Papers by Nghia Ngo Trung

2 papers
Unsupervised Domain Adaptation for Event Detection using Domain-specific Adapters (2021.findings-acl)

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Challenge: Existing approaches to ED are limited due to complexity of textual data and domain shift problem.
Approach: They propose to use domain adapter-based Adaptation framework to improve event detection across domains.
Outcome: The proposed framework significantly boosts the performance on target domains.
Modeling Document-Level Context for Event Detection via Important Context Selection (2021.emnlp-main)

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Challenge: Existing methods for Event Detection (ED) do not encode long-range document-level context . e.g., BERT cannot encode long text-level contextual information .
Approach: They propose a method to model document-level context for Event Detection using transformer-based language models.
Outcome: The proposed model can predict event prediction of target sentence in document-level context . the proposed model is effective on multiple benchmark datasets .

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