Weaver: Deep Co-Encoding of Questions and Documents for Machine Reading
Table 5: Document-scale results with training and testing on SQuAD (using the dev set for evaluation). For each architecture, we indicate the setting used for training and testing (single paragraph or full document). The DrQA⋆ model refers to an improved version of DrQA (see section 5.3 for details).
['[EMPTY]', 'Train', 'Test', 'EM', 'F1']
For both models, training on full documents is critical to get good performance on this task. To speed up training of the Weaver model, instead of processing all paragraphs, we pick the paragraph containing the correct answer and sample 5 other paragraphs at random from the document. We take the final softmax across all paragraphs.