Evaluating and Enhancing the Robustness of Dialogue Systems: A Case Study on a Negotiation Agent

NAACL 2019 Minhao ChengWei WeiCho-Jui Hsieh

Recent research has demonstrated that goal-oriented dialogue agents trained on large datasets can achieve striking performance when interacting with human users. In real world applications, however, it is important to ensure that the agent performs smoothly interacting with not only regular users but also those malicious ones who would attack the system through interactions in order to achieve goals for their own advantage... (read more)

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