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Beyond One-Size-Fits-All : Inversion Learning for Highly Effective NLG Evaluation Prompts

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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:52928
institution FRELIP
journal_source_facet Transactions of the Association for Computational Linguistics
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Beyond One-Size-Fits-All : Inversion Learning for Highly Effective NLG Evaluation Prompts
— — — — — 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 Beyond One-Size-Fits-All : Inversion Learning for Highly Effective NLG Evaluation Prompts
title_auth Beyond One-Size-Fits-All : Inversion Learning for Highly Effective NLG Evaluation Prompts
title_full Beyond One-Size-Fits-All : Inversion Learning for Highly Effective NLG Evaluation Prompts
title_fullStr Beyond One-Size-Fits-All : Inversion Learning for Highly Effective NLG Evaluation Prompts
title_full_unstemmed Beyond One-Size-Fits-All : Inversion Learning for Highly Effective NLG Evaluation Prompts
title_short Beyond One-Size-Fits-All : Inversion Learning for Highly Effective NLG Evaluation Prompts
title_sort beyond one-size-fits-all : inversion learning for highly effective nlg evaluation prompts
topic — — — — — Linguistics and Philology
Language & Literature
Arts & Humanities
url https://direct.mit.edu/tacl/article/doi/10.1162/TACL.a.617/136551/Beyond-One-Size-Fits-All-Inversion-Learning-for