MeaningBERT: assessing meaning preservation between sentences.

ABSTRACT: In the field of automatic text simplification, assessing whether or not the meaning of the original text has been preserved during simplification is of paramount importance. Metrics relying on n-gram overlap assessment may struggle to deal with simplifications which replace complex phrases with their simpler paraphrases. Current evaluation metrics for meaning preservation based on large language models (LLMs), such as BertScore in machine translation or QuestEval in summarization, have been proposed. However, none has a strong correlation with human judgment of meaning preservation. Moreover, such metrics have not been assessed in the context of text simplification research. In this study, we present a meta-evaluation of several metrics we apply to measure content similarity in text simpli

SUBMITTER: Beauchemin D 

PROVIDER: S-EPMC10557945 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature