most citedLMOD+: A Comprehensive Multimodal Dataset and Benchmark for Developing and Evaluating Multimodal Large Language Models in Ophthalmology

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cs.CL2026

Toward Federated Large Language Models in Medicine: A Parameter-Efficient Framework for Privacy-Preserving, Multi-Institutional Adaptation

Anran Li, Yuanyuan Chen, Wenjun Long +16

Large language models (LLMs) are increasingly adapted for medical applications, but most are trained using data from a single institution because privacy and governance constraints…

cs.CL2026★ 1 cited

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…

cs.CL2025

Can OpenAI o1 Reason Well in Ophthalmology? A 6,990-Question Head-to-Head Evaluation Study

Sahana Srinivasan, Xuguang Ai, Minjie Zou +14

Question: What is the performance and reasoning ability of OpenAI o1 compared to other large language models in addressing ophthalmology-specific questions? Findings: This study ev…