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Found 5 papers, 1 papers with code
Uncertainty Quantification on Graph Learning: A Survey
Graphical models, including Graph Neural Networks (GNNs) and Probabilistic Graphical Models (PGMs), have demonstrated their exceptional capabilities across numerous fields.
An Iterative Associative Memory Model for Empathetic Response Generation
Empathetic response generation is to comprehend the cognitive and emotional states in dialogue utterances and generate proper responses.
Exploiting Emotion-Semantic Correlations for Empathetic Response Generation
Based on dynamic emotion-semantic vectors and dependency trees, we propose a dynamic correlation graph convolutional network to guide the model in learning context meanings in dialogue and generating empathetic responses.
Machine Reading Comprehension Using Structural Knowledge Graph-aware Network
Our method dynamically updates the representation of the knowledge according to the structural information of the constructed sub-graph.
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