Open domain question answering using Wikipedia-based knowledge model

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How researchers see this paper

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

Reading Wikipedia to Answer Open-Domain Questions (2017, methodology): “The authors of (Ryu et al., 2014) perform open-domain QA using a Wikipedia-based knowledge model.”
Delaying Interaction Layers in Transformer-based Encoders for Efficient Open Domain Question Answering (2020, background): “…time, researchers have been interested in Automatic Question Answering (Woods and WA 1977) to build intelligent search engines and browse large-scale unstructured documents databases such as Wikipedia (Chen et al. 2017; Ryu, Jang, and Kim 2014; Wang et al. 2017; Yang et al. 2019a; Lee et al. 2018).”
Knowledge Aware Conversation Generation with Explainable Reasoning over Augmented Graphs (2019, background): “…texts: In the task of QA, combination of a KG and a text corpus has been studied with a strategy of late fusion (Gardner and Krishnamurthy, 2017; Ryu et al., 2014) or early fusion (Das et al., 2017b; Sun et al., 2018), which can help address the issue of low coverage to answers in KG based…”
Improving Large-Scale Fact-Checking using Decomposable Attention Models and Lexical Tagging (2018, methodology): “In addition, question answering (Dang et al., 2007; Chen et al., 2017a; Ryu et al., 2014; Ahn et al., 2004) and task-oriented dialog systems (Dhingra et al., 7: Full-pipeline evaluation on the test set using k = 2 and th = 0 .”