RCML at TSAR-2022 Shared Task: Lexical Simplification With Modular Substitution Candidate Ranking

Desislava Aleksandrova, Olivier Brochu Dufour
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引用次数: 4

Abstract

This paper describes the lexical simplification system RCML submitted to the English language track of the TSAR-2022 Shared Task. The system leverages a pre-trained language model to generate contextually plausible substitution candidates which are then ranked according to their simplicity as well as their grammatical and semantic similarity to the target complex word. Our submissions secure 6th and 7th places out of 33, improving over the SOTA baseline for 27 out of the 51 metrics.
RCML在TSAR-2022共享任务:词汇简化与模块化替代候选排序
本文描述了提交给TSAR-2022共享任务英语语言轨道的词汇简化系统RCML。该系统利用预先训练的语言模型来生成上下文合理的替代候选词,然后根据其简单性以及与目标复杂词的语法和语义相似性进行排名。我们的提交在33项中获得了第6和第7名,在51项指标中有27项比SOTA基线有所提高。
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