Year: 2025
Type: article
Abstract: In the vast landscape of CERN’s internal documentation, finding and accessing relevant detailed information remains a complex and timeconsuming task. To address this challenge, the AccGPT project (Accelerating Science GPT) aims for the development of an intelligent chatbot leveraging Natural Language Processing (NLP) technologies. We utilize open-source Large Language Models (LLMs) to create a specialized chatbot for CERN internal text-based knowledge retrieval, with the potential future extensions to code assistance and other functionalities. A promising first prototype utilising a Retrieval Augmented Generation (RAG) pipeline has already been developed and deployed. Ongoing improvements focus on enhancing the retrieval accuracy, integrating more powerful and larger LLMs, or fine-tuning with domain-specific data to improve domain accuracy and relevance. The chatbot’s user interface design and overall experience are being iteratively improved, and efforts are underway to prepare AccGPT for community-wide testing. Additionally, automated data scraping and preprocessing pipelines are being implemented to ensure an up-to-date, selfsustaining knowledge base.
Institution: European Organization for Nuclear Research
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7127129452
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