Abductive Reasoning as Self-Supervision for Common Sense Question Answering
Table 1: Performance on SWAG data set
['[BOLD] Supervision', '[BOLD] Approach', '[BOLD] Val.', '[BOLD] Test']
We first evaluate our approach on the SWAG dataset and compare against fully supervised and weakly supervised. We show the performance of fastText to highlight the importance of commonsense knowledge and the abductive reasoning process. FastText models a given text as a bag of n-grams and predicts the probability of each ending being correct or incorrect. This approach is heavily reliant on word embeddings and does not generalize well to this task. It is also interesting to note that our approach outperforms all weakly supervised baselines such as the dual bag of words approach and the SNLI-based approaches. These approaches are the closest related to our approach since they are not trained directly on the SWAG training split.