Papers by Anran Hao

2 papers
Soft Syntactic Reinforcement for Neural Event Extraction (2025.naacl-long)

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Challenge: Recent event extraction methods rely on pre-trained language models but still suffer from errors due to a lack of syntactic knowledge.
Approach: They propose a method to incorporate syntactic information into PLM-based models for event extraction (EE) this method uses a standard dependency corpus to select syntax-related dimensions of the model's representation.
Outcome: The proposed method outperforms baseline models and existing syntactic reinforcement methods on sentence-level and document-level EE benchmark datasets.
Jointprop: Joint Semi-supervised Learning for Entity and Relation Extraction with Heterogeneous Graph-based Propagation (2023.acl-long)

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Challenge: Named Entity Recognition and Relation Extraction are two crucial tasks in Information Extraction.
Approach: They propose a framework for joint semi-supervised entity and relation extraction that captures the global structure information between tasks and exploits interactions within unlabeled data.
Outcome: The proposed framework outperforms state-of-the-art semi-supervised approaches on NER and RE tasks.

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