Learning to Attend On Essential Terms: An Enhanced Retriever-Reader Model for Open-domain Question Answering
Table 7: Accuracy on multiple-choice selection on ARC, RACE-Open and MCScript-Open.
['Model', 'ARC', 'RACE-Open', 'MCScript-Open']
We compare ET-RR with existing retrieve-and-read methods on both datasets. Recently, finetuning on pre-trained models has shown great improvement over a wide range of NLP tasks. Sun et al. They trained Reading Strategies on the RACE dataset to obtain more auxiliary knowledge and then finetune that model on the ARC corpus. As shown, though Reading Strategies trained on both ARC and RACE dataset outperforms ET-RR, ET-RR outperforms Reading Strategies using only the ARC dataset at training time.