Papers by Shujuan Yin
A Novel Global Feature-Oriented Relational Triple Extraction Model based on Table Filling (2021.emnlp-main)
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| Challenge: | Table filling based relational triple extraction methods focus on using local features but ignore the global associations of relations and token pairs, which increases the possibility of overlooking some important information during triple extraction. |
| Approach: | They propose a global feature-oriented triple extraction model that makes full use of the two kinds of global associations of relations and token pairs. |
| Outcome: | The proposed model achieves state-of-the-art on three benchmark datasets. |
A Three-Stage Learning Framework for Low-Resource Knowledge-Grounded Dialogue Generation (2021.emnlp-main)
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| Challenge: | Existing knowledge-grounded dialogues perform poorly when transfer into new domains with limited training samples. |
| Approach: | They propose a weakly supervised three-stage learning framework based on weakly-supervised learning based upon large scale ungrounded dialogues and unstructured knowledge base. |
| Outcome: | The proposed framework outperforms state-of-the-art methods even in zero-resource setting. |