Papers by Honghui Chen

2 papers
DRK: Discriminative Rule-based Knowledge for Relieving Prediction Confusions in Few-shot Relation Extraction (2022.coling-1)

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Challenge: Existing methods to identify relation type in low-resource scenario fall into prediction confusions owing to the limited inference ability over shallow text features.
Approach: They propose a discriminative rule-based knowledge method to identify the relation type between entities in a given text in the low-resource scenario.
Outcome: The proposed method improves on four types of meta tasks with a 6.0% accuracy gain on average.
Heterogeneous Graph Neural Networks to Predict What Happen Next (2020.coling-main)

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Challenge: Existing work on event representation cannot capture discontinuous event segments . Existing models cannot represent heterogeneous relations and discontinuous events .
Approach: They propose a heterogeneous-event graph network to model missing events . they employ each unique word and individual event as nodes in the graph .
Outcome: The proposed model outperforms baseline models on one-step and multi-step inference tasks.

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