Mask-filling: Given a sequence of tables T and a question Q with [MASK], what is the word at [MASK].
Q：We provide an extensive evaluation of the span selection pre-training method across four reading comprehension tasks: the Stanford Question Answering Dataset (SQuAD) in both version 1.1 and [MASK]; followed by the Google Natural Qu
T:<C>Dataset Method  SQUAD  SQUAD,<max>2.0<bold>,<C>Dataset Method  SQUAD,<max>1.1<bold>,<C>Model Method  Exact,Dataset BERT BASE,81.22, +SSPT,85.10<bold>, +SSPT - PN,84.94,Dataset BERT  LARGE,84.20, +SSPT,<max>86.86<bold>,<C> Answer  F1,Dataset BERT BASE  BERT BASE,73.86, +SSPT  +SSPT,77.25<bold>, +SSPT - PN  BERT  LARGE,75.48,Dataset BERT  LARGE  +SSPT,<max>79.39<bold>,<C>Model Method  Exact,Dataset BERT BASE,73.29, +SSPT,79.19, +SSPT - PN,79.32<bold>,Dataset BERT  LARGE,78.41, +SSPT,<max>82.07<bold>,<C>Model Method  F1,Dataset BERT BASE,88.52, +SSPT,91.71<bold>, +SSPT - PN,91.60,Dataset BERT  LARGE,90.97, +SSPT,<max>92.75<bold>,<C>Model Facts  Exact,Dataset BERT BASE  BERT BASE,53.15, +SSPT  +SSPT,56.58<bold>, +SSPT - PN  BERT  LARGE,55.99,Dataset BERT  LARGE  +SSPT,<max>57.57<bold>,<C>Model Method  F1,Dataset BERT BASE,76.45, +SSPT,82.31, +SSPT - PN,82.34<bold>,Dataset BERT  LARGE,81.50, +SSPT,<max>85.03<bold>,<C>Model Facts  F1,Dataset BERT BASE  BERT BASE,84.00, +SSPT  +SSPT,85.13<bold>, +SSPT - PN  BERT  LARGE,85.27,Dataset BERT  LARGE  +SSPT,<max>86.17<bold>,<C> Answer  Exact,Dataset BERT BASE  BERT BASE,59.97, +SSPT  +SSPT,63.31<bold>, +SSPT - PN  BERT  LARGE,61.62,Dataset BERT  LARGE  +SSPT,<max>65.87<bold>,Table 6: Dev Set Results on HotpotQA  There should be exactly 7 paragraphs separated by the markdown divider: ***.
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