73 citations · 167 across the 8 of their papers we have counts for
8 papers
Hierarchical Phrase-based Sequence-to-Sequence Learning
Bailin Wang, Ivan Titov, Jacob Andreas +1
We describe a neural transducer that maintains the flexibility of standard sequence-to-sequence (seq2seq) models while incorporating hierarchical phrases as a source of inductive b…
Meta-Learning for Domain Generalization in Semantic Parsing
Bailin Wang, Mirella Lapata, Ivan Titov
The importance of building semantic parsers which can be applied to new domains and generate programs unseen at training has long been acknowledged, and datasets testing out-of-dom…
GraPPa: Grammar-Augmented Pre-Training for Table Semantic Parsing
Tao Yu, Chien-Sheng Wu, Xi Victoria Lin +6
We present GraPPa, an effective pre-training approach for table semantic parsing that learns a compositional inductive bias in the joint representations of textual and tabular data…
RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers
Bailin Wang, Richard Shin, Xiaodong Liu +2
When translating natural language questions into SQL queries to answer questions from a database, contemporary semantic parsing models struggle to generalize to unseen database sch…
Learning Semantic Parsers from Denotations with Latent Structured Alignments and Abstract Programs
Bailin Wang, Ivan Titov, Mirella Lapata
Semantic parsing aims to map natural language utterances onto machine interpretable meaning representations, aka programs whose execution against a real-world environment produces…
Combining Spans into Entities: A Neural Two-Stage Approach for Recognizing Discontiguous Entities
Bailin Wang, Wei Lu
In medical documents, it is possible that an entity of interest not only contains a discontiguous sequence of words but also overlaps with another entity. Entities of such structur…