Yuan Chen


Learning Syntactic Dense Embedding with Correlation Graph for Automatic Readability Assessment
Xinying Qiu | Yuan Chen | Hanwu Chen | Jian-Yun Nie | Yuming Shen | Dawei Lu
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

Deep learning models for automatic readability assessment generally discard linguistic features traditionally used in machine learning models for the task. We propose to incorporate linguistic features into neural network models by learning syntactic dense embeddings based on linguistic features. To cope with the relationships between the features, we form a correlation graph among features and use it to learn their embeddings so that similar features will be represented by similar embeddings. Experiments with six data sets of two proficiency levels demonstrate that our proposed methodology can complement BERT-only model to achieve significantly better performances for automatic readability assessment.


ECNU: Effective Semantic Relations Classification without Complicated Features or Multiple External Corpora
Yuan Chen | Man Lan | Jian Su | Zhi Min Zhou | Yu Xu
Proceedings of the 5th International Workshop on Semantic Evaluation