activity
20242026
most citedAn AI Co-Data-Scientist for Prioritizing Candidate Biomarkers from Wearable Sensor Data

2 citations · 2 across the 4 of their papers we have counts for

collaborators

10 papers

cs.AI2026

MatrAIx: Simulating the World with 8.3 Billion Persona Agents

Xiaomin Li, Yuexing Hao, Jianheng Hou +90

Human evaluation of AI systems and digital products is costly, slow, and difficult to scale. Offline evaluations are more scalable but often abstract away human diversity and inter…

cs.AI20262 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.CV2026

MedCTA: A Benchmark for Clinical Tool Agents

Tajamul Ashraf, Hyewon Jeong, Fida Mohammad Thoker +1

To make clinically grounded decisions, medical AI agents are expected to go beyond simple recognition and be capable of tool retrieval, evidence acquisition, and integration. Exist…

cond-mat.mtrl-sci2026

From Knowledge to Action: Outcomes of the 2025 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry

Aritra Roy, Kevin Shen, Andrew MacBride +350

Large language models (LLMs) are rapidly changing how researchers in materials science and chemistry discover, organize, and act on scientific knowledge. This paper analyzes a broa…

cs.CL2025

Medical Hallucinations in Foundation Models and Their Impact on Healthcare

Yubin Kim, Hyewon Jeong, Shan Chen +24

Hallucinations in foundation models arise from autoregressive training objectives that prioritize token-likelihood optimization over epistemic accuracy, fostering overconfidence an…

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…