Papers by Vanessa Yan

1 papers
Unsupervised Cross-Domain Prerequisite Chain Learning using Variational Graph Autoencoders (2021.acl-short)

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Challenge: Existing methods to learn prerequisite relations between concepts require annotated concept pairs during training.
Approach: They propose to use an optimized variational graph autoencoder to learn prerequisite chains in unsupervised manner using an information-rich domain and an information poor domain.
Outcome: The proposed model learns to transfer concept prerequisite relations from an information-rich domain (source domain) to an information poor domain (target domain) the annotated data and resources as well as the code will be made publicly available.

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