8 papers
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…
Supervising the search process produces reliable and generalizable information-seeking agents
Guangzhi Xiong, Qiao Jin, Xiao Wang +9
Large language models (LLMs) are transforming web search by shifting from document ranking to synthesizing answers, and are increasingly deployed as autonomous agentic search syste…
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…
CT-Bench: A Benchmark for Multimodal Lesion Understanding in Computed Tomography
Qingqing Zhu, Qiao Jin, Tejas S. Mathai +10
Artificial intelligence (AI) can automatically delineate lesions on computed tomography (CT) and generate radiology report content, yet progress is limited by the scarcity of publi…
Memorization in Large Language Models in Medicine: Prevalence, Characteristics, and Implications
Anran Li, Lingfei Qian, Mengmeng Du +18
Large Language Models (LLMs) have demonstrated significant potential in medicine, with many studies adapting them through continued pre-training or fine-tuning on medical data to e…
Gene-R1: Reasoning with Data-Augmented Lightweight LLMs for Gene Set Analysis
Zhizheng Wang, Yifan Yang, Qiao Jin +1
The gene set analysis (GSA) is a foundational approach for uncovering the molecular functions associated with a group of genes. Recently, LLM-powered methods have emerged to annota…