Papers by Fangzhou Zhai
Script Parsing with Hierarchical Sequence Modelling (2021.starsem-1)
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| Challenge: | Script knowledge is a category of commonsense knowledge that describes how people conduct everyday activities sequentially. |
| Approach: | They propose a hierarchical sequence model and transfer learning to do script parsing with a sequence model that accurately tags script participants. |
| Outcome: | The proposed model improves state of the art of event parsing by over 16 points F-score and, for the first time, accurately tags script participants. |
Zero-shot Script Parsing (2022.coling-1)
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| Challenge: | Existing resources cover only a small number of tasks, limiting its practical usefulness. |
| Approach: | They propose a zero-shot learning approach to script parsing which enables us to acquire script knowledge without domain-specific annotations. |
| Outcome: | The proposed model outperforms a previous model with scenario-specific supervision and achieves 68.1/74.4 average F1 for event / participant parsing. |
Aligning Actions Across Recipe Graphs (2021.emnlp-main)
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| Challenge: | a recipe explains step by step how to cook a dish, but recipes differ in which cooking actions they describe explicitly, how they describe them, and in which order. |
| Approach: | They propose a recipe corpus which annotates cooking steps in recipes at sentence level . they train a neural model to predict recipes on ARA and model it for automatic understanding . |
| Outcome: | The proposed model can predict recipes with fine-grained structural information . it shows that recipes can be explained in different ways, or not at all . |
Story Generation with Rich Details (2020.coling-main)
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| Challenge: | Recent neural story generation systems have been able to produce coherent stories. |
| Approach: | They propose a model that features an outliner, which proceeds the main story line to realize global coherence, and a detailer, which supplies relevant details to the story in a locally coherent manner. |
| Outcome: | The proposed model outperforms baseline models in the informativeness and coherence tests on human participants. |