Papers by Kailun Lyu

2 papers
From Local Perspective to Global Reasoning: A Neuro-Symbolic Framework for Zero-Shot Relation Extraction (2026.findings-acl)

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Challenge: Existing methods for zero-shot relationship extraction do not distinguish between unseen, semantically similar relations.
Approach: They propose a framework to enable global reasoning across a set of predictions.
Outcome: The proposed framework outperforms existing methods and establishes new state-of-the-art results on widely used datasets.
Re-Cent: A Relation-Centric Framework for Joint Zero-Shot Relation Triplet Extraction (2025.coling-main)

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Challenge: Existing methods to extract triplets from context often decompose into named entity recognition and relation classification, which may introduce error propagation.
Approach: They propose a Relation-centric joint ZSRTE method which leverages unseen relation labels to extract triplets in one go.
Outcome: The proposed method achieves state-of-the-art performance with fewer parameters and does not rely on synthetic data or manual labor.

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