Thought Graph: Generating Thought Process for Biological Reasoning

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Time matters: Examine temporal effects on biomedical language models

W Liu, Z He, X Huang - arXiv preprint arXiv:2407.17638, 2024 - arxiv.org
Time roots in applying language models for biomedical applications: models are trained on
historical data and will be deployed for new or future data, which may vary from training …
被引用次数：7 相关文章 所有 3 个版本
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BrainMAP: Learning Multiple Activation Pathways in Brain Networks

S Wang, Z Lei, Z Tan, J Ding, X Zhao, Y Dong… - arXiv preprint arXiv …, 2024 - arxiv.org
Functional Magnetic Resonance Image (fMRI) is commonly employed to study human brain
activity, since it offers insight into the relationship between functional fluctuations and human …
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A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Models

Q Zhang, S Chen, Y Bei, Z Yuan, H Zhou… - arXiv preprint arXiv …, 2025 - arxiv.org
Large language models (LLMs) have demonstrated remarkable capabilities in a wide range
of tasks, yet their application to specialized domains remains challenging due to the need for …
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Examining Imbalance Effects on Performance and Demographic Fairness of Clinical Language Models

P Jones, W Liu, I Huang, X Huang - arXiv preprint arXiv:2412.17803, 2024 - arxiv.org
Data imbalance is a fundamental challenge in applying language models to biomedical
applications, particularly in ICD code prediction tasks where label and demographic …
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