| Challenge: | Existing approaches to question answering on tabular data have limited capabilities due to ambiguousness inherent to tabular datasets. |
| Approach: | They propose to use large language models to answer questions on tabular data by analyzing tabular tables and detecting ambiguity. |
| Outcome: | The proposed model can detect ambiguity in tabular data and provide an initial ground for a deeper discussion on how to approach it in the age of LLMs. |
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AmbigQA: Answering Ambiguous Open-domain Questions (2020.emnlp-main)
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| Challenge: | Existing open-domain question answering systems assume questions have a single welldefined answer. |
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