Papers by Simin Rao

2 papers
Cross-Lingual Leveled Reading Based on Language-Invariant Features (2021.findings-emnlp)

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Challenge: Leveled reading (LR) aims to automatically classify texts by the cognitive levels of readers.
Approach: They propose to use adversarial training and cross-lingual pre-training methods to transfer LR knowledge from annotated data in resource-rich English to Chinese.
Outcome: The proposed method captures language-invariant features between English and Chinese.
Promoting Pre-trained LM with Linguistic Features on Automatic Readability Assessment (2022.aacl-short)

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Challenge: Automatic readability assessment (ARA) aims at classifying the readability level of a text automatically.
Approach: They propose to integrate linguistic features with pre-trained language models to improve the accuracy of ARA.
Outcome: The proposed algorithm improves on the long passage characteristic of ARA using commonly used linguistic features and abundant datasets.

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