activity
20242026
most citedEntry-level guide to the use of large language models for medical research

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

collaborators

5 papers

cs.AI20262 cited

Entry-level guide to the use of large language models for medical research

Qiao Jin, Nicholas Wan, Robert Leaman +20

Frontier large language models (LLMs), such as GPT-5, Claude 4.5, Gemini 3, Llama 4, and DeepSeek-R1, represent a transformative class of AI tools capable of revolutionizing variou…

cs.CL2026

MedHopQA: A Disease-Centered Multi-Hop Reasoning Benchmark and Evaluation Framework for LLM-Based Biomedical Question Answering

Rezarta Islamaj, Robert Leaman, Joey Chan +13

Evaluating large language models (LLMs) in the biomedical domain requires benchmarks that can distinguish reasoning from pattern matching and remain discriminative as model capabil…

cs.CL2025

Enhancing Biomedical Relation Extraction with Directionality

Po-Ting Lai, Chih-Hsuan Wei, Shubo Tian +2

Biological relation networks contain rich information for understanding the biological mechanisms behind the relationship of entities such as genes, proteins, diseases, and chemica…

cs.AI2024

GeneAgent: Self-verification Language Agent for Gene Set Knowledge Discovery using Domain Databases

Zhizheng Wang, Qiao Jin, Chih-Hsuan Wei +6

Gene set knowledge discovery is essential for advancing human functional genomics. Recent studies have shown promising performance by harnessing the power of Large Language Models…

cs.CL2024

EnzChemRED, a rich enzyme chemistry relation extraction dataset

Po-Ting Lai, Elisabeth Coudert, Lucila Aimo +16

Expert curation is essential to capture knowledge of enzyme functions from the scientific literature in FAIR open knowledgebases but cannot keep pace with the rate of new discoveri…