Corpus ID: 218763640

Fluent Response Generation for Conversational Question Answering

@article{Baheti2020FluentRG,
  title={Fluent Response Generation for Conversational Question Answering},
  author={Ashutosh Baheti and Alan Ritter and Kevin Small},
  journal={ArXiv},
  year={2020},
  volume={abs/2005.10464}
}
  • Ashutosh Baheti, Alan Ritter, Kevin Small
  • Published 2020
  • Computer Science
  • ArXiv
  • Question answering (QA) is an important aspect of open-domain conversational agents, garnering specific research focus in the conversational QA (ConvQA) subtask. One notable limitation of recent ConvQA efforts is the response being answer span extraction from the target corpus, thus ignoring the natural language generation (NLG) aspect of high-quality conversational agents. In this work, we propose a method for situating QA responses within a SEQ2SEQ NLG approach to generate fluent grammatical… CONTINUE READING

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 45 REFERENCES

    CoQA: A Conversational Question Answering Challenge

    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    QuAC : Question Answering in Context

    VIEW 6 EXCERPTS
    HIGHLY INFLUENTIAL