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 2791–2800 of 4891 papers

TitleStatusHype
Fast Algorithms for Quantile Regression with Selection—0
InterroGate: Learning to Share, Specialize, and Prune Representations for Multi-task Learning—0
Deep Neural Network Initialization with Sparsity Inducing Activations—0
LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting—0
Efficient State Space Model via Fast Tensor Convolution and Block DiagonalizationCode0
CFIR: Fast and Effective Long-Text To Image Retrieval for Large CorporaCode0
opp/ai: Optimistic Privacy-Preserving AI on Blockchain—0
DiffuSolve: Diffusion-based Solver for Non-convex Trajectory Optimization—0
Bayesian Off-Policy Evaluation and Learning for Large Action Spaces—0
An FPGA-Based Accelerator Enabling Efficient Support for CNNs with Arbitrary Kernel Sizes—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified