  Cross-Language Text Summarization (CLTS) generates summaries in a language
different from the language of the source documents. Recent methods use
information from both languages to generate summaries with the most informative
sentences. However, these methods have performance that can vary according to
languages, which can reduce the quality of summaries. In this paper, we propose
a compressive framework to generate cross-language summaries. In order to
analyze performance and especially stability, we tested our system and
extractive baselines on a dataset available in four languages (English, French,
Portuguese, and Spanish) to generate English and French summaries. An automatic
evaluation showed that our method outperformed extractive state-of-art CLTS
methods with better and more stable ROUGE scores for all languages.
