Neural Skill Transfer from Supervised Language Tasks to Reading Comprehension
Table 1: Results for transferring knowledge from skill tasks. ‘Fine-tuning’: parameters of the skill tasks are fine-tuned during training.‘EM’ shows the results for Exact Match with the gold answers. We show evaluation results on the dev set of SQuAD [35].
['[BOLD] Setup', '[BOLD] Fine-tuning  [BOLD] F-score', '[BOLD] Fine-tuning  [BOLD] EM', '[BOLD] No fine-tuning  [BOLD] F-Score', '[BOLD] No fine-tuning  [BOLD] EM']
Training on the full training set. We do not aim for state-of-the art performance but focus on the impact of injecting skill knowledge. It shows that individual skills and all skills jointly show a noticeable impact in the early training stages compared to a model without skills.