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Integrating Physician Diagnostic Logic into Large Language Models: Preference Learning from Process Feedback
The use of large language models in medical dialogue generation has garnered significant attention, with a focus on improving response quality and fluency.
Enhancing the Spatial Awareness Capability of Multi-Modal Large Language Model
The Multi-Modal Large Language Model (MLLM) refers to an extension of the Large Language Model (LLM) equipped with the capability to receive and infer multi-modal data.
PlugMed: Improving Specificity in Patient-Centered Medical Dialogue Generation using In-Context Learning
PlugMed is equipped with two modules, the prompt generation (PG) module and the response ranking (RR) module, to enhances LLMs' dialogue strategies for improving the specificity of the dialogue.
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