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Efficient Attention Mechanism
MemoryFormer : Minimize Transformer Computation by Removing Fully-Connected Layers
Published:11/6/2024
Transformer architectureEfficient Attention MechanismIn-Memory Lookup TablesReduction of Computational ComplexityMulti-Head Attention Operation
MemoryFormer is a novel transformer architecture that reduces computational complexity by eliminating most fullyconnected layers while retaining necessary multihead attention operations, utilizing inmemory lookup tables and hash algorithms for dynamic vector retrieval, validat
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STORE: Semantic Tokenization, Orthogonal Rotation and Efficient Attention for Scaling Up Ranking Models
Published:11/24/2025
Scalable Ranking ModelsSemantic TokenizationOrthogonal Rotation TransformationHigh-Dimensional Feature SparsityEfficient Attention Mechanism
The paper introduces STORE, a scalable ranking framework addressing representation and computational bottlenecks in personalized recommendation systems through semantic tokenization, efficient attention, and orthogonal rotation.
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Fast Video Generation with Sliding Tile Attention
Published:2/7/2025
Sliding Tile Attention MechanismVideo Diffusion Generation ModelsEfficient Attention MechanismHunyuanVideoComputational Efficiency Optimization
The study introduces Sliding Tile Attention (STA) to reduce computational bottlenecks in video generation, achieving 58.79% Model FLOPs Utilization while decreasing latency to 501 seconds without quality loss, demonstrating significant efficiency improvements over existing method
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