MedDialog: Large-scale Medical Dialogue Datasets

1 code implementation • EMNLP 2020 • Guangtao Zeng, Wenmian Yang, Zeqian Ju, Yue Yang, Sicheng Wang, Ruisi Zhang, Meng Zhou, Jiaqi Zeng, Xiangyu Dong, Ruoyu Zhang, Hongchao Fang, Penghui Zhu, Shu Chen, Pengtao Xie

We also study the transferability of models trained on MedDialog to low-resource medical dialogue generation tasks.

Dialogue Generation Transfer Learning

Uncovering Main Causalities for Long-tailed Information Extraction

1 code implementation • EMNLP 2021 • Guoshun Nan, Jiaqi Zeng, Rui Qiao, Zhijiang Guo, Wei Lu

Information Extraction (IE) aims to extract structural information from unstructured texts.

Causal Inference Selection bias

Adversarial Learning with Mask Reconstruction for Text-Guided Image Inpainting

1 code implementation • Conference 2021 • Xingcai Wu, Yucheng Xie, Jiaqi Zeng, Zhenguo Yang, Yi Yu, Qing Li, and Wenyin Liu

In this paper, we propose an adversarial learning framework with mask reconstruction (ALMR) for image inpainting with textual guidance, which consists of a two-stage generator and dual discriminators.

Image Inpainting

Counterfactual Thinking for Long-tailed Information Extraction

no code implementations • 1 Jan 2021 • Guoshun Nan, Jiaqi Zeng, Rui Qiao, Wei Lu

However, in practice, the long-tailed and imbalanced data may lead to severe bias issues for deep learning models, due to very few training instances available for the tail classes.

Causal Inference Event Detection +8

Contrastive Self-supervised Learning for Graph Classification

no code implementations • 13 Sep 2020 • Jiaqi Zeng, Pengtao Xie

A contrastive loss is defined to learn graph encoders by judging whether two augmented graphs are from the same original graph.

Data Augmentation General Classification +2

MedDialog: Two Large-scale Medical Dialogue Datasets

1 code implementation • arXiv 2020 • Xuehai He, Shu Chen, Zeqian Ju, Xiangyu Dong, Hongchao Fang, Sicheng Wang, Yue Yang, Jiaqi Zeng, Ruisi Zhang, Ruoyu Zhang, Meng Zhou, Penghui Zhu, Pengtao Xie

Medical dialogue systems are promising in assisting in telemedicine to increase access to healthcare services, improve the quality of patient care, and reduce medical costs.