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 2321–2330 of 4891 papers

TitleStatusHype
Efficient Meta-Learning for Continual Learning with Taylor Expansion Approximation—0
Bivariate DeepKriging for Large-scale Spatial Interpolation of Wind Fields—0
An Efficient FPGA Accelerator for Point Cloud—0
Efficient Malware Detection with Optimized Learning on High-Dimensional Features—0
Efficiently Predicting Protein Stability Changes Upon Single-point Mutation with Large Language Models—0
Efficiently Expanding Receptive Fields: Local Split Attention and Parallel Aggregation for Enhanced Large-scale Point Cloud Semantic Segmentation—0
BitNet b1.58 2B4T Technical Report—0
An Efficient Decomposition Framework for Discriminative Segmentation with Supermodular Losses—0
LREA: Low-Rank Efficient Attention on Modeling Long-Term User Behaviors for CTR Prediction—0
Bit Cipher -- A Simple yet Powerful Word Representation System that Integrates Efficiently with Language Models—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified