activity
20192026
most citedMatching Patients to Clinical Trials with Large Language Models

244 citations · 508 across the 40 of their papers we have counts for

collaborators
Showing 2025Show all

8 papers · 1 filter

cs.IR2025

DeepEvidence: Empowering Biomedical Discovery with Deep Knowledge Graph Research

Zifeng Wang, Zheng Chen, Ziwei Yang +5

Biomedical knowledge graphs (KGs) encode vast, heterogeneous information spanning literature, genes, pathways, drugs, diseases, and clinical trials, but leveraging them collectivel…

cs.AI2025★ 1 cited

Adaptation of Agentic AI: A Survey of Post-Training, Memory, and Skills

Pengcheng Jiang, Jiacheng Lin, Zhiyi Shi +31

Large language model (LLM) agents are moving beyond prompting alone. ChatGPT marked the rise of general-purpose LLM assistants, DeepSeek showed that on-policy reinforcement learnin…

cs.AI2025★ 1 cited

BioDSA-1K: Benchmarking Data Science Agents for Biomedical Research

Zifeng Wang, Benjamin Danek, Jimeng Sun

Validating scientific hypotheses is a central challenge in biomedical research, and remains difficult for artificial intelligence (AI) agents due to the complexity of real-world da…

cs.AI2025

Developing Large Language Models for Clinical Research Using One Million Clinical Trials

Zifeng Wang, Jiacheng Lin, Qiao Jin +5

Developing artificial intelligence (AI) for clinical research requires a comprehensive data foundation that supports model training and rigorous evaluation. Here, we introduce Tria…

cs.AI2025

s3: You Don't Need That Much Data to Train a Search Agent via RL

Pengcheng Jiang, Xueqiang Xu, Jiacheng Lin +4

Retrieval-augmented generation (RAG) systems empower large language models (LLMs) to access external knowledge during inference. Recent advances have enabled LLMs to act as search…

cs.IR2025★ 1 cited

DeepRetrieval: Hacking Real Search Engines and Retrievers with Large Language Models via Reinforcement Learning

Pengcheng Jiang, Jiacheng Lin, Lang Cao +5

Information retrieval systems are crucial for enabling effective access to large document collections. Recent approaches have leveraged Large Language Models (LLMs) to enhance retr…

cs.CL2025

InformGen: An AI Copilot for Accurate and Compliant Clinical Research Consent Document Generation

Zifeng Wang, Junyi Gao, Benjamin Danek +5

Leveraging large language models (LLMs) to generate high-stakes documents, such as informed consent forms (ICFs), remains a significant challenge due to the extreme need for regula…

cs.CL2025

A foundation model for human-AI collaboration in medical literature mining

Zifeng Wang, Lang Cao, Qiao Jin +20

Systematic literature review is essential for evidence-based medicine, requiring comprehensive analysis of clinical trial publications. However, the application of artificial intel…