  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.
