Zero-Shot Cross-Lingual Abstractive Sentence Summarization through Teaching Generation and Attention
Xiangyu Duan, Mingming Yin, Min Zhang, Boxing Chen, Weihua Luo · 2019
Abstractive Sentence Summarization (AS-SUM) targets at grasping the core idea of the source sentence and presenting it as the summary.It is extensively studied using statistical models or neural models based on the large-scale monolingual source-summary parallel corpus.But there is no cross-lingual parallel corpus, whose source sentence language is different to the summary language, to directly train a cross-lingual ASSUM system.We propose to solve this zero-shot problem by using resource-rich monolingual AS-SUM system to teach zero-shot cross-lingual ASSUM system on both summary word generation and attention.This teaching process is along with a back-translation process which simulates source-summary pairs.Experiments on cross-lingual ASSUM task show that our proposed method is significantly better than pipeline baselines and previous works, and greatly enhances the cross-lingual performances closer to the monolingual performances.We release the code and data at https://github.com/KelleyYin/ Cross-lingual-Summarization.