39 citations · 115 across the 15 of their papers we have counts for
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cs.CL2017★ 39 cited
Table-to-text Generation by Structure-aware Seq2seq Learning
Tianyu Liu, Kexiang Wang, Lei Sha +2
Table-to-text generation aims to generate a description for a factual table which can be viewed as a set of field-value records. To encode both the content and the structure of a t…
cs.CL2017★ 13 cited
Order-Planning Neural Text Generation From Structured Data
Lei Sha, Lili Mou, Tianyu Liu +4
Generating texts from structured data (e.g., a table) is important for various natural language processing tasks such as question answering and dialog systems. In recent studies, r…
cs.CL2017★ 1 cited
Syntax Aware LSTM Model for Chinese Semantic Role Labeling
Feng Qian, Lei Sha, Baobao Chang +2
As for semantic role labeling (SRL) task, when it comes to utilizing parsing information, both traditional methods and recent recurrent neural network (RNN) based methods use the f…