Cross-Language Document Summarization Based on Machine Translation Quality Prediction

By Xiaojun Wan, Huiying Li, Jianguo Xiao. 2010

123 citations recorded by the source corpus.

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Citations in the corpus

WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization (2020, methodology): “(Lim et al., 2004; Orăsan and Chiorean, 2008; Wan et al., 2010) are widely used approaches in prior studies, they are prone to error propagation.”
Zero-Shot Cross-Lingual Abstractive Sentence Summarization through Teaching Generation and Attention (2019, background): “Early explorations on cross-lingual summarization mainly depend on the traditional monolingual summarization methods, and integrate bilingual parallel informations into the monolingual methods through sentence selection based on translation quality estimation (Wan et al., 2010), sentence ranking bas”
NCLS: Neural Cross-Lingual Summarization (2019, methodology): “summary into target language (Lim et al., 2004; Orasan and Chiorean, 2008; Wan et al., 2010).”
Abstractive Cross-Language Summarization via Translation Model Enhanced Predicate Argument Structure Fusing (2016, background): “Pilot studies investigate this task by utilizing only one language side information (source or target language side) [1], [22]–[26].”
A Robust Abstractive System for Cross-Lingual Summarization (2019, methodology): “Wan et al. (2010) describe two approaches: summarize then translate, and translate then summarize.”
Cross-language document summarization via extraction and ranking of multiple summaries (2019, background): “[23] proposed to rank and select sentences by fusing two kinds of sentence-level scores: the informativeness and the quality.”
Global Voices: Crossing Borders in Automatic News Summarization (2019, background): “Previous work on cross-lingual summarization performs evaluation with human judgments (Orsan and Chiorean, 2008), or with automatic metrics and noisy source articles generated by automatic translation systems (Wan et al., 2010; Ouyang et al., 2019).”
Zero-Shot Cross-Lingual Neural Headline Generation (2018, background): “The most related task is cross-lingual summarization [1]–[4], in which existing studies focus only on single sentence extraction or compression.”