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Found 5 papers, 1 papers with code
Modeling Dual Period-Varying Preferences for Takeaway Recommendation
Different from traditional recommendation, takeaway recommendation faces two main challenges: (1) Dual Interaction-Aware Preference Modeling.
Translation vs. Dialogue: A Comparative Analysis of Sequence-to-Sequence Modeling
Understanding neural models is a major topic of interest in the deep learning community.
Who Is Speaking to Whom? Learning to Identify Utterance Addressee in Multi-Party Conversations
Previous research on dialogue systems generally focuses on the conversation between two participants, yet multi-party conversations which involve more than two participants within one session bring up a more complicated but realistic scenario.
Learning from Positive and Unlabeled Data with Adversarial Training
Positive-unlabeled (PU) learning learns a binary classifier using only positive and unlabeled examples without labeled negative examples.
Tree2Tree Learning with Memory Unit
Traditional recurrent neural network (RNN) or convolutional neural net- work (CNN) based sequence-to-sequence model can not handle tree structural data well.
