Papers by Siu Hui

2 papers
Separation and Fusion: A Novel Multiple Token Linking Model for Event Argument Extraction (2024.naacl-long)

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Challenge: Existing methods for event argument extraction (EAE) lack cross-event information and require longer role sequences . et al. (2017): outperforms state-of-the-art methods for EE.
Approach: They propose a separation-and-fusion paradigm to separate the acquisition of cross-event information and fuse it into the argument extraction of a target event.
Outcome: The proposed model outperforms the state-of-the-art models on four widely used datasets.
InteMATs: Integrating Granularity-Specific Multilingual Adapters for Cross-Lingual Transfer (2023.findings-emnlp)

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Challenge: Existing work relies on full-model fine-tuning on large parallel datasets to enhance cross-lingual alignment of MLLMs.
Approach: They propose an approach that integrates multilingual adapters trained on texts of different levels of granularity into multilingual models.
Outcome: The proposed approach improves the performance of multilingual language models on low-resource languages.

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