Papers with Deep learning methods

2 papers
Exploiting Document Structures and Cluster Consistencies for Event Coreference Resolution (2021.acl-long)

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Challenge: Existing deep learning models for event coreference resolution are limited in that they cannot exploit important interactions between relevant objects for ECR.
Approach: They propose a deep learning model that groups coreferent event mentions into the same clusters . they use document structures to capture relevant objects for ECR .
Outcome: The proposed model achieves state-of-the-art on two benchmark datasets.
Improving Event Coreference Resolution Using Document-level and Topic-level Information (2022.emnlp-main)

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Challenge: Experimental results show that our model outperforms the SOTA baselines due to the encoding length limitation.
Approach: They propose a longformer-based encoder and an encoder with a trigger-mask mechanism to learn sentence-level embeddings based on local context.
Outcome: The proposed model outperforms the baselines on the KBP 2017 dataset.

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