Papers with omnivorous pretraining approach
OmniTab: Pretraining with Natural and Synthetic Data for Few-shot Table-based Question Answering (2022.naacl-main)
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| Challenge: | a table-based question answering system requires complex reasoning and alignment between questions and tables. |
| Approach: | They propose a table-based QA model that consumes both natural and synthetic data . they combine retrieval with masking to pair natural sentences with QA . |
| Outcome: | The proposed model outperforms existing models in few-shot and full settings and on WikiTableQuestions. |