiru Zhang +5

Cardiorespiratory coupling (CRC) captures the dynamic interaction between the cardiac and respiratory systems--an interaction strengthened by physical exercise and linked to improv…

cs.LG2025

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…

cs.LG2025★ 1 cited

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…

cs.AI2025

Tiered Agentic Oversight: A Hierarchical Multi-Agent System for Healthcare Safety

Yubin Kim, Hyewon Jeong, Chanwoo Park +9

Large language models (LLMs) deployed as agents introduce significant safety risks in clinical settings due to their potential for error and single points of failure. We introduce…