Large language models (LLMs) can learn to perform a wide range of natura...
Compositional and domain generalization present significant challenges i...
While large language models (LLMs) have demonstrated strong capability i...
We describe a neural transducer that maintains the flexibility of standa...
The importance of building text-to-SQL parsers which can be applied to n...
Natural language is compositional; the meaning of a sentence is a functi...
Despite success in many domains, neural models struggle in settings wher...
Synthesizing data for semantic parsing has gained increasing attention
r...
Semantic parsing aims at translating natural language (NL) utterances on...
The importance of building semantic parsers which can be applied to new
...
We present GraPPa, an effective pre-training approach for table semantic...
When translating natural language questions into SQL queries to answer
q...
Semantic parsing aims to map natural language utterances onto machine
in...
In medical documents, it is possible that an entity of interest not only...
In this work, we propose a novel segmental hypergraph representation to ...
It is common that entity mentions can contain other mentions recursively...