Cross-Lingual Machine Reading Comprehension
Table 3: Zero-shot cross-lingual machine reading comprehension results on Japanese and French SQuAD data. † are extracted in Asai et al. (2018).
['[EMPTY]', '[BOLD] Japanese  [BOLD] EM', '[BOLD] Japanese  [BOLD] F1', '[BOLD] French  [BOLD] EM', '[BOLD] French  [BOLD] F1']
In this paper, we propose a simple but effective approach called SimpleMatch to align translated answer to original passage span. While one may argue that using neural machine translation attention to project source answer to original target passage span is ideal as used in Asai et al. However, to extract attention value in neural machine translation system and apply it to extract the original passage span is bothersome and computationally ineffective. To demonstrate the effectiveness of using SimpleMatch instead of using NMT attention to extract original passage span in zero-shot condition, we applied SimpleMatch to Japanese and French SQuAD (304 samples for each) which is what exactly used in Asai et al.