no code implementations • 4 Aug 2023 • Shiyao Cui, Xin Cong, Jiawei Sheng, Xuebin Wang, Tingwen Liu, Jinqiao Shi
In this paper, we regard public pre-trained language models as knowledge bases and automatically mine the script-related knowledge via prompt-learning.
no code implementations • 5 Apr 2023 • Shiyao Cui, Jiangxia Cao, Xin Cong, Jiawei Sheng, Quangang Li, Tingwen Liu, Jinqiao Shi
For the first issue, a refinement-regularizer probes the information-bottleneck principle to balance the predictive evidence and noisy information, yielding expressive representations for prediction.
no code implementations • 19 Mar 2023 • Hongmeng Liu, Jiapeng Zhao, Yixuan Huo, Yuyan Wang, Chun Liao, Liyan Shen, Shiyao Cui, Jinqiao Shi
Traditional user representation methods mainly rely on modeling the text information of posts and cannot capture the temporal content and the forum interaction of posts.
no code implementations • 1 Mar 2023 • Wenrui Li, Zhengyu Ma, Jinqiao Shi, Xiaopeng Fan
The main module is the common knowledge adaptor (CKA) with both the style embedding extractor (SEE) and the common knowledge optimization (CKO) modules.
1 code implementation • COLING 2022 • Shiyao Cui, Jiawei Sheng, Xin Cong, Quangang Li, Tingwen Liu, Jinqiao Shi
Event Causality Identification (ECI), which aims to detect whether a causality relation exists between two given textual events, is an important task for event causality understanding.
1 code implementation • 3 Jul 2022 • Shaopu Wang, Xiaojun Chen, Mengzhen Kou, Jinqiao Shi
Besides, our method allows researchers to distill knowledge from deeper networks to improve students further.
no code implementations • 7 Feb 2022 • Shiyao Cui, Xin Cong, Bowen Yu, Tingwen Liu, Yucheng Wang, Jinqiao Shi
Meanwhile, rough reading is explored in a multi-round manner to discover undetected events, thus the multi-events problem is handled.
no code implementations • 3 Dec 2020 • Shiyao Cui, Bowen Yu, Xin Cong, Tingwen Liu, Quangang Li, Jinqiao Shi
A heterogeneous graph attention networks is then introduced to propagate relational message and enrich information interaction.
1 code implementation • Findings of the Association for Computational Linguistics 2020 • Shiyao Cui, Bowen Yu, Tingwen Liu, Zhen-Yu Zhang, Xuebin Wang, Jinqiao Shi
Previous studies on the task have verified the effectiveness of integrating syntactic dependency into graph convolutional networks.