BIBI System Description: Building with CNNs and Breaking with Deep Reinforcement Learning

WS 2017  ·  Yitong Li, Trevor Cohn, Timothy Baldwin ·

This paper describes our submission to the sentiment analysis sub-task of {``}Build It, Break It: The Language Edition (BIBI){''}, on both the builder and breaker sides. As a builder, we use convolutional neural nets, trained on both phrase and sentence data. As a breaker, we use Q-learning to learn minimal change pairs, and apply a token substitution method automatically. We analyse the results to gauge the robustness of NLP systems.

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