Papers by Xingxian Liu
Cluster-aware Pseudo-Labeling for Supervised Open Relation Extraction (2022.coling-1)
Copied to clipboard
| Challenge: | Existing methods to extract novel relations do not achieve effective knowledge transfer . experimental results show that the proposed method is state-of-the-arts . |
| Approach: | They propose a Cluster-aware Pseudo-Labeling method to improve pseudo-labels quality . they firstly pre-trained the relation models with pre-defined relations to learn them . |
| Outcome: | The proposed method improves the pseudo-labels quality and transfer more knowledge for discovering novel relations. |
Learning to Rank Utterances for Query-Focused Meeting Summarization (2023.findings-acl)
Copied to clipboard
| Challenge: | Existing methods to generate a generic summary for meetings are limited due to the conflict between long meetings and limited input size. |
| Approach: | They propose a Ranker-Generator framework that learns to rank utterances by comparing them in pairs and learning from the global orders, then uses top utterrances as the generator’s input. |
| Outcome: | The proposed model outperforms existing models with fewer parameters due to the conflict between long meetings and limited input size. |