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Fine-tuning Large Language Models with Limited Data: A Survey and Practical Guide

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Published in:Transactions of the Association for Computational Linguistics
Format: Online Article RSS Article
Published: 2026
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container_title Transactions of the Association for Computational Linguistics
description
discipline_display Arts & Humanities
discipline_facet Arts & Humanities
format Online Article
RSS Article
genre Journal Article
id rss_article:25534
institution FRELIP
journal_source_facet Transactions of the Association for Computational Linguistics
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Fine-tuning Large Language Models with Limited Data: A Survey and Practical Guide
— — — — — Linguistics and Philology
Language & Literature
Arts & Humanities
sub_discipline_display Language & Literature
sub_discipline_facet Language & Literature
subject_display — — — — — Linguistics and Philology
Language & Literature
Arts & Humanities
— — — — — Linguistics and Philology
Language & Literature
Arts & Humanities
subject_facet — — — — — Linguistics and Philology
Language & Literature
Arts & Humanities
title Fine-tuning Large Language Models with Limited Data: A Survey and Practical Guide
title_auth Fine-tuning Large Language Models with Limited Data: A Survey and Practical Guide
title_full Fine-tuning Large Language Models with Limited Data: A Survey and Practical Guide
title_fullStr Fine-tuning Large Language Models with Limited Data: A Survey and Practical Guide
title_full_unstemmed Fine-tuning Large Language Models with Limited Data: A Survey and Practical Guide
title_short Fine-tuning Large Language Models with Limited Data: A Survey and Practical Guide
title_sort fine-tuning large language models with limited data: a survey and practical guide
topic — — — — — Linguistics and Philology
Language & Literature
Arts & Humanities
url https://direct.mit.edu/tacl/article/doi/10.1162/TACL.a.627/136154/Fine-tuning-Large-Language-Models-with-Limited