@inproceedings{schneider-etal-2025-collex,
    title = "{C}oll{EX} {--} A Multimodal Agentic {RAG} System Enabling Interactive Exploration of Scientific Collections",
    author = "Schneider, Florian  and
      Baba Ahmadi, Narges  and
      Baba Ahmadi, Niloufar  and
      Vogel, Iris  and
      Semmann, Martin  and
      Biemann, Chris",
    editor = "Kriz, Reno  and
      Murray, Kenton",
    booktitle = "Proceedings of the 1st Workshop on Multimodal Augmented Generation via Multimodal Retrieval (MAGMaR 2025)",
    month = aug,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/landing_page/2025.magmar-1.2/",
    pages = "18--39",
    ISBN = "979-8-89176-280-0",
    abstract = "In this paper, we introduce CollEx, an innovative multimodal agentic Retrieval-Augmented Generation (RAG) system designed to enhance interactive exploration of extensive scientific collections. Given the overwhelming volume and inherent complexity of scientific collections, conventional search systems often lack necessary intuitiveness and interactivity, presenting substantial barriers for learners, educators, and researchers. CollEx addresses these limitations by employing state-of-the-art Large Vision-Language Models (LVLMs) as multimodal agents accessible through an intuitive chat interface. By abstracting complex interactions via specialized agents equipped with advanced tools, CollEx facilitates curiosity-driven exploration, significantly simplifying access to diverse scientific collections and records therein. Our system integrates textual and visual modalities, supporting educational scenarios that are helpful for teachers, pupils, students, and researchers by fostering independent exploration as well as scientific excitement and curiosity. Furthermore, CollEx serves the research community by discovering interdisciplinary connections and complementing visual data. We illustrate the effectiveness of our system through a proof-of-concept application containing over 64,000 unique records across 32 collections from a local scientific collection from a public university."
}