Papers by Yechun Tang
Heterogeneous Graph Neural Networks for Concept Prerequisite Relation Learning in Educational Data (2021.naacl-main)
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| Challenge: | Existing methods to learn prerequisite relations among concepts are lacking . concepts are crucial for learning, organizing, applying and generating knowledge . |
| Approach: | They propose a concept prerequisite relation learning approach which combines concept representation and concept pairwise features to make it more practical. |
| Outcome: | The proposed method achieves state-of-the-art results on four datasets. |
Improving Complex Knowledge Base Question Answering via Question-to-Action and Question-to-Question Alignment (2022.emnlp-main)
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| Challenge: | ALCQA addresses the semantic and structural gap between natural language and action sequences . a priori, the semantics of the question and action are not well understood . |
| Approach: | They propose an alignment-enhanced complex question answering framework which aligns questions and actions into sequences. |
| Outcome: | The proposed framework outperforms state-of-the-art methods on a CQA and WQSP dataset. |