A Framework for Domain-Specific Dataset Creation and Adaptation of Large Language Models

A Framework for Domain-Specific Dataset Creation and Adaptation of Large Language Models

This paper introduces a novel framework for addressing domain adaptation challenges in large language models (LLMs), emphasising privacy-preserving synthetic data generation and efficient fine-tuning. The proposed framework employs a multi-stage approach that includes document ingestion, relevance a...

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Bibliographic Details
Main Authors: George Balaskas, Homer Papadopoulos, Dimitra Pappa, Quentin Loisel, Sebastien Chastin
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Computers
Subjects:
dataset creation
model adaptation
model fine-tuning
deep learning
large language models
Online Access:https://www.mdpi.com/2073-431X/14/5/172
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