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Found 2 papers, 1 papers with code
Diffusion-based Contrastive Learning for Sequential Recommendation
However, these random augmentation strategies (e. g., mask or substitution) neglect the semantic consistency of different augmented views for the same user, leading to semantically inconsistent sequences with similar representations.
Evolve Cost-aware Acquisition Functions Using Large Language Models
Many real-world optimization scenarios involve expensive evaluation with unknown and heterogeneous costs.
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