Papers with MLSUM

2 papers
Neural Label Search for Zero-Shot Multi-Lingual Extractive Summarization (2022.acl-long)

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Challenge: Existing methods to translate sentences to other languages using heuristics are challenging.
Approach: They propose a model that learns hierarchical weights for different sets of labels and applies them to other languages to translate them.
Outcome: The proposed model can translate English datasets to other languages and obtain different sets of labels again using heuristics.
MLSUM: The Multilingual Summarization Corpus (2020.emnlp-main)

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Challenge: Existing biases in multi-lingual datasets are limiting the use of multilingual data in document summarization tasks.
Approach: They present MLSUM, the first large-scale MultiLingual SUMmarization dataset.
Outcome: The proposed dataset contains 1.5M+ article/summary pairs in five different languages.

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