Papers by Jinxi Liu
Causality-aware Concept Extraction based on Knowledge-guided Prompting (2023.acl-long)
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| Challenge: | Concepts in knowledge graphs (KGs) are far from complete in existing knowledge graph models. |
| Approach: | They propose to equip a PLM-based extractor with a knowledge-guided prompt to alleviate concept bias by removing spurious co-occurrence correlations from existing knowledge. |
| Outcome: | The proposed prompt can alleviate concept bias and improve the performance of existing models. |
Generative Entity Typing with Curriculum Learning (2022.emnlp-main)
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| Challenge: | Entity typing fails to assign an entity to the types beyond the predefined type set. |
| Approach: | They propose a generative entity typing paradigm that assigns types to entities . traditional classification-based approaches fail to assign entities to the types beyond the predefined set . they employ curriculum learning to train the model on heterogeneous data . |
| Outcome: | The proposed model outperforms the state-of-the-art model on heterogeneous training data. |