Large Language Models: New Opportunities for Access to Science

TL;DR

Large Language Models like ChatGPT are transforming access to scientific information by improving retrieval and understanding of scientific data, publications, and software, thus enhancing open science and systematic insights.

Contribution

This paper explores the potential of Large Language Models in scientific information retrieval and demonstrates their application in the open science environment of KM3NeT neutrino detectors.

Findings

Enhanced access to scientific data and publications.

Successful integration of Retrieval Augmented Generation in open science.

Potential for broader application in scientific research.

Abstract

The adaptation of Large Language Models like ChatGPT for information retrieval from scientific data, software and publications is offering new opportunities to simplify access to and understanding of science for persons from all levels of expertise. They can become tools to both enhance the usability of the open science environment we are building as well as help to provide systematic insight to a long-built corpus of scientific publications. The uptake of Retrieval Augmented Generation-enhanced chat applications in the construction of the open science environment of the KM3NeT neutrino detectors serves as a focus point to explore and exemplify prospects for the wider application of Large Language Models for our science.