5 papers · 1 filter
Enhancing Accuracy and Maintainability in Nuclear Plant Data Retrieval: A Function-Calling LLM Approach Over NL-to-SQL
Mishca de Costa, Muhammad Anwar, Dave Mercier +2
Retrieving operational data from nuclear power plants requires exceptional accuracy and transparency due to the criticality of the decisions it supports. Traditionally, natural lan…
Unlocking the Potential of Large Language Models in the Nuclear Industry with Synthetic Data
Muhammad Anwar, Daniel Lau, Mishca de Costa +1
The nuclear industry possesses a wealth of valuable information locked away in unstructured text data. This data, however, is not readily usable for advanced Large Language Model (…
Towards Secure and Private Language Models for Nuclear Power Plants
Muhammad Anwar, Mishca de Costa, Issam Hammad +1
This paper introduces a domain-specific Large Language Model for nuclear applications, built from the publicly accessible Essential CANDU textbook. Drawing on a compact Transformer…
Classification of Safety Events at Nuclear Sites using Large Language Models
Mishca de Costa, Muhammad Anwar, Daniel Lau +1
This paper proposes the development of a Large Language Model (LLM) based machine learning classifier designed to categorize Station Condition Records (SCRs) at nuclear power stati…
Evaluating ChatGPT on Nuclear Domain-Specific Data
Muhammad Anwar, Mischa de Costa, Issam Hammad +1
This paper examines the application of ChatGPT, a large language model (LLM), for question-and-answer (Q&A) tasks in the highly specialized field of nuclear data. The primary focus…