Decoder-based LLMs tuned with LoRA match or beat encoder-only models on clinical concept and relation extraction, and multi-task instruction tuning sharply improves zero- and few-shot transfer, approaching full fine-tuning with 20% of the data.
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A Study of Large Language Models for Patient Information Extraction: Model Architecture, Fine-Tuning Strategy, and Multi-task Instruction Tuning
Decoder-based LLMs tuned with LoRA match or beat encoder-only models on clinical concept and relation extraction, and multi-task instruction tuning sharply improves zero- and few-shot transfer, approaching full fine-tuning with 20% of the data.