Papers by Hongyao Tu

2 papers
LLM-OREF: An Open Relation Extraction Framework Based on Large Language Models (2025.emnlp-main)

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Challenge: Existing studies focus on building models that can only handle predefined relations . however, their reliance on human annotation limits their practicality .
Approach: They propose an open relation extraction framework that can generalize to new relations not encountered during training.
Outcome: The proposed framework can generalize to new relations not encountered during training.
HCRE: LLM-based Hierarchical Classification for Cross-Document Relation Extraction with a Prediction-then-Verification Strategy (2026.findings-acl)

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Challenge: Existing approaches to cross-document relation extraction (RE) focus on identifying relations between head and tail entities from single sentence or document.
Approach: They propose a hierarchical relation tree-based LLM-based hierarchic classification model for cross-document relation extraction (HCRE) based on predefined relations, the model can perform hierarchically classification level by level.
Outcome: The proposed model outperforms existing baselines and validates its effectiveness.

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