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 3601–3610 of 4891 papers

TitleStatusHype
A Question of Time: Revisiting the Use of Recursive Filtering for Temporal Calibration of Multisensor Systems—0
Radiance Surfaces: Optimizing Surface Representations with a 5D Radiance Field Loss—0
A Rank-SVM Approach to Anomaly Detection—0
Spatial Attention-based Implicit Neural Representation for Arbitrary Reduction of MRI Slice Spacing—0
Architecting Digital Twins for Intelligent Transportation Systems—0
Architectural Fusion Through Contextual Partitioning in Large Language Models: A Novel Approach to Parameterized Knowledge Integration—0
A Real-time Edge-AI System for Reef Surveys—0
A Real-Time Robust Ecological-Adaptive Cruise Control Strategy for Battery Electric Vehicles—0
A Reinforcement Learning Approach for Scheduling Problems With Improved Generalization Through Order Swapping—0
A reinforcement learning strategy for p-adaptation in high order solvers—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified