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Found 4 papers, 1 papers with code
Imputing Knowledge Tracing Data with Subject-Based Training via LSTM Variational Autoencoders Frameworks
The paper finally compare the model performance between training the original data and training the data imputed with generated data from non-subject based model VAE-NS and subject-based training models (i. e., VAE and LVAE).
JAMES: Normalizing Job Titles with Multi-Aspect Graph Embeddings and Reasoning
In online job marketplaces, it is important to establish a well-defined job title taxonomy for various downstream tasks (e. g., job recommendation, users' career analysis, and turnover prediction).
MathBERT: A Pre-trained Language Model for General NLP Tasks in Mathematics Education
Due to the nature of mathematical texts, which often use domain specific vocabulary along with equations and math symbols, we posit that the development of a new BERT model for mathematics would be useful for many mathematical downstream tasks.
Classifying Math KCs via Task-Adaptive Pre-Trained BERT
Educational content labeled with proper knowledge components (KCs) are particularly useful to teachers or content organizers.
