@inproceedings{1375a2f43d274dbf91fc4be8d0e5922e,
title = "Two Large Language Model-based Methods to Validate Open-Ended Problem Solving in Teams",
abstract = "This paper describes two Large Language Model (LLM)-based methods to validate programming solutions devised in small teams for open-ended problems. The methods address the static mode, when validation is conducted at the end of problem solving, and a real-time mode, if validation is repeatedly performed at consecutive time intervals. The validation methods automatically prompt an LLM to find inconsistencies between the problem description, the user intentions verbally expressed through dialog, and the created programming code. Experiments studied the performance of the two validation methods.",
keywords = "Large Language Models, open-ended problems, prompting, solution validation, teams",
author = "Hashmath Shaik and Gnaneswar Villuri and Alex Doboli",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025 ; Conference date: 25-11-2025 Through 28-11-2025",
year = "2025",
doi = "10.1109/FLLM67465.2025.11390952",
language = "English",
series = "2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1203--1210",
editor = "Kai Erenli and Christian Guetl and Yaser Jararweh and Jim Jansen",
booktitle = "2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025",
}