Papers with event extraction methods
Joint Multimedia Event Extraction from Video and Article (2021.findings-emnlp)
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Brian Chen, Xudong Lin, Christopher Thomas, Manling Li, Shoya Yoshida, Lovish Chum, Heng Ji, Shih-Fu Chang
| Challenge: | Existing methods to extract multimedia events from video and text are limited to video and images. |
| Approach: | They propose a task to jointly extract events from video and text documents . they propose 'self-supervised' cross-modal event coreference model and cross-mod transformer architecture . |
| Outcome: | The proposed method achieves 6.0% and 5.8% absolute F-score gain on video-article pairs . the proposed method can resolve coreference and extract multimodal event frames more accurately than existing methods. |
ZSEE: A Dataset based on Zeolite Synthesis Event Extraction for Automated Synthesis Platform (2024.findings-naacl)
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| Challenge: | Automated synthesis of zeolite holds great significance for attaining economic and environmental benefits. |
| Approach: | They propose an event extraction task to mine structural synthesis actions from experimental narratives for modular automated synthesis. |
| Outcome: | The proposed method can significantly expedite automated synthesis of zeolites owing to its machine readability. |
Semi-supervised New Event Type Induction and Description via Contrastive Loss-Enforced Batch Attention (2023.eacl-main)
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| Challenge: | Existing methods for event extraction use annotated event types but are expensive and time-consuming. |
| Approach: | They propose a semi-supervised approach to learning new event types using a masked contrastive loss. |
| Outcome: | The proposed method learns similarities between clusters by enforcing an attention mechanism over the data minibatch. |
Corpus-based Open-Domain Event Type Induction (2021.emnlp-main)
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| Challenge: | Existing event extraction methods require predefined event types and their annotations to learn event extractors. |
| Approach: | They propose to represent each event type as a cluster of predicate sense, object head> pairs. |
| Outcome: | The proposed method can discover salient and high-quality event types on three datasets from different domains. |
HMEAE: Hierarchical Modular Event Argument Extraction (D19-1)
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| Challenge: | Existing event extraction methods classify each argument role independently, ignoring conceptual correlations between different argument roles. |
| Approach: | They propose a Hierarchical Modular Event Argument Extraction model to provide inductive bias from the concept hierarchy of event argument roles. |
| Outcome: | The proposed model outperforms existing methods on real-world datasets and shows that it leverages useful knowledge from the concept hierarchy. |
Reflective Agreement: Combining Self-Mixture of Agents with a Sequence Tagger for Robust Event Extraction (2025.emnlp-main)
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| Challenge: | Existing methods for event extraction are limited in their ability to recall nuanced or rare events. |
| Approach: | They propose a hybrid approach that leverages a self-mixture of agents and a discriminative sequence tagger to resolve ambiguities and enhance overall event prediction quality. |
| Outcome: | The proposed approach outperforms existing state-of-the-art methods across three benchmark datasets. |