Learning from Dialogue after Deployment: Feed Yourself, Chatbot!

Pierre-Emmanuel Mazaré
Pierre-Emmanuel Mazaré

ACL (1), pp. 3667-3684, 2019.

Cited by: 0|Bibtex|Views134|DOI:https://doi.org/10.18653/v1/p19-1358
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Other Links: dblp.uni-trier.de|arxiv.org

Abstract:

The majority of conversations a dialogue agent sees over its lifetime occur after it has already been trained and deployed, leaving a vast store of potential training signal untapped. In this work, we propose the self-feeding chatbot, a dialogue agent with the ability to extract new training examples from the conversations it participat...More

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