147 citations · 245 across the 14 of their papers we have counts for
4 papers · 2 filters
Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Training
Peng Shi, Patrick Ng, Zhiguo Wang +5
Most recently, there has been significant interest in learning contextual representations for various NLP tasks, by leveraging large scale text corpora to train large neural langua…
Answering Ambiguous Questions through Generative Evidence Fusion and Round-Trip Prediction
Yifan Gao, Henghui Zhu, Patrick Ng +7
In open-domain question answering, questions are highly likely to be ambiguous because users may not know the scope of relevant topics when formulating them. Therefore, a system ne…
End-to-End Synthetic Data Generation for Domain Adaptation of Question Answering Systems
Siamak Shakeri, Cicero Nogueira dos Santos, Henry Zhu +5
We propose an end-to-end approach for synthetic QA data generation. Our model comprises a single transformer-based encoder-decoder network that is trained end-to-end to generate bo…
Template-Based Question Generation from Retrieved Sentences for Improved Unsupervised Question Answering
Alexander R. Fabbri, Patrick Ng, Zhiguo Wang +2
Question Answering (QA) is in increasing demand as the amount of information available online and the desire for quick access to this content grows. A common approach to QA has bee…