Abstractive Cross-Language Summarization via Translation Model Enhanced Predicate Argument Structure Fusing

By Jiajun Zhang, Yu Zhou, Chengqing Zong. 2016

70 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Molecular Biology, Natural Language Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Molecular Biology

In Natural Language Processing

Citations in the corpus

WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization (2020, background): “Scarcity of cross-lingual summarization data has limited prior work to a few languages, and mostly in the news domain (Wan et al., 2010; Wan, 2011; Yao et al., 2015; Zhang et al., 2016; Wan et al., 2019).”
Ensure the Correctness of the Summary: Incorporate Entailment Knowledge into Abstractive Sentence Summarization (2018, methodology): “Text summarization methods can be categorized into extraction-based methods (Erkan and Radev, 2004; Wan et al., 2007; Cheng and Lapata, 2016; Zhang et al., 2016; Nallapati et al., 2017; Li et al., 2017a) and abstraction-based methods.”
Recent advances in document summarization (2017, background): “Currently proposed solutions include bilingual graph coranking [183] and other approaches inspired by statistical machine translation [205, 213].”
NCLS: Neural Cross-Lingual Summarization (2019, background): “Zhang et al. (2016) propose an abstrac-tive CLS which constructs a pool of bilingual concepts represented by the bilingual elements of the source-side predicate-argument structures (PAS) and the target-side counterparts.”
A Robust Abstractive System for Cross-Lingual Summarization (2019, background): “Zhang et al. (2016) parsed the original English documents into predicate-argument structures that were aligned with their Chinese translations and generated the summary from these structures.”
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.”
Zero-Shot Cross-Lingual Abstractive Sentence Summarization through Teaching Generation and Attention (2019, methodology): “…methods through sentence selection based on translation quality estimation (Wan et al., 2010), sentence ranking based on cross-lingual sentence similarity (Wan, 2011), or abstractive summarization based on phrase pair (Yao et al., 2015) and predicate-argument structure fusing (Zhang et al., 2016).”