Puneet Mathur, Vlad I. Morariu, Aparna Garimella, Franck Dernoncourt, Jiuxiang Gu, Ramit Sawhney, Preslav Nakov, Dinesh Manocha, Rajiv Jain
| Challenge: | Existing script event prediction frameworks such as ChatGPT and FlanT5 lack the ability to learn long-range dependencies between events. |
| Approach: | They propose a novel script event prediction task which aims to predict the next event from a candidate list of narrative events in long-form documents. |
| Outcome: | The proposed architecture can learn sequential ordering between events at the document scale. |
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proScript: Partially Ordered Scripts Generation (2021.findings-emnlp)
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Integrating External Event Knowledge for Script Learning (2020.coling-main)
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| Challenge: | Recent studies focus on event co-occurrence to solve this problem. |
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An AMR-based Link Prediction Approach for Document-level Event Argument Extraction (2023.acl-long)
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