Papers by Zhilei Hu

3 papers
Semantic Structure Enhanced Event Causality Identification (2023.acl-long)

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Challenge: Existing methods for Event Causality Identification (ECI) capture implicit associations between events, which are difficult because they lack the ability to understand the associations between two events.
Approach: They propose a model that captures the implicit associations between two events and integrates the event-centric structure information into a GNN-based event aggregator.
Outcome: The proposed model improves on three widely used datasets showing that it integrates event-centric and event-associated semantic elements and captures event associations.
Large Language Model-Based Event Relation Extraction with Rationales (2025.coling-main)

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Challenge: Existing methods for ERE rely on large language models, but they face limitations.
Approach: They propose an LLM-based approach with rationales for the ERE task . LLMERE transforms ERE into a question-and-answer task that may have multiple answers .
Outcome: Experimental results show that LLMERE improves over existing methods.

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