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AOP-Smart: A RAG-Enhanced Large Language Model Framework for Adverse Outcome Pathway Analysis

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学术前沿 5.0 分 — 中等质量:常规学术论文,有适度参考价值
原文: cs.AI updates on arXiv.org

评分 5.0 · 来源:cs.AI updates on arXiv.org · 发布于 2026-04-14

评分依据:中等质量:常规学术论文,有适度参考价值

AOP-Smart: A RAG-Enhanced Large Language Model Framework for Adverse Outcome Pathway Analysis

arXiv:2604.10874v1 Announce Type: cross Abstract: Adverse Outcome Pathways (AOPs) are an important knowledge framework in toxicological research and risk assessment. In recent years, large language models (LLMs) have gradually been applied to AOP-related question answering and mechanistic reasoning tasks. However, due to the existence of the hallucination problem, that is, the model may generate content that is inconsistent with facts or lacks evidence, their reliability is still limited. To…