Achieving Efficient Prompt Engineering in Large Language Models Using a Hybrid and Multi-Objective Optimization Framework

Achieving Efficient Prompt Engineering in Large Language Models Using a Hybrid and Multi-Objective Optimization Framework

Prompt optimization is crucial for enhancing the performance of large language models. Traditional Bayesian Optimization (BO) methods face challenges such as local refinement limitations, insufficient parameter tuning, and difficulty handling multi-objectives. This study introduces a hybrid multi-ob...

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Bibliographic Details
Main Authors: Narayanaswamy Sridevi Kottapalli, Muniswamy Rajanna
Format: Article
Language:English
Published: Sciendo 2025-06-01
Series:Cybernetics and Information Technologies
Subjects:
bayesian optimization
bert
evolutionary algorithm
large language model
prompt engineering
Online Access:https://doi.org/10.2478/cait-2025-0012
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https://doi.org/10.2478/cait-2025-0012

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