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20232026
most citedBidirectional Generative Pre-training for Improving Healthcare Time-series Representation Learning

2 citations · 4 across the 9 of their papers we have counts for

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Showing 2026Show all

6 papers · 1 filter

cs.CL2026

SMI: Ontology-Grounded Semantic IDs for Hierarchy-Aware Medical Concept Representation

Ziyang Song, Lia Shen, Yixuan Li +6

Biomedical language models (LMs) provide strong representations for clinical tasks, but they often fail to capture the hierarchical structure among medical concepts. This limitatio…

cs.LG2026

FedEHR-Agents: Federated Agentic Optimization for Automated EHR Modeling

Jun Bai, Ruilin Wang, Yue Li

Recent advances in large language models are enabling autonomous clinical agents to perform increasingly complex electronic health record (EHR) modeling workflows. However, agents…

cs.AI2026

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data

Ruilin Wang, Bo-Hong Wang, Elizabeth Kourbatski +6

Clinical machine learning (ML) has the potential to support high-stakes medical decision-making, but reliable deployment is often constrained by scarce, heterogeneous, and temporal…

cs.AI2026

ChatHealthAI: Aligning Electronic Health Record Representations with Large Language Models for Grounded Clinical Reasoning

Bo-Hong Wang, Baicheng Peng, Ruilin Wang +3

Large language models (LLMs) exhibit strong natural-language reasoning abilities for clinical decision support, but struggle to effectively model structured longitudinal electronic…

cs.LG2026

FedEHR-Gen: Federated Synthetic Time-Series EHR Generation via Latent Space Alignment and Distribution-Aware Aggregation

Jun Bai, Ziyang Song, Yue Li

Synthetic Electronic Health Record (EHR) generation provides a promising avenue for data augmentation and cross-hospital modeling in privacy-constrained healthcare settings. Howeve…

cs.AI2026

Sketch Then Paint: Hierarchical Reinforcement Learning for Diffusion Multi-Modal Large Language Models

Siqi Luo, Jianghan Shen, Yi Xin +9

Diffusion Multi-Modal Large Language Models (dMLLMs) are powerful for image generation, but optimizing them through reinforcement learning (RL) remains a major challenge. One prima…