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Found 7 papers, 1 papers with code
Dual Latent Variable Model for Low-Resource Natural Language Generation in Dialogue Systems
Recent deep learning models have shown improving results to natural language generation (NLG) irrespective of providing sufficient annotated data.
Adversarial Domain Adaptation for Variational Neural Language Generation in Dialogue Systems
In this procedure, a model is first trained on a source domain data and then fine-tuned on a small set of target domain utterances under the guidance of two proposed critics.
Improving Legal Information Retrieval by Distributional Composition with Term Order Probabilities
In this work, a two-stage method for Legal Information Retrieval is proposed, combining lexical statistics and distributional sentence representations in the context of Competition on Legal Information Extraction/Entailment (COLIEE).
Semantic Refinement GRU-based Neural Language Generation for Spoken Dialogue Systems
Natural language generation (NLG) plays a critical role in spoken dialogue systems.
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