We present a novel approach for structured data-to-text generation that
...
The open-ended Visual Question Answering (VQA) task requires AI models t...
Entities can be expressed in diverse formats, such as texts, images, or
...
A practical text-to-SQL system should generalize well on a wide variety ...
Neural text-to-SQL models have achieved remarkable performance in transl...
Recently, there has been increasing interest in synthesizing data to imp...
There has been great progress in unifying various table-to-text tasks us...
Question answering over knowledge bases (KBs) aims to answer natural lan...
Most recent research on Text-to-SQL semantic parsing relies on either pa...
Relation extraction is an important but challenging task that aims to ex...
The current state-of-the-art generative models for open-domain question
...
In this work, we focus on two crucial components in the cross-domain
tex...
A commonly observed problem with the state-of-the art abstractive
summar...
Compositional reasoning tasks like multi-hop question answering, require...
Most recently, there has been significant interest in learning contextua...
In open-domain question answering, questions are highly likely to be
amb...
We propose an end-to-end approach for synthetic QA data generation. Our ...
Question Answering (QA) is in increasing demand as the amount of informa...
BERT model has been successfully applied to open-domain QA tasks. Howeve...
One of the ubiquitous representation of long DNA sequence is dividing it...
An important goal of online comparison shopping services is to "convert"...