Papers with generation method
Competence-based Question Generation (2022.coling-1)
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| Challenge: | Existing models of natural language understanding rely on question answering and logical inference benchmark challenges to evaluate performance of systems. |
| Approach: | They propose a method to generate CB questions using English cooking recipes . they argue that a broader effort needs to be put on measuring linguistic competencies . |
| Outcome: | The proposed method performs poorly on large pretrained language models until they are provided with additional contextualized semantic information. |
HypoGen: Hyperbole Generation with Commonsense and Counterfactual Knowledge (2021.findings-emnlp)
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| Challenge: | despite its abundance, the computational explorations of hyperboles remain under-explored. |
| Approach: | They propose a sentence-level hyperbole generation method that leverages commonsense and counterfactual inference to generate hyperbolic candidates based on the results. |
| Outcome: | The proposed method generates hyperboles with high success rate, intensity, funniness, and creativity. |
Generation and Extraction Combined Dialogue State Tracking with Hierarchical Ontology Integration (2021.emnlp-main)
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| Challenge: | Current models are not satisfactory for solving out-of-vocabulary problems . current models assume that the task ontology is well defined in advance . |
| Approach: | They propose to enhance the interrelation between slots with masked hierarchical attention. |
| Outcome: | The proposed model yields a significant performance gain over current state-of-the-art model and is more robust to out-ofvocabulary problem compared with other methods. |
Exploring Pre-trained Language Models for Event Extraction and Generation (P19-1)
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| Challenge: | Existing methods to extract event data are laborious to create and limited in size. |
| Approach: | They propose an event extraction model to overcome the roles overlap problem by separating the argument prediction in terms of roles. |
| Outcome: | The proposed method surpasses existing methods on the ACE2005 dataset and improves on the previous methods. |