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Found 2 papers, 0 papers with code
Contrastive Quantization based Semantic Code for Generative Recommendation
Finally, we train and test semantic code with with generative retrieval on a sequential recommendation model.
Towards Realizing the Value of Labeled Target Samples: a Two-Stage Approach for Semi-Supervised Domain Adaptation
We further propose a consistency learning based mean teacher model to effectively adapt the learned UDA model using labeled and unlabeled target samples.
Semi-supervised Domain Adaptation
Unsupervised Domain Adaptation
