@inproceedings{trienes-etal-2025-marcel,
title = "Marcel: A Lightweight and Open-Source Conversational Agent for University Student Support",
author = {Trienes, Jan and
Derzhanskaia, Anastasiia and
Schwarzkopf, Roland and
M{\"u}hling, Markus and
Schl{\"o}tterer, J{\"o}rg and
Seifert, Christin},
editor = {Habernal, Ivan and
Schulam, Peter and
Tiedemann, J{\"o}rg},
booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
month = nov,
year = "2025",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.emnlp-demos.13/",
pages = "181--195",
ISBN = "979-8-89176-334-0",
abstract = "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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%0 Conference Proceedings
%T Marcel: A Lightweight and Open-Source Conversational Agent for University Student Support
%A Trienes, Jan
%A Derzhanskaia, Anastasiia
%A Schwarzkopf, Roland
%A Mühling, Markus
%A Schlötterer, Jörg
%A Seifert, Christin
%Y Habernal, Ivan
%Y Schulam, Peter
%Y Tiedemann, Jörg
%S Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
%D 2025
%8 November
%I Association for Computational Linguistics
%C Suzhou, China
%@ 979-8-89176-334-0
%F trienes-etal-2025-marcel
%X 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.
%U https://aclanthology.org/2025.emnlp-demos.13/
%P 181-195
Markdown (Informal)
[Marcel: A Lightweight and Open-Source Conversational Agent for University Student Support](https://aclanthology.org/2025.emnlp-demos.13/) (Trienes et al., EMNLP 2025)
ACL