Online Sequence-to-Sequence Active Learning for Open-Domain Dialogue Generation
2017-06-28 11:36
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introduction
Seq2Seq drawback: generate short, dull and inconsistent responses.DRL:
reward function: most hand-crafted
this paper propose an end-to-end, neural network based generative conversational model that learns open-domain conversation skills via online interaction with human users.
Model
Offline Two-Phase Supervised Learningresponses are short and dull
use Online Active Learning to tackle this issue
Online Active Learning
interacts with real users and learns incrementally from their feedback at each turn of dialog
datasets: considerably small (300K and 8K
resp.)
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