Papers with Event Temporal Relation Extraction

2 papers
Temporal Cognitive Tree: A Hierarchical Modeling Approach for Event Temporal Relation Extraction (2024.findings-emnlp)

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Challenge: Recent studies focus on locating relative position of event pairs on timeline . hierarchical modeling approach neglects multidimensional information in temporal relation and hierarchy of reasoning.
Approach: They propose a novel hierarchical modeling approach that mimics human logical reasoning by introducing a Temporal Cognitive Tree.
Outcome: The proposed model outperforms existing methods on TB-Dense and MATRES datasets.
GDLLM: A Global Distance-aware Modeling Approach Based on Large Language Models for Event Temporal Relation Extraction (2025.findings-emnlp)

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Challenge: Existing approaches to analyzing large language models are limited by their pre-trained knowledge of Small Language Models(SLMs).
Approach: They propose a global distance-aware modeling approach based on Large Language Models (LLMs) they first present a distance-based graph structure utilizing Graph Attention Network(GAT)
Outcome: The proposed approach significantly improves minority relation class learning ability on two publicly available datasets, TB-Dense and MATRES.

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