基于字词粒度噪声数据增强的中文语法纠错(Chinese Grammatical Error Correction enhanced by Data Augmentation from Word and Character Levels)

no code implementations • CCL 2021 • Zecheng Tang, Yixin Ji, Yibo Zhao, Junhui Li

Data Augmentation Grammatical Error Correction

Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models

1 code implementation • 8 Mar 2023 • Chenfei Wu, Shengming Yin, Weizhen Qi, Xiaodong Wang, Zecheng Tang, Nan Duan

To this end, We build a system called \textbf{Visual ChatGPT}, incorporating different Visual Foundation Models, to enable the user to interact with ChatGPT by 1) sending and receiving not only languages but also images 2) providing complex visual questions or visual editing instructions that require the collaboration of multiple AI models with multi-steps.

Improving Temporal Generalization of Pre-trained Language Models with Lexical Semantic Change

1 code implementation • 31 Oct 2022 • Zhaochen Su, Zecheng Tang, Xinyan Guan, Juntao Li, Lijun Wu, Min Zhang

Existing methods mainly perform continual training to mitigate such a misalignment.

Language Modelling

Chinese grammatical error correction based on knowledge distillation

2 code implementations • 31 Jul 2022 • Peng Xia, Yuechi Zhou, Ziyan Zhang, Zecheng Tang, Juntao Li

In view of the poor robustness of existing Chinese grammatical error correction models on attack test sets and large model parameters, this paper uses the method of knowledge distillation to compress model parameters and improve the anti-attack ability of the model.

Grammatical Error Correction Knowledge Distillation