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 1271–1280 of 4891 papers

TitleStatusHype
A Cascaded Dilated Convolution Approach for Mpox Lesion ClassificationCode0
evS2CP: Real-time Simultaneous Speed and Charging Planner for Connected Electric Vehicles—0
Wait-Less Offline Tuning and Re-solving for Online Decision Making—0
Operator Learning for Robust Stabilization of Linear Markov-Jumping Hyperbolic PDEs—0
Mojito: Motion Trajectory and Intensity Control for Video Generation—0
Stellar parameter prediction and spectral simulation using machine learning—0
From Noise to Nuance: Advances in Deep Generative Image Models—0
Isogeometric Analysis for the Pricing of Financial Derivatives with Nonlinear Models: Convertible Bonds and Options—0
Dynamic-VLM: Simple Dynamic Visual Token Compression for VideoLLMCode1
New keypoint-based approach for recognising British Sign Language (BSL) from sequences—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified