Abductive Reasoning as Self-Supervision for Common Sense Question Answering
Table 4: Ablative Studies for our model, where we compare against variations of our approach. We compare different source of knowledge and different student networks.
['[BOLD] Approach', '[BOLD] Val.']
We also perform ablative studies to evaluate our approach by varying the student model and the source of semantic knowledge. We train two student networks other than BERT. We use two strong models as student networks, namely ESIM and Unary LSTM models, which achieve 51.9% and 43.1% respectively on SWAG. We also test the effectiveness of using contextualized interpretations by relying only on the direct semantic relationships between two concepts in the ConceptNet semantic network.