mlsanityData to 14 Oct 2026

Marcel: A Lightweight and Open-Source Conversational Agent for University Student Support

arXiv 2507.13937 ↗First posted 18 Jul 2025cs.CLcited by 1

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Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 11 of its 29 references that are in the map. First posted on arXiv 18 Jul 2025.

Builds on

11 of 29 references.

References · 11

  1. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  2. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  3. 2023Efficient Memory Management for Large Language Model Serving with PagedAttentioncited by 5,944
  4. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,512
  5. 2024Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preferencecited by 1,184
  6. 2024LLM Evaluators Recognize and Favor Their Own Generationscited by 686
  7. 2022Precise Zero-Shot Dense Retrieval without Relevance Labelscited by 517
  8. 2021Decontextualization: Making Sentences Stand-Alonecited by 102
  9. 2017Rasa: Open Source Language Understanding and Dialogue Managementcited by 67
  10. 2024Walert: Putting Conversational Search Knowledge into Action by Building and Evaluating a Large Language Model-Powered Chatbotcited by 3
  11. 2025URAG: Implementing a Unified Hybrid RAG for Precise Answers in University Admission Chatbots -- A Case Study at HCMUTcited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026hoBIT: A Profile-Aware Retrieval-Augmented Chatbot for University Academic Advisingcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025An Empirical Study of Multi-Agent RAG for Real-World University Admissions Counseling
  2. 2025ALOHA: Empowering Multilingual Agent for University Orientation with Hierarchical Retrieval
  3. 2024From Questions to Insightful Answers: Building an Informed Chatbot for University Resources
  4. 2026Large Language Models for Assisting American College Applications
  5. 2026BLADE: Better Language Answers through Dialogue and Explanations
  6. 2024Toward Conversational Agents with Context and Time Sensitive Long-term Memory
  7. 2026Carolina Guide: A Multi-Agent RAG System with Institutional Guardrails for Academic Policy Assistance
  8. 2024AGENT-CQ: Automatic Generation and Evaluation of Clarifying Questions for Conversational Search with LLMs