Lidia S. Chao

Improving Grammatical Error Correction with Multimodal Feature Integration

2023

Grammatical error correction (GEC) is a promising task aimed at correcting errors in a text. Many methods have been proposed to facilitate this task with remarkable results. However, most of them only focus on enhancing …

ConsistTL: Modeling Consistency in Transfer Learning for Low-Resource Neural Machine Translation

2022

Transfer learning is a simple and powerful method that can be used to boost model performance of low-resource neural machine translation (NMT). Existing transfer learning methods for NMT are static, which simply transfer knowledge from …

Learning Deep Transformer Models for Machine Translation

2019

Transformer is the state-of-the-art model in recent machine translation evaluations. Two strands of research are promising to improve models of this kind: the first uses wide networks (a.k.a. Transformer-Big) and has been the de facto …

Modeling Localness for Self-Attention Networks

2018

Self-attention networks have proven to be of profound value for its strength of capturing global dependencies. In this work, we propose to model localness for self-attention networks, which enhances the ability of capturing useful local …