Demo: Soccer Information Retrieval via Natural Queries using SoccerRAG

• URL: http://arxiv.org/abs/2406.01280v2
• Date: Mon, 22 Jul 2024 06:44:20 GMT
• Title: Demo: Soccer Information Retrieval via Natural Queries using SoccerRAG
• Authors: Aleksander Theo Strand, Sushant Gautam, Cise Midoglu, Pål Halvorsen,
• Abstract summary: SoccerRAG is an innovative framework designed to harness the power of Retrieval Augmented Generation (RAG) and Large Language Models (LLMs) By leveraging a multimodal dataset, SoccerRAG supports dynamic querying and automatic data validation. We present a novel interactive user interface (UI) based on the Chainlit framework which wraps around the core functionality.
• Score: 42.095162323265676
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The rapid evolution of digital sports media necessitates sophisticated information retrieval systems that can efficiently parse extensive multimodal datasets. This paper demonstrates SoccerRAG, an innovative framework designed to harness the power of Retrieval Augmented Generation (RAG) and Large Language Models (LLMs) to extract soccer-related information through natural language queries. By leveraging a multimodal dataset, SoccerRAG supports dynamic querying and automatic data validation, enhancing user interaction and accessibility to sports archives. We present a novel interactive user interface (UI) based on the Chainlit framework which wraps around the core functionality, and enable users to interact with the SoccerRAG framework in a chatbot-like visual manner.

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