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sub:assertion {
  <https://doi.org/10.48550/arXiv.2405.19266> dct:title "PediatricsGPT: Large Language Models as Chinese Medical Assistants for Pediatric Applications";
    <http://purl.org/spar/cito/describes> <https://neverblink.eu/ontologies/llm-kg/methods#PediatricsGPTTrainingPipeline>;
    <http://purl.org/spar/cito/discusses> <https://neverblink.eu/ontologies/llm-kg/methods#RLHF>,
      <https://neverblink.eu/ontologies/llm-kg/methods#VanillaDPO>;
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  <https://neverblink.eu/ontologies/llm-kg/methods#PediatricsGPTTrainingPipeline> dct:subject
      <https://neverblink.eu/ontologies/llm-kg/categories#KGEnhancedLLMPretraining>;
    a <http://purl.org/spar/fabio/Workflow>;
    rdfs:comment "The PediatricsGPT method proposes a systematic training pipeline for an LLM assistant. A key component of this pipeline, the \"hybrid instruction pre-training mechanism\" within the Continuous Pre-Training phase, explicitly integrates knowledge graph resources into the PedCorpus-CPT dataset. This integration directly enhances the LLM's foundational medical knowledge and domain adaptation during pre-training, ultimately improving its performance in pediatric applications.";
    rdfs:label "PediatricsGPT (Training Pipeline)";
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  <https://neverblink.eu/ontologies/llm-kg/methods#VanillaDPO> a <http://purl.org/spar/fabio/Workflow>;
    rdfs:label "Vanilla DPO" .
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