Papers by Xihan Li

1 papers
MEMD: A Diversity-Promoting Learning Framework for Short-Text Conversation (C18-1)

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Challenge: Neural encoder-decoder models tend to generate meaningless and generic responses regardless of what the input text is.
Approach: They propose an easy-to-extend learning framework based on latent vectors to provide training guidance without resorting to extra data or complicating network’s inner structure.
Outcome: The proposed framework improves the quality of generated responses according to automatic metrics and human evaluations, yielding more diverse and smooth replies.

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