CLOct 12, 2023

Simplicity Level Estimate (SLE): A Learned Reference-Less Metric for Sentence Simplification

arXiv:2310.08170v1137 citationsh-index: 9
Originality Highly original
AI Analysis

This addresses the problem of evaluating sentence simplification for researchers and practitioners, offering a reference-less metric that improves upon current methods.

The paper tackles the challenge of automatic evaluation for sentence simplification by proposing a new learned metric called Simplicity Level Estimate (SLE), which focuses on simplicity and outperforms almost all existing metrics in correlation with human judgments.

Automatic evaluation for sentence simplification remains a challenging problem. Most popular evaluation metrics require multiple high-quality references -- something not readily available for simplification -- which makes it difficult to test performance on unseen domains. Furthermore, most existing metrics conflate simplicity with correlated attributes such as fluency or meaning preservation. We propose a new learned evaluation metric (SLE) which focuses on simplicity, outperforming almost all existing metrics in terms of correlation with human judgements.

Code Implementations1 repo
Foundations

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