Hierarchical Graph Network for Multi-hop Question Answering
Table 3: Ablation study on the effectiveness of the hierarchical graph on the dev set in the Distractor setting. RoBERTa-large is used for context encoding.
['Model', 'Ans F1', 'Sup F1', 'Joint F1']
Table 3 shows the performance of paragraph selection on the dev set of HotpotQA. In DFGN, paragraphs are selected based on a threshold to maintain high recall (98.27%), leading to a low precision (60.28%). Compared to both threshold-based and pure TopN -based paragraph selection, our two-step paragraph selection process is more accurate, achieving 94.53% precision and 94.53% recall.