DeBaTeR adds timestamps into graph recommender embeddings and uses the augmented scores to reweight edges or losses, reporting modest accuracy and robustness gains over existing denoising methods.
Toward s robust neural graph collaborative filtering via structure denoising and e mbedding perturba- tion
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DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation
DeBaTeR adds timestamps into graph recommender embeddings and uses the augmented scores to reweight edges or losses, reporting modest accuracy and robustness gains over existing denoising methods.