Browse State-of-the-Art › Cross-Lingual Abstractive Summarization
Cross-Lingual Abstractive Summarization
9 papers with code · 0 benchmarks · 4 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
4 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
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Most implemented papers archive 2025-07-28
9 shown of 9 papers with code (15 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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1 May 2022 2 repositories listedWe propose the shared task of cross-lingual conversation summarization, \emph{ConvSumX Challenge}, opening new avenues for researchers to investigate solutions that integrate conversation summarization and machine…
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15 May 2023 1 repository listedThis paper introduces PMIndiaSum, a multilingual and massively parallel summarization corpus focused on languages in India.
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22 Mar 2023 1 repository listedBut, for low-resource languages, the scarcity of reference articles makes monolingual summarization ineffective in solving this problem.
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1 May 2022 1 repository listedWhen applied to zero-shot cross-lingual abstractive summarization, it produces an average performance gain of 12.
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23 Apr 2022 1 repository listedCross-lingual summarization (CLS) is the task to produce a summary in one particular language for a source document in a different language.
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16 Dec 2021 1 repository listedLaSE is strongly correlated with ROUGE and, unlike ROUGE, can be reliably measured even in the absence of references in the target language.
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16 Oct 2021 1 repository listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)When applied to zero-shot cross-lingual abstractive summarization, it produces an average performance gain of 12.
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28 May 2021 1 repository listed Syntology ran 6 of 11 samples · 5 unverifiedEmploying one unified decoder to generate the sequential concatenation of monolingual and cross-lingual summaries, MCLAS makes the monolingual summarization task a prerequisite of the cross-lingual summarization (CLS)…
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7 Oct 2020 1 repository listedAs a set of baselines for further studies, we evaluate the performance of existing cross-lingual abstractive summarization methods on our dataset.
Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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