ESAC (EQ-SANS Assisting Chatbot): Application of Large Language Models and Retrieval-Augmented Generation for Enhanced User Experience at EQ-SANS

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Do, Changwoo, Nagy, Gergely, Heller, William T.
Natura: Preprint
Pubblicazione: 2024
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866916338109251584
author Do, Changwoo
Nagy, Gergely
Heller, William T.
author_facet Do, Changwoo
Nagy, Gergely
Heller, William T.
contents Neutron scattering experiments have played vital roles in exploring materials properties in the past decades. While user interfaces have been improved over time, neutron scattering experiments still require specific knowledge or training by an expert due to the complexity of such advanced instrumentation and the limited number of experiments each person may perform each year. This paper introduces an innovative chatbot application that leverages Large Language Models(LLM) and Retrieval-Augmented Generation (RAG) technologies to significantly enhance the user experience at the EQ-SANS, a small-angle neutron scattering instrument at the Spallation Neutron Source of Oak Ridge National Laboratory. Through a user-centric design approach, the EQ-SANS Assisting Chatbot (ESAC) serves as an interactive reference for users, thereby facilitating the use of the instrument by visiting scientists. By bridging the gap between the users of EQ-SANS and the control systems required to perform their experiments, the ESAC sets a new standard for interactive learning and support for the scientific community using large-scale scientific facilities.
format Preprint
id arxiv_https___arxiv_org_abs_2407_19075
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle ESAC (EQ-SANS Assisting Chatbot): Application of Large Language Models and Retrieval-Augmented Generation for Enhanced User Experience at EQ-SANS
Do, Changwoo
Nagy, Gergely
Heller, William T.
Instrumentation and Detectors
Neutron scattering experiments have played vital roles in exploring materials properties in the past decades. While user interfaces have been improved over time, neutron scattering experiments still require specific knowledge or training by an expert due to the complexity of such advanced instrumentation and the limited number of experiments each person may perform each year. This paper introduces an innovative chatbot application that leverages Large Language Models(LLM) and Retrieval-Augmented Generation (RAG) technologies to significantly enhance the user experience at the EQ-SANS, a small-angle neutron scattering instrument at the Spallation Neutron Source of Oak Ridge National Laboratory. Through a user-centric design approach, the EQ-SANS Assisting Chatbot (ESAC) serves as an interactive reference for users, thereby facilitating the use of the instrument by visiting scientists. By bridging the gap between the users of EQ-SANS and the control systems required to perform their experiments, the ESAC sets a new standard for interactive learning and support for the scientific community using large-scale scientific facilities.
title ESAC (EQ-SANS Assisting Chatbot): Application of Large Language Models and Retrieval-Augmented Generation for Enhanced User Experience at EQ-SANS
topic Instrumentation and Detectors
url https://arxiv.org/abs/2407.19075