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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 3 of 3 1 ClidSum: A Benchmark Dataset for Cross-Lingual Dialogue Summarization ... Wang, Jiaan; Meng, Fandong; Lu, Ziyao. - : arXiv, 2022 BASE Show details 2 A Survey on Cross-Lingual Summarization ... Wang, Jiaan; Meng, Fandong; Zheng, Duo. - : arXiv, 2022 BASE Show details 3 SportsSum2.0: Generating High-Quality Sports News from Live Text Commentary ... Wang, Jiaan; Li, Zhixu; Yang, Qiang; Qu, Jianfeng; Chen, Zhigang; Liu, Qingsheng; Hu, Guoping. - : arXiv, 2021 Abstract: Sports game summarization aims to generate news articles from live text commentaries. A recent state-of-the-art work, SportsSum, not only constructs a large benchmark dataset, but also proposes a two-step framework. Despite its great contributions, the work has three main drawbacks: 1) the noise existed in SportsSum dataset degrades the summarization performance; 2) the neglect of lexical overlap between news and commentaries results in low-quality pseudo-labeling algorithm; 3) the usage of directly concatenating rewritten sentences to form news limits its practicability. In this paper, we publish a new benchmark dataset SportsSum2.0, together with a modified summarization framework. In particular, to obtain a clean dataset, we employ crowd workers to manually clean the original dataset. Moreover, the degree of lexical overlap is incorporated into the generation of pseudo labels. Further, we introduce a reranker-enhanced summarizer to take into account the fluency and expressiveness of the summarized news. ... : Accepted as a short paper in CIKM 2021 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2110.05750 https://dx.doi.org/10.48550/arxiv.2110.05750 BASE Hide details

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