The fine art of fine-tuning: A structured review of advanced LLM fine-tuning techniques
Transformer-based models have consistently demonstrated superior accuracy compared to various traditional models across a range of downstream tasks. However, due to their large nature, training or fine-tuning them for specific tasks has heavy computational and memory demands. This causes the creatio...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
|
| Series: | Natural Language Processing Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2949719125000202 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|