Search Results for author:
Found 2 papers, 1 papers with code
Raw Text is All you Need: Knowledge-intensive Multi-turn Instruction Tuning for Large Language Model
In this paper, we present a novel framework named R2S that leverages the CoD-Chain of Dialogue logic to guide large language models (LLMs) in generating knowledge-intensive multi-turn dialogues for instruction tuning.
REALM: RAG-Driven Enhancement of Multimodal Electronic Health Records Analysis via Large Language Models
Leveraging clinical notes and multivariate time-series EHR, existing models often lack the medical context relevent to clinical tasks, prompting the incorporation of external knowledge, particularly from the knowledge graph (KG).
Cannot find the paper you are looking for? You can
Submit a new open access paper.
