13 citations · 23 across the 5 of their papers we have counts for
5 papers
Enhancing Complex Causality Extraction via Improved Subtask Interaction and Knowledge Fusion
Jinglong Gao, Chen Lu, Xiao Ding +3
Event Causality Extraction (ECE) aims at extracting causal event pairs from texts. Despite ChatGPT's recent success, fine-tuning small models remains the best approach for the ECE…
Improving Cross-Task Generalization with Step-by-Step Instructions
Yang Wu, Yanyan Zhao, Zhongyang Li +2
Instruction tuning has been shown to be able to improve cross-task generalization of language models. However, it is still challenging for language models to complete the target ta…
ReCo: Reliable Causal Chain Reasoning via Structural Causal Recurrent Neural Networks
Kai Xiong, Xiao Ding, Zhongyang Li +4
Causal chain reasoning (CCR) is an essential ability for many decision-making AI systems, which requires the model to build reliable causal chains by connecting causal pairs. Howev…
CausalBERT: Injecting Causal Knowledge Into Pre-trained Models with Minimal Supervision
Zhongyang Li, Xiao Ding, Kuo Liao +2
Recent work has shown success in incorporating pre-trained models like BERT to improve NLP systems. However, existing pre-trained models lack of causal knowledge which prevents tod…
ELG: An Event Logic Graph
Xiao Ding, Zhongyang Li, Ting Liu +1
The evolution and development of events have their own basic principles, which make events happen sequentially. Therefore, the discovery of such evolutionary patterns among events…