160 citations · 192 across the 7 of their papers we have counts for
Showing 2018Show all
3 papers · 1 filter
cs.CL2018★ 6 cited
SQL-to-Text Generation with Graph-to-Sequence Model
Kun Xu, Lingfei Wu, Zhiguo Wang +2
Previous work approaches the SQL-to-text generation task using vanilla Seq2Seq models, which may not fully capture the inherent graph-structured information in SQL query. In this p…
cs.CL2018★ 22 cited
Exploiting Rich Syntactic Information for Semantic Parsing with Graph-to-Sequence Model
Kun Xu, Lingfei Wu, Zhiguo Wang +3
Existing neural semantic parsers mainly utilize a sequence encoder, i.e., a sequential LSTM, to extract word order features while neglecting other valuable syntactic information su…
cs.AI2018★ 160 cited
Graph2Seq: Graph to Sequence Learning with Attention-based Neural Networks
Kun Xu, Lingfei Wu, Zhiguo Wang +3
The celebrated Sequence to Sequence learning (Seq2Seq) technique and its numerous variants achieve excellent performance on many tasks. However, many machine learning tasks have in…