BlossomRec is a sparse attention mechanism that uses two distinct block-level patterns for long-term and short-term interests, fused by a gated output, to reduce computation in sequential recommendation Transformers.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
verdicts
UNVERDICTED 2representative citing papers
ITS-Mina introduces an all-MLP model with iterative refinement, external attention via learnable memory units, and HHO-tuned dropout that reports state-of-the-art or competitive results on six multivariate time series benchmarks versus eleven baselines.
citing papers explorer
-
BlossomRec: Block-level Fused Sparse Attention Mechanism for Sequential Recommendations
BlossomRec is a sparse attention mechanism that uses two distinct block-level patterns for long-term and short-term interests, fused by a gated output, to reduce computation in sequential recommendation Transformers.
-
ITS-Mina: A Harris Hawks Optimization-Based All-MLP Framework with Iterative Refinement and External Attention for Multivariate Time Series Forecasting
ITS-Mina introduces an all-MLP model with iterative refinement, external attention via learnable memory units, and HHO-tuned dropout that reports state-of-the-art or competitive results on six multivariate time series benchmarks versus eleven baselines.