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So far we rely on matching questions with the one of existing FAQs.
Pro: fast + reliable answers
Con: does only work for the most common questions
=> We could add an extractive QA model + some trustworthy text datasources to handle the long tail of questions. If there's no good match in the FAQs we could forward the request to this extractive QA model
The text was updated successfully, but these errors were encountered:
We could also think of extractive QA on the CORD-19 dataset. Probably we should then separate in the UI the user groups (general public vs. researchers)
So far we rely on matching questions with the one of existing FAQs.
=> We could add an extractive QA model + some trustworthy text datasources to handle the long tail of questions. If there's no good match in the FAQs we could forward the request to this extractive QA model
The text was updated successfully, but these errors were encountered: