3 citations · 6 across the 8 of their papers we have counts for
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cs.CL2022★ 1 cited
An Understanding-Oriented Robust Machine Reading Comprehension Model
Feiliang Ren, Yongkang Liu, Bochao Li +5
Although existing machine reading comprehension models are making rapid progress on many datasets, they are far from robust. In this paper, we propose an understanding-oriented mac…
cs.CL2022★ 2 cited
Deep Understanding based Multi-Document Machine Reading Comprehension
Feiliang Ren, Yongkang Liu, Bochao Li +7
Most existing multi-document machine reading comprehension models mainly focus on understanding the interactions between the input question and documents, but ignore following two…
cs.CL2022★ 3 cited
A Simple but Effective Bidirectional Framework for Relational Triple Extraction
Feiliang Ren, Longhui Zhang, Xiaofeng Zhao +3
Tagging based relational triple extraction methods are attracting growing research attention recently. However, most of these methods take a unidirectional extraction framework tha…