用轻量开源对话系统帮大学快速回复招生咨询。
Marcel: A Lightweight and Open-Source Conversational Agent for University Student Support
- 用检索增强生成技术结合校内资料回答问题。
- 自研问答检索器提升准确率，管理员可干预检索结果。
- 适合资源有限的高校部署，已实测可用。
我们提出Marcel，一个轻量级且开源的对话代理，旨在为潜在学生提供招生相关咨询支持。该系统致力于快速生成个性化回复，减轻高校工作人员负担。采用检索增强生成技术，将回答基于校内资源，确保信息可验证且上下文相关。我们引入一种频发问题检索器（FAQ retriever），可将用户问题映射至知识库条目，使管理员能干预检索过程，并优于标准稠密或混合检索策略。系统设计注重在资源受限的学术环境中易于部署。本文详述了系统架构，对各组件进行了技术评估，并报告了真实场景部署中的观察结果。
原文摘要 · Abstract (English)
We present Marcel, a lightweight and open-source conversational agent designed to support prospective students with admission-related inquiries. The system aims to provide fast and personalized responses, while reducing workload of university staff. We employ retrieval-augmented generation to ground answers in university resources and to provide users with verifiable, contextually relevant information. We introduce a Frequently Asked Question (FAQ) retriever that maps user questions to knowledge-base entries, which allows administrators to steer retrieval, and improves over standard dense/hybrid retrieval strategies. The system is engineered for easy deployment in resource-constrained academic settings. We detail the system architecture, provide a technical evaluation of its components, and report insights from a real-world deployment.
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