Synthetic Data Generation Using Large Language Models: Advances in Text and Code

Synthetic Data Generation Using Large Language Models: Advances in Text and Code

This survey reviews how large language models (LLMs) are transforming synthetic training data generation in both natural language and code domains. By producing artificial but task-relevant examples, these models can significantly augment or even substitute for real-world datasets, particularly in s...

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Bibliographic Details
Main Authors: Mihai Nadas, Laura Diosan, Andreea Tomescu
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Synthetic data generation
large language models (LLMs)
text data augmentation
code data synthesis
prompt engineering
instruction tuning
Online Access:https://ieeexplore.ieee.org/document/11080380/
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https://ieeexplore.ieee.org/document/11080380/

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