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English(EN) Before the Ticket: Grounding HPC User Support in Documentation and Resolved Tickets with an Agentic LLM Assistant

LLM助手通过查询文档和票据改进HPC用户支持

研究人员开发了一种代理式LLM助手,旨在改善高性能计算(HPC)环境的用户支持。该助手利用实时文档上的检索增强生成(RAG)以及在历史支持票据上使用QLoRA微调的Llama 3-8B模型。该系统旨在通过借鉴现有文档和已解决的票据来回答用户查询,解决了用户在导航这些资源时遇到的困难。在普渡大学先进计算罗森中心(Rosen Center for Advanced Computing)的未公开票据上进行的评估表明,对重写的票据解决方案进行微调,显著提高了与该中心解决方案的一致性,优于基础模型。 AI

影响 这项研究展示了LLM在专业技术支持中的实际应用,有望提高HPC环境的效率和用户体验。

排序理由 该集群包含一篇学术论文,详细介绍了LLM在特定领域的创新应用。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

LLM助手通过查询文档和票据改进HPC用户支持

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该集群包含一篇学术论文,详细介绍了LLM在特定领域的创新应用。[lever_c_demoted from research: ic=1 ai=1.0]
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完整方法见我们的编辑标准。

报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Elham J. Barezi, Primus C Kabuo, Niveditha Nerella ·

    票务之前:通过代理式LLM助手在文档和已解决票务中为HPC用户提供支持

    arXiv:2610.31703v1 Announce Type: cross Abstract: Most questions that reach an HPC help desk have already been answered in the center's user guides or in a ticket someone else filed last semester; users still file new tickets because the guides are hard to navigate and the ticket…