Exploring Sentence Community for Document-Level Event Extraction (2021.findings-emnlp)
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| Challenge: | Existing approaches to document-level event extraction neglect the complex logic structures in long texts. |
| Approach: | They propose a framework that exploits the relationship between sentences to extract multiple events by sentence community detection using graph attention networks. |
| Outcome: | The proposed framework achieves competitive results over state-of-the-art methods on the large-scale document-level event extraction dataset. |
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| Challenge: | Existing methods for document-level event extraction are not effective due to two challenges . existing methods fail to extract events whose arguments spread in multiple sentences . |
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Multi-Document Event Extraction Using Large and Small Language Models (2025.emnlp-main)
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| Challenge: | Existing approaches to multi-document event extraction have limited attention . despite its practical significance, this task has inherent challenges . |
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Document-Level Event Extraction via Information Interaction Based on Event Relation and Argument Correlation (2024.lrec-main)
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| Challenge: | Document-level Event Extraction (DEE) is a vital task in NLP . current approaches overlook intricate relationships among events and subtle correlations among arguments within a document . |
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| Challenge: | Existing approaches for event extraction focus on sentence-level event extraction, but they lack a broader view of the document context. |
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Harvesting Events from Multiple Sources: Towards a Cross-Document Event Extraction Paradigm (2024.findings-acl)
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| Challenge: | Document-level event extraction aims to extract structured information from unstructured text. |
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| Challenge: | Existing methods for document-level relation extraction capture non-local interactions but are not able to capture rich non-linguistic interactions. |
| Approach: | They propose a document-level relation extraction model that empowers relational reasoning across sentences by automatically inducing the latent document- level graph. |
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Anaphor Assisted Document-Level Relation Extraction (2023.emnlp-main)
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| Challenge: | Existing methods for document-level relation extraction are incomplete and lack anaphor for identifying relations between entities. |
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Double Graph Based Reasoning for Document-level Relation Extraction (2020.emnlp-main)
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| Challenge: | Existing methods for document-level relation extraction fail to recognize relations between entities across sentences. |
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CLIO: Role-interactive Multi-event Head Attention Network for Document-level Event Extraction (2022.coling-1)
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| Challenge: | Existing methods for document-level event extraction struggle due to two intrinsic challenges: nested arguments and multiple events. |
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Intra-Event and Inter-Event Dependency-Aware Graph Network for Event Argument Extraction (2023.findings-emnlp)
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| Challenge: | Existing models do not build dependency information among event argument roles . Existing methods do not learn the interactions between different roles based on event structure . |
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