Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text

@inproceedings{Sun2018OpenDQ,
  title={Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text},
  author={Haitian Sun and Bhuwan Dhingra and M. Zaheer and Kathryn Mazaitis and R. Salakhutdinov and William W. Cohen},
  booktitle={EMNLP},
  year={2018}
}
Open Domain Question Answering (QA) is evolving from complex pipelined systems to end-to-end deep neural networks. [...] Key Method We construct a suite of benchmark tasks for this problem, varying the difficulty of questions, the amount of training data, and KB completeness. We show that GRAFT-Net is competitive with the state-of-the-art when tested using either KBs or text alone, and vastly outperforms existing methods in the combined setting. Source code is available at this https URL .Expand
A General FOFE-net Framework for Simple and Effective Question Answering over Knowledge Bases
VIRTUAL KNOWLEDGE BASE
Differentiable Reasoning over a Virtual Knowledge Base
Question answering over knowledge bases with continuous learning
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References

SHOWING 1-10 OF 55 REFERENCES
Question Answering on Knowledge Bases and Text using Universal Schema and Memory Networks
R3: Reinforced Reader-Ranker for Open-Domain Question Answering
Question Answering from Unstructured Text by Retrieval and Comprehension
Simple and Effective Semi-Supervised Question Answering
Reading Wikipedia to Answer Open-Domain Questions
Weaver: Deep Co-Encoding of Questions and Documents for Machine Reading
YodaQA: A Modular Question Answering System Pipeline
Question Answering over Knowledge Base using Factual Memory Networks
The Web as a Knowledge-base for Answering Complex Questions
...
1
2
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4
5
...