Papers with Cross-lingual summarization (

3 papers
SumTra: A Differentiable Pipeline for Few-Shot Cross-Lingual Summarization (2024.naacl-long)

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Challenge: Existing approaches to cross-lingual summarization are limited due to limited training data.
Approach: They propose to re-use existing multilingual summarization and translation pipelines to perform cross-lingual summaries in a sequence.
Outcome: The proposed approach outperforms existing methods in many languages with only 10% of the fine-tuning samples.
NCLS: Neural Cross-Lingual Summarization (D19-1)

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Challenge: Existing approaches to cross-lingual summarization divide the task into two steps: summarizing and translation.
Approach: They propose to integrate two related tasks into the training process of CLS under multi-task learning to improve cross-lingual summarization.
Outcome: The proposed framework improves on English-to-Chinese and Chinese-to English CLS human-corrected test sets.
CroCoSum: A Benchmark Dataset for Cross-Lingual Code-Switched Summarization (2024.lrec-main)

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Challenge: Cross-lingual summarization (CLS) has attracted increasing interest due to the availability of large-scale web-mined datasets and the advancements of multilingual language models.
Approach: They propose a dataset of cross-lingual code-switched summaries in Chinese and English . they show that leveraging existing CLS resources does not improve performance .
Outcome: The proposed method does not improve on CroCoSum, indicating the limited generalizability of existing approaches.

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