Papers with causality existence identification

2 papers
Evaluating Instructively Generated Statement by Large Language Models for Directional Event Causality Identification (2025.findings-acl)

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Challenge: Existing studies focus on identifying existence of causality between two event mentions, but the direction of causalities is crucial for understanding the causal relation.
Approach: They propose to instruct a GLM to generate causality statements and identify directional event causality by evaluating the generated statements.
Outcome: The proposed method significantly outperforms state-of-the-art methods even with fewer training data.
Identifying while Learning for Document Event Causality Identification (2024.acl-long)

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Challenge: Existing studies focus on causality existence, but ignore causal direction.
Approach: They propose a new *identifying while learning* mode for the ECI task that takes care of the causal direction and updates events’ representations for boosting next round of causality identification.
Outcome: The proposed method outperforms the state-of-the-art methods on two public datasets.

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