Papers by Menghua Lu
Few-shot Table-to-text Generation with Prefix-Controlled Generator (2022.coling-1)
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| Challenge: | Neural table-to-text generation approaches are data-hungry and lack labeled data. |
| Approach: | They propose a prompt-based approach for few-shot table-to-text generation using a task-specific prefix and an input-specific input prefix. |
| Outcome: | The proposed approach is able to generate table-to-text summaries with a few instances and is validated on human, book and song datasets. |