Адаптиране на големи езикови модели за специфични бизнес процеси
Adapting large language Models for Specific Business Processes

Author(s): Venko Andonov
Subject(s): Economy, Business Economy / Management, ICT Information and Communications Technologies
Published by: Университет за национално и световно стопанство (УНСС)
Keywords: large language models; AI model adaptation; performance evaluation
Summary/Abstract: In the rapidly evolving field of artificial intelligence, large language models (LLMs) are emerging as key tools for business applications, but their effectiveness depends on adaptation to specific organizational needs. This study provides an analysis of three main methods for adapting LLMs: prompt engineering, retrieval-augmented generation (RAG), and fine-tuning. By examining the potential for personalization, resource requirements, and economic aspects of each method, the study offers guidance for organizations seeking to optimize LLM performance. Additionally, key aspects of performance evaluation are considered, including metrics such as accuracy, relevance, and coherence, as well as the financial implications of implementing these methods.

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