Papers with Event Semantic Relation Reasoning

2 papers
Event-Centric Question Answering via Contrastive Learning and Invertible Event Transformation (2022.findings-emnlp)

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Challenge: Existing QA frameworks that use event-centric reasoning are lacking.
Approach: They propose a novel QA model with contrastive learning and invertible event transformation . they use an invertable transformation matrix to project event vectors into a common event embedding space .
Outcome: The proposed model achieves 8.4% gain in token-level F1 score and 3.0% gain in Exact Match score on the ESTER dataset.
ESTER: A Machine Reading Comprehension Dataset for Reasoning about Event Semantic Relations (2021.emnlp-main)

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Challenge: Recent event-centric reading comprehension datasets focus mostly on event arguments or temporal relations.
Approach: They propose a machine reading comprehension dataset that leverages natural language queries to reason about the five most common event semantic relations.
Outcome: The proposed dataset shows that current SOTA systems achieve 22.1%, 63.3% and 83.5% for token-based exact-match, **F1** and event-based **HIT@1** scores.

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