Exploiting Structured Knowledge in Text via Graph-Guided Representation Learning
Table 2: Results on CommonsenseQA for single models.“-” denotes unavailable result, and underlined score is the previous best. ∗IR stands for information retrieval. †GLM is initialized with RoBERTa-large and falls into the last group.
['[BOLD] Method', '[BOLD] Dev', '[BOLD] Test']
A brief introduction to each approach without reference can be found on the leaderboard. Compared to the previous best model RoBERTa+KE which is also trained with an extra in-domain corpus (i.e., OMCS) and uses retrieval during finetuning, our approach achieves 0.8% absolute improvement to deliver a new state-of-the-art result. In addition, GLM based on RoBERTa-large outperforms its respective baseline RoBERTa-large by 2.0%.