In a semi-supervised setting, our method of reusing (V)RAE encodings in a reading comprehension framework is effective, with SWEAR-PR reaching an accuracy of 66.5 on 1% of the dataset against last year's state of the art of 71.8 using the full dataset.
these methods require careful configuration and tuning to succeed, and making them more robust presents an excellent opportunity for future work.