Keyphrase generation is the task of automatically predicting keyphrases given
a piece of long text. Despite its recent flourishing, keyphrase generation on
non-English languages haven't been vastly investigated. In this paper, we call
attention to a new setting named multilingual keyphrase generation and we
contribute two new datasets, EcommerceMKP and AcademicMKP, covering six
languages. Technically, we propose a retrieval-augmented method for
multilingual keyphrase generation to mitigate the data shortage problem in
non-English languages. The retrieval-augmented model leverages keyphrase
annotations in English datasets to facilitate generating keyphrases in
low-resource languages. Given a non-English passage, a cross-lingual dense
passage retrieval module finds relevant English passages. Then the associated
English keyphrases serve as external knowledge for keyphrase generation in the
current language. Moreover, we develop a retriever-generator iterative training
algorithm to mine pseudo parallel passage pairs to strengthen the cross-lingual
passage retriever. Comprehensive experiments and ablations show that the
proposed approach outperforms all baselines.

该论文介绍了一种新的情景，名为多语言关键短语生成，并提出了一种基于检索增强的方法来缓解非英语语言中数据短缺的问题，使用检索模型找到相关的英文段落并生成当前语言的关键短语。实验结果表明，所提出的方法优于所有基线模型。