Papers with EAE models
GENEVA: Benchmarking Generalizability for Event Argument Extraction with Hundreds of Event Types and Argument Roles (2023.acl-long)
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| Challenge: | Existing benchmarking datasets for Event Argument Extraction (EAE) cover less than 40 event types and 25 entity-centric argument roles. |
| Approach: | They propose to use a large and diverse EAE ontology to create a semantic role labeling dataset for EAE that incorporates 115 events and 220 argument roles. |
| Outcome: | The proposed ontology concludes with 115 events and 220 argument roles, with a significant portion of roles not being entities. |
BEMEAE: Moving Beyond Exact Span Match for Event Argument Extraction (2025.naacl-long)
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| Challenge: | Event Argument Extraction (EAE) is a complex task that requires deep comprehension of text to accurately identify and classify event arguments. |
| Approach: | They propose a new evaluation metric that integrates deterministic components with a semantic matching component for more accurate assessment. |
| Outcome: | The proposed evaluation metric leads to higher F1 scores and significant changes in model rankings, underscoring ESM’s inadequacy for comprehensive evaluation of EAE. |
Graph Transformer Networks with Syntactic and Semantic Structures for Event Argument Extraction (2020.findings-emnlp)
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| Challenge: | Existing models for Event Argument Extraction fail to exploit semantic structures of sentences to induce effective representations for EAE. |
| Approach: | They propose a novel model that exploits syntactic and semantic structures of sentences to learn more effective sentence structures for EAE. |
| Outcome: | The proposed model improves the performance of the existing models on standard datasets. |
Separation and Fusion: A Novel Multiple Token Linking Model for Event Argument Extraction (2024.naacl-long)
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Jing Xu, Dandan Song, Siu Hui, Zhijing Wu, Meihuizi Jia, Hao Wang, Yanru Zhou, Changzhi Zhou, Ziyi Yang
| Challenge: | Existing methods for event argument extraction (EAE) lack cross-event information and require longer role sequences . et al. (2017): outperforms state-of-the-art methods for EE. |
| Approach: | They propose a separation-and-fusion paradigm to separate the acquisition of cross-event information and fuse it into the argument extraction of a target event. |
| Outcome: | The proposed model outperforms the state-of-the-art models on four widely used datasets. |
Revisiting Event Argument Extraction: Can EAE Models Learn Better When Being Aware of Event Co-occurrences? (2023.acl-long)
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| Challenge: | Recent studies on event argument extraction (EAE) have not taken event co-occurrences into account. |
| Approach: | They propose to reformulate event co-occurrences as a problem of table generation and extend a SOTA prompt-based EAE model into a non-autoregressive generation framework that extracts the arguments of multiple events in parallel. |
| Outcome: | The proposed framework can extract arguments of multiple events in parallel. |