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

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Showing 581–590 of 4891 papers

TitleStatusHype
Pan-LUT: Efficient Pan-sharpening via Learnable Look-Up Tables—0
Rethinking Key-Value Cache Compression Techniques for Large Language Model ServingCode1
Tree-Guided L_1-Convex ClusteringCode0
Free Parametrization of L2-bounded State Space ModelsCode0
Adaptive Attention-Based Model for 5G Radio-based Outdoor Localization—0
A Low-complexity Structured Neural Network to Realize States of Dynamical SystemsCode0
CoMatch: Dynamic Covisibility-Aware Transformer for Bilateral Subpixel-Level Semi-Dense Image Matching—0
SU-YOLO: Spiking Neural Network for Efficient Underwater Object DetectionCode0
SpINR: Neural Volumetric Reconstruction for FMCW Radars—0
A Time Splitting Based Optimization Method for Nonlinear MHE—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified