39 citations · 52 across the 2 of their papers we have counts for
3 papers
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.CL2016
Joint Learning Templates and Slots for Event Schema Induction
Lei Sha, Sujian Li, Baobao Chang +1
Automatic event schema induction (AESI) means to extract meta-event from raw text, in other words, to find out what types (templates) of event may exist in the raw text and what ro…