Label-aware Multi-level Contrastive Learning for Cross-lingual Spoken Language Understanding

no code implementations • 7 May 2022 • Shining Liang, Linjun Shou, Jian Pei, Ming Gong, Wanli Zuo, Xianglin Zuo, Daxin Jiang

Despite the great success of spoken language understanding (SLU) in high-resource languages, it remains challenging in low-resource languages mainly due to the lack of labeled training data.

Contrastive Learning Spoken Language Understanding +1

Reinforced Iterative Knowledge Distillation for Cross-Lingual Named Entity Recognition

no code implementations • 1 Jun 2021 • Shining Liang, Ming Gong, Jian Pei, Linjun Shou, Wanli Zuo, Xianglin Zuo, Daxin Jiang

Named entity recognition (NER) is a fundamental component in many applications, such as Web Search and Voice Assistants.

Cross-Lingual NER Knowledge Distillation +5

A Review of Dataset and Labeling Methods for Causality Extraction

no code implementations • COLING 2020 • Jinghang Xu, Wanli Zuo, Shining Liang, Xianglin Zuo

Moreover, there is a lack of unified causal sequence label methods, which constitute the key factors that hinder the progress of causality extraction research.

A Multi-level Neural Network for Implicit Causality Detection in Web Texts

1 code implementation • 18 Aug 2019 • Shining Liang, Wanli Zuo, Zhenkun Shi, Sen Wang, Junhu Wang, Xianglin Zuo

Mining causality from text is a complex and crucial natural language understanding task corresponding to the human cognition.

Causal Inference Feature Engineering +3