A comparative analysis of encoder only and decoder only models for challenging LLM-generated STEM MCQs using a self-evaluation approach
Large Language Models (LLMs) have demonstrated impressive capabilities in various tasks, including Multiple-Choice Question Answering (MCQA) evaluated on benchmark datasets with few-shot prompting. Given the absence of benchmark Science, Technology, Engineering, and Mathematics (STEM) datasets on Mu...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
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| Series: | Natural Language Processing Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S294971912500007X |
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