KamerRaad: Enhancing Information Retrieval in Belgian National Politics through Hierarchical Summarization and Conversational Interfaces
<|reference_start|>KamerRaad: Enhancing Information Retrieval in Belgian National Politics through Hierarchical Summarization and Conversational Interfaces: KamerRaad is an AI tool that leverages large language models to help citizens interactively engage with Belgian political information. The tool extracts and concisely summarizes key excerpts from parliamentary proceedings, followed by the potential for interaction based on generative AI that allows users to steadily build up their understanding. KamerRaad's front-end, built with Streamlit, facilitates easy interaction, while the back-end employs open-source models for text embedding and generation to ensure accurate and relevant responses. By collecting feedback, we intend to enhance the relevancy of our source retrieval and the quality of our summarization, thereby enriching the user experience with a focus on source-driven dialogue.<|reference_end|>
@article{rogiers2024kamerraad:,
    title={KamerRaad: Enhancing Information Retrieval in Belgian National Politics
  through Hierarchical Summarization and Conversational Interfaces},
    author={Alexander Rogiers, Maarten Buyl, Bo Kang, and Tijl De Bie},
    journal={arXiv preprint arXiv:2404.17597},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.17597},
    primaryClass={cs.IR}
}