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 471–480 of 4891 papers

TitleStatusHype
CFIS-YOLO: A Lightweight Multi-Scale Fusion Network for Edge-Deployable Wood Defect Detection—0
Enhancing Autonomous Driving Systems with On-Board Deployed Large Language ModelsCode2
Change State Space Models for Remote Sensing Change DetectionCode1
A Signal Matrix-Based Local Flaw Detection Framework for Steel Wire Ropes Using Convolutional Neural Networks—0
Influence Maximization in Temporal Social Networks with a Cold-Start Problem: A Supervised ApproachCode0
Fast-Powerformer: A Memory-Efficient Transformer for Accurate Mid-Term Wind Power Forecasting—0
Robust MPC for Uncertain Linear Systems -- Combining Model Adaptation and Iterative LearningCode1
QAMA: Quantum annealing multi-head attention operator with classical deep learning framework—0
Focus on Local: Finding Reliable Discriminative Regions for Visual Place RecognitionCode1
Mavors: Multi-granularity Video Representation for Multimodal Large Language Model—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified