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A unified framework and benchmark for generalizable biomedical knowledge extraction and applications with large language models
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DOI：10.1016/j.xcrm.2026.102975.png)
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Abstract
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• A unified framework enables generalizable biomedical knowledge extraction • Ontology-guided alignment harmonizes 40 public biomedical datasets • Task-conditioned schema instruction tuning improves task generalization • The framework supports retrieval, diagnosis, and knowledge graph expansion
Keywords:
biomedical information extraction
large language models
ontology-guided alignment
instruction tuning
biomedical benchmark
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