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Found 2 papers, 1 papers with code
Small Language Models Learn Enhanced Reasoning Skills from Medical Textbooks
While recent advancements in commercial large language models (LM) have shown promising results in medical tasks, their closed-source nature poses significant privacy and security concerns, hindering their widespread use in the medical field.
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Improving Medical Reasoning through Retrieval and Self-Reflection with Retrieval-Augmented Large Language Models
To address challenges that still cannot be handled with the encoded knowledge of LLMs, various retrieval-augmented generation (RAG) methods have been developed by searching documents from the knowledge corpus and appending them unconditionally or selectively to the input of LLMs for generation.
