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Building open-domain dialogue systems capable of rich human-likeconversational ability is one of the fundamental challenges in languagegeneration. However, even with recent advancements in the field, existingopen-domain generative models fail to capture and utilize external knowledge,leading to repetitive or generic responses to unseen utterances. Current workon knowledge-grounded dialogue generation primarily focuses on personaincorporation or searching a fact-based structured knowledge source such asWikipedia. Our method takes a broader and simpler approach, which aims toimprove the raw conversation ability of the system by mimicking the humanresponse behavior through casual interactions found on social media. Utilizinga joint retriever-generator setup, the model queries a large set of filteredcomment data from Reddit to act as additional context for the seq2seqgenerator. Automatic and human evaluations on open-domain dialogue datasetsdemonstrate the effectiveness of our approach.

Grounding in social media: An approach to building a chit-chat dialogue model