WikiLingua: A New Benchmark Dataset for Cross-Lingual Abstractive Summarization
Faisal Ladhak, Esin Durmus, Claire Cardie, Kathleen R. McKeown · 2020
We introduce WikiLingua, a large-scale, multilingual dataset for the evaluation of crosslingual abstractive summarization systems.We extract article and summary pairs in 18 languages from WikiHow 12 , a high quality, collaborative resource of how-to guides on a diverse set of topics written by human authors.We create gold-standard articlesummary alignments across languages by aligning the images that are used to describe each how-to step in an article.As a set of baselines for further studies, we evaluate the performance of existing cross-lingual abstractive summarization methods on our dataset.We further propose a method for direct crosslingual summarization (i.e., without requiring translation at inference time) by leveraging synthetic data and Neural Machine Translation as a pre-training step.Our method significantly outperforms the baseline approaches, while being more cost efficient during inference. * Equal contribution.