Papers by Zhouji Zhouji

1 papers
Thinking about how to extract: Energizing LLMs’ emergence capabilities for document-level event argument extraction (2024.findings-acl)

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Challenge: Existing models for document-level event argument extraction (D-EAE) lack key feature forgetting and cross-event argument confusion.
Approach: They propose a document-level event argument extraction method based on guided summarization and reasoning that leverages the emergence capabilities of large language models to highlight key event information.
Outcome: The proposed method outperforms baseline models by 1.3% F1 and 1.6% F1 on WIKIEVENTS and RAMS.

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