SOTAVerified

Computational Efficiency

Methods and optimizations to reduce the computational resources (e.g., time, memory, or power) needed for training and inference in models. This involves techniques that streamline processing, optimize algorithms, or leverage hardware to enhance performance without compromising accuracy.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1091–1100 of 4891 papers

TitleStatusHype
Beyond Attentive Tokens: Incorporating Token Importance and Diversity for Efficient Vision TransformersCode0
Global Safe Sequential Learning via Efficient Knowledge TransferCode0
GLUSE: Enhanced Channel-Wise Adaptive Gated Linear Units SE for Onboard Satellite Earth Observation Image ClassificationCode0
Hamiltonian Monte Carlo Acceleration Using Surrogate Functions with Random BasesCode0
Geoseg: A Computer Vision Package for Automatic Building Segmentation and Outline ExtractionCode0
Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry DetectionCode0
GFSNetwork: Differentiable Feature Selection via Gumbel-Sigmoid RelaxationCode0
BERT-LSH: Reducing Absolute Compute For AttentionCode0
Geographical Context Matters: Bridging Fine and Coarse Spatial Information to Enhance Continental Land Cover MappingCode0
Supervised Dimensionality Reduction for Big DataCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified